Individual supporters (2024)

EurAI Fellow, Italian representative of IFIP Technical Committee on Artificial Intelligence (TC-12)

EurAI Fellow

EurAI Fellow

EurAI Fellow, Member Academia Europaea, CHI Academy, Leopoldina

IEEE, IET and HEA Fellow, Vice President INNS

EurAI Fellow

EurAI Fellow

IEEE Fellow

EURAI Fellow

EurAI Fellow

EurAI and GI Fellow

head of the ERC project Matryoshka

EurAI Fellow

EurAI fellow

EurAI Fellow

EurAI Fellow

EurAI Fellow

Eur AI Fellow, AAAI Fellow, ACM Fellow, Royal Society Fellow, Royal Academy of Engineering Fellow, Commander of the British Empire

Fellow AAAI, IEEE and EurAI, President IEEE-RAS Society, Member of Leopoldina and Academia Europaea, Member of the Heidelberger Academy of Sciences, ERC Advanced Grant, Gottfried Wilhelm Leibniz Prize

EurAI Fellow

EurAI Fellow

AAAI Fellow, EurAI Fellow, IJCAI past Trustee and President

EurAI Fellow

Fellow IEEE, Past President IEEE-RAS Society

EurAI and Royal Academy of Engineering Fellow

EuRAI Fellow, ACL Fellow

AAAI Fellow, ACM Fellow, EurAI Fellow

EurAI Fellow

GI Member, Chair of FFPA

EurAI Fellow

EurAI Fellow

EurAI Fellow

Fellow AAAI, EurAI and IEEE; ERC Advanced Grant;
IEEE Frank Rosenblatt Prize; Co-director IRIDIA AI Lab

EurAI Fellow

EurAI Fellow, Director of the Intelligent Systems Lab, Dept. of Computer Science and Biomedical Informatics

EurAI Fellow, Member Academia Europea, kM Austrian Academy of Sciences

EurAI Fellow

AAAI and EurAI Fellow

EurAI Fellow

EuRAI Fellow

EurAI Fellow, AAAI member

EurAI Fellow

Member of the Royal Irish Academy

EurAI Fellow, Dean

EurAI and GI Fellow

AAAI an d EurAI Fellow

EurAI Fellow

EuRAI Fellow, was IJCAI president, was IJCAI Trustee

EurAI Fellow

EurAI Fellow

EurAI, IEEE, and IAPR fellow

EurAI Fellow

Director, Centre for Artificial Intelligence Research (CAIR)

EurAI Fellow

EurAI Fellow

Senior Fellow ‘Institut Universitaire de France’

EurAI Fellow, member of Royal Dutch Academy of Sciences, member of Academia Europaea

EuRAI Fellow – IEEE Fellow – IAPR Fellow – Former President of AFIA, French Association of AI

IJCAI Computers and Thought Award; ERC Starting Grant; ERC Consolidator Grant

EurAI Fellow

EurAI Fellow

EurAI Fellow

EuRAI Fellow

AAAI Fellow

EurAI Fellow

Vice-Rector

CB, FREng, EurAI Fellow, Vice-Provost

EurAI Fellow

Fellow of EurAI, IEEE, IET, IFSA, SMIA, Member: Polish Academy of Sciences, Academia Europaea, European Academy of Sciences and Arts, Bulgarian Academy of Sciences, Spanish Royal Academy of Economic and Financial Sciences (RACEF), Finnish Society of Sciences and Letters

EurAI Fellow

AAAI Fellow, ACM Fellow, EurAI Fellow

IEEE Fellow

ACM Fellow, AAAI Fellow, EurAI Fellow, Member of the Academia Europaea

EurAI Fellow

FEurAI, RAEng Chair in Emerging Technologies

EurAI Fellow, Director of the Artificial Intelligence Research Institute, Former IJCAI President and Trustee

Director

IEEE Fellow

EurAI Fellow – Senior Fellow of the Institut Universitaire de France

EurAI Fellow

ECCAI Fellow, CAIAC Felow

EurAI fellow

EurAI fellow

EURAI Fellow

Immediate-Past-President of the International Society on Multiple Criteria Decision Making, Member of the Steering Group on Evolutionary Multicriteria Optimization, Director of the thematic research field at DEMO (Decision Analytics utilizing Causal Models and Multiobjective Optmization) at the Univ. of Jyvaskyla, Finland

EurAI Fellow

Fellow of AAAI and EurAI, Member of Leopoldina and Academia Europaea, Secretary/Treasurer of IJCAI

EurAI Fellow, AAAI member

EurAI Fellow, Member of the Royal Irish Academy, Insight Centre for Data Analytics

Expertise Statistical Machine Learning
Human Behavior modeling from data
Interactive, intelligent systems
Computational Social Sciences
ACM Fellow
IEEE Fellow
EuroAI Fellow
Academic of the Spanish Royal Academy of Engineering
Spokesperson and member of the Panel of Experts for the Spanish Government on AI and Big Data

EurAI Fellow, Spotify

EurAI Fellow

EurAI Fellow
Founding president APPIA
Honoris causa PhD from T.U. Dresden

EurAIi Fellow

EurAI Fellow

EurAI Fellow

EurAI Fellow, member of Academie des technologies

EurAI fellow

EurAI fellow

EurAI Fellow

EurAI board member

Scientific Director

Prof. Dr. (Ph. D.) grad. Ing. Jörg Siekmann
Co-Founder of DFKI, the German Research Centre for AI, (https://www.dfki.de/web)
Saarbrücken , Germany

EurAI Fellow

EurAI Fellow, IRSS Fellow

Fellow of AAAI, EurAI, AISB

Roman Słowiński is a full member of the Polish Academy of Sciences and Academia Europaea.
He has conducted extensive research on methodology and techniques of intelligent decision support where he combines Operational Research and Artificial Intelligence. His particular interest is focused on: addressing robustness issues in decision analysis; ordinal data mining; preference learning; modeling of uncertainty and imprecision in decision problems; rough set theory; fuzzy set theory; evolutionary multiobjective optimization; project scheduling, including multiple category resources, multiple job modes, multiple criteria and uncertainty; decision support in medicine, technology, economics and environmental studies.
Today Roman Słowiński is renown for his seminal research on using rough sets in decision analysis. He started this work in 1983 with the founder of the rough set concept, the late Zdzisław Pawlak, and continued with Salvatore Greco and Benedetto Matarazzo since the early 90’s. He organized the First International Workshop on Rough Set Theory and Applications that took place in Poznań in 1992.
As author or co-author, he has published 14 books and more than 400 articles, including 300 papers in major scientific journals (Web of Science h-index=45, Scopus h-index=55, Google Scholar h-index=82). He advised 26 Ph.D. theses in Operational Research and Computer Science; his 16 former PhD students are professors in academia.
He has been holder of European Chair at the University of Paris Dauphine, and invited professor at the Swiss Federal Institute of Technology in Lausanne, the University of Catania, Polytech’Mons, University of Michigan-Ann Arbor, Yokohama National University, Université Laval-Québec, University of Missouri-Columbia, University of Osaka, Polytech’Tours, Ecole Centrale Paris, and others.
Roman Słowiński is recipient of the EURO Gold Medal (1991), and Doctor Honoris Causa of Polytechnic Faculty of Mons (2000), University Paris Dauphine (2001) and Technical University of Crete (2008). He is also a Honorary Professor of the Nanjing University of Aeronautics and Astronautics (2018).
In 1997 he was given the Edgeworth-Pareto Award by International Society on Multiple Criteria Decision Making and in 2005 he received the Annual Prize of the Foundation for Polish Science – regarded as the highest scientific honor awarded in Poland. In 2016, he received the Scientific Award of the President of the Polish Academy of Sciences. Since 2017, he has been elevated to the grade of IEEE Fellow for “contributions to dominance-based rough set theory, robust ordinal regression and preference learning”. The society of the 19th century Polish positivist Hipolit Cegielski gave him the title of “Outstanding Personage of Organic Work” (2017), and the City Council of Poznań awarded him the title of “Distinguished Citizen of the City of Poznań” (2018).
In December 2018, Roman Słowiński has been elected vice-president of the Polish Academy of Sciences for the term 2019-2022.
Since 1999, he is Coordinating Editor of the European Journal of Operational Research (Elsevier, CiteScore=4,08), a premier journal in Operations Research. In years 1998-2003, he was editor of Decision Analysis Section of the International Journal on Fuzzy Sets and Systems. Currently, he is on editorial board of twenty scientific journals. He is coordinator of the EURO Working Group on Multiple Criteria Decision Aiding, and Past President and Fellow of the International Rough Set Society. Moreover, in years 2009-2013, he has been an expert of the panel (PE6–Computer Science) of the European Research Council.

Scientific Director at German Research Center for AI (DFKI), EG Fellow

EurAI Fellow

EurAI Fellow, Chair of WSTNet – Web Science Trust Network of Research Labs

EurAI Fellow, Founder VUB AI Lab, Founder Sony Computer Science Lab Paris

EurAI Fellow, AAAI fellow

IEEE Fellow, Research Director, IRIDIA AI Lab

EurAI Fellow. IEEE Fellow. ISI elected member

EurAI Fellow, IEEE Fellow and ERC Advanced Grant grantee

EurAI Fellow

Director of the European Research Center for Information Systems (ERCIS), ACM member, Associate Editor of Evolutionary Computation Journal

head of the ERC project AI4REASON

EurAI Fellow, member of the Royal Netherlands Academy for Arts and Sciences

EurAI Fellow

Head of department Artificial Intelligence at University of Groningen, president International Association for AI & Law

EurAI Fellow

EurAI, AAAI and GI Fellow

AAAI Fellow, EurAI Fellow

EurAI Fellow

EURAI Fellow

ACM Fellow, AAAI Fellow, EurAI Fellow, Head of Department of Computer Science

AI Safety, Multimodal AI, Generative AI

Am a –
FELLOW: https://www.thersa.org/
AMBASSADOR: https://www.dkv.global/
SCHOLAR: https://www.emiratesscholar.com/
MEMBER of:
https://aaai.org/
https://bigdatacouncil.com/
https://aicouncil.in
https://www.globalcouncil.ai/
In the COUNCIL of:
https://www.technologyreview.com/
https://hbr.org/

Irving Martinez holds a Ph.D. in Economics and Management, and masters degrees in Innovation & Entrepreneurship, Marketing & Finance. He has over 25 years of academic experience teaching courses like Marketing, Consumer Behavior, Entrepreneurship, AI, and Organizational Behavior at multiple universities in Bolivia. His expertise spans Marketing, Innovation, AI, Entrepreneurship, and Sustainability. He has published articles on topics like AI integration in education, value-based marketing, and entrepreneurial education. Martinez has received recognitions like National Academic Article awards, Good Academic Practices awards, and performance recognitions for his teaching. He serves as a mentor for early-stage entrepreneurs globally and has judged AI, cybersecurity, and advertising competitions. His current interests include AI sustainability, reforesting marketing, and integrating AI in virtual classrooms.

Dear CLAIRE organizers,
I would like to register the Institut de Physique du Globe de Paris (IPGP) as a Green Member of CLAIRE. IPGP is a world-renowned geoscience institute based in Paris, France. Our research spans the Earth and the planets from the core to the most superficial fluid envelopes through observation, experimentation, and modeling. We are also in charge of labeled observation services in volcanology, seismology (both terrestrial and spatial), magnetism, gravimetry, and erosion. We start developing AI and ML activities in various fields of research in geosciences and computational chemistry. We would highly appreciate the opportunity to become an active member of CLAIRE.
Sincerely yours,
Razvan Caracas
Senior Researcher
on behalf of the Institut de Physique du Globe de Paris, Université Paris Cité

– Head of the LISPEN laboratory (multi sites laboratory), which investigate: a) Control, planning and autonomy in industrial Robotics, b) Human-robot interaction and c) decision support for industrial management.
– Senior member IEEE in robotics

Dr. en Filosofía por Cambridge International University. Experto en Roboética. Autor de diversos libros sobre Roboética/IA.

In a few months, I will defend my doctoral thesis on responsible decision-making in a human-IA interaction. I have been a researcher at the DFKI Berlin since November 2023. In the KI-Kompas Inklusiv project, I oversee data protection and data ethics. My interest in CLAIRE is to be part of the CLAIRE SIG ETHICS.

My AI research builds on my earlier research and work in decision support, digital ethics, information ecosystems, and human-computer interaction. I have worked with companies on AI and written reports on AI in regard to these fields since 2019.

HELLO

Personal: BSc Aeronautics and Astronautics. Advisor and Consultant to both EU and non-EU government agencies on digital transformation .

As an AI design studio, we help you make the right choices from the start when developing AI systems by connecting with your target audience. We’re not talking about the visual side of things, nor the technical, but about making something that your audience can connect with in their personal lives. Think of it this way: You might have the fanciest, most technically advanced AI, but if people can’t or won’t use it, what’s the point? Our speciality lies in bespoke and international human-centered research services for AI development.

Chemical Engineer (2000) and holds a MSc in Project Management (2008) by University of Oviedo.
20 years’ experience in innovation management and R&D projects. He started his career in Fundación ITMA (2000), a technology center focused on materials. There he was involved in projects for the development of new coatings for steel. After that, he worked as Innovation Manager in ATECMA (2003), the Spanish Association of Aerospace Industries, where he launched the support service on innovation for Associated. In 2004, He joined Fundación PRODINTEC, a technology centre specialized in industrial design and production. He was part of the initial team in charge of the starting up of the center and he performed functions as Head of R&D Management, Director of Projects and Innovation Management and Director of Operations.
In 2013, he created a company called ICUBE together with other founding partners. ICUBE is a technology-based company oriented to the industrialization of additive manufacturing processes and valorization of innovative technologies and R&D project results.
In October 2014, Pablo Coca joined CTIC, a technology center specialized in Information and Communciation Technologies. Since January 2024 he is CTIC General Director . He is Lead Auditor of R&D Management Systems according to the Spanish standard UNE166002, performing certification audits for the Spanish Association for Standardisation and Certification (AENOR). He is also external evaluator of the European Commission in R&D and innovation Programmes.

Special interest in medical human factors, human-computer-interaction and medical simulation

I hold a PhD in Deep Learning and work as a Senior ML Engineer. I have been concerned with AI Safety for over a decade now and would like to support the idea of a CERN for AI via ClaireAI.

I serve on the boards of and am associated with several organisations involved in deciphering the activities of humanity. I am a Behavioural Health Economist, Author, Speaker, Lecturer at the University of Greenwich, London, CEO of Noimosini, Chief Editor of the Journal of Politics and Ethics in New Technologies and AI and Researcher of LabHEM-University of Piraeus.

I am a mentor with a multifaceted background and compassion I have earned my reputation as a visionary. With publications spanning a wide range of topics (AI, parenting, the environment, Artificial Intelligence, healthcare, and everything in between), I firmly believe in the power of combining different disciplines to arrive at a more well-rounded conclusion perspective. This reflects my firm belief in the power of combining different disciplines to arrive at a more balanced and nuanced view of the topic concerned. Iris has spent the last few years researching and writing about the issues that she believes we will face in the fast-changing world of the future.

I was a college director and have established my own consultancy in Public Affairs. My work has involved collaborations with politicians, diplomats, entrepreneurs, academics, and journalists, including speaking engagements at the UN Headquarters in Geneva. Previously she served as a Global Public Health Lecturer at the University of East London, she has an impressive publication record, including over 15 books, 50 articles, and book chapters in peer-reviewed journals. I am also a member of BIC, of All-Party Parliamentary Group on Artificial Intelligence (APPG AI) UK, APPG Artificial Intelligence, APPG Digital Finance, The INNOVATORS BOARD, Member of the Association for Computing Machinery and ACM Committee on Women, Member of AI for Good, Member of the Board CCB (Creative Commerce Board) of Guildhouse School, London (Boarding School). I am an active Board member of HAPSc, the Board of Academics, the President of the Interdisciplinary Committee of HAPSc, and a member of the Board of Womanitee. She is also a Scientific Associate of the Laboratory of Health Economics and Management (LabHEM) of the University of Piraeus.

I studied Economics at the University of Athens and earned a Master’s in Health Economics and Management, and PhD, in Behavioural Economics, at the University of Piraeus, Together with the continual updating necessary for my business career, I have continued to maintain and widen my knowledge base by undertaking numerous external studies at various institutions including The Karolinska Institute, Harvardx, and MITx.

My breadth of knowledge and research-based approach give me the ability to analyse some of the major issues facing humanity in a fast-changing world.

I believe in equal opportunities, uniqueness, and the normality of imperfection!

Recognition of my contributions includes the Exceptional Women of Excellence/Exceptional Leaders of Excellence award at the Annual Women Economic Forum in March 2020.

Charalampos Z. Patrikakis is a Professor at the University of West Attica (UniWA) on the Design and Implementation of Interconnected Electronic Systems and Services, with emphasis on data collection and processing. He is the Director of Computer Network Services Research laboraTory, Director of the Information Transmission-Processing and Networks Division of the Dept. of Electrical and Electronics Engineering of UniWA, a founding member of THINGENIOUS, a spinoff company of UniWA and the Director of the MSc Program “Artificial Intelligence and Deep Learning”. He has served as advisor to the Deputy Minister of Development in Greece, responsible for issues related to research during 2006-2007. He is currently Editor of IEEE IT Professional Magazine, Computer Society representative at the Steering committee of IEEE Internet of Things Journal, a Senior Member of IEEE, an IEEE Computer Society Distinguished Contributor, Member of the Technical Chamber of Greece, IEEE Computer society Distinguished Visitor and counselor of IEEE Student Branch of UniWA.

I am the Principal Investigator for an NGI-Search-funded project, HeReFaNMi (Health-Related Fake News Mitigation). Recipient of two Best Paper Awards at International Workshops associated with ICIAP (International Conference on Image Analysis and Processing) and AIxIA (Italian Association for Artificial Intelligence). Editorial Member of several International Journals: International Journal of Biomedical Imaging, International Journal of Digital Media Broadcasting, Societal Impacts. Guest Editor of Special Issues in the Journal of Imaging, Applied Sciences, Sensors, Multimedia Tools and Applications.

I am an entrepreneur fascinated by nature and how everything works and believe we can build a better future together with fresh air, less pollution and traffic. My mission is to work on solutions using road data and citizen engagement to improve outside spaces, commutes and quality of life. AI tech is an important partner for what we do.

The Wellbeing Driven Economy proposes a new economic system (paradigm), based on technology, aiming to provide for: the human wellbeing, and the environmental wellbeing. It is based, initially, on an interdisciplinary mix encompassing: Life sciences, AI, and Economics.
Dr. Fernando Andrés Sánchez González supports the CLAIRE vision, but with the side note that AI should aim to provide a good life for all, within the planetary boundaries.

Working in an ai observatory and phd student in ML

Bogdan Okreša Đurić is a postdoctoral researcher and senior teaching assistant at the Faculty of Organization and Informatics, a member of the Artificial Intelligence Laboratory at the Faculty of Organization and Informatics, and the assistant to the ECTS Coordinator, who participates in, or participated in, teaching the following courses in Croatian or English: Data Structures, Databases 1, Knowledge Management, Declarative Programming, Database Theory, Multiagent Systems, Computer Games Development, and Computer Game Development Platforms. His scientific interests can be found in multiagent systems, artificial intelligence, computer games, gamification, and semantic modelling.

Since the beginning of his Master studies, he was active in international activities and promoting international relations: he was an Erasmus student at Karl-Franzens University of Graz (AT), Erasmus intern at Jožef Stefan Institute in Ljubljana (SI), Erasmus+ intern at Elettra Sincrotrone in Trieste (IT), spent some time on research stay at Universitat Politècnica de València in Valencia (ES), and participated in an ITEC course at Centre for Development of Advanced Computing in Noida (IN). These are the experiences he cherishes, and is willing to further develop.

Scientific work in national and international context he considers important, interesting and beneficial, as well as social inclusion and responsibility, along with knowledge transfer and learning.

ORCID: https://orcid.org/0000-0001-5653-6646

I have a PhD in machine learning at Sorbonne University where I have worked on the topic of Sparse rewards through Quality Diversity algorithms.
Currently I am a Senior Research Scientist at Huawei Technologies France where I work on research on Model-Based Reinforcement Learning.
My research interests lie in the field of RL, evolution algorithms and AI-driven control.

– Active in responsible AI and Explainable AI
– Publish in journals as MLj, JMLR, Nature Machine Intelligence, DM&KD, IEEE TKDE
– Author of “Data Science Ethics: Concepts, Techniques and Cautionary Tales” (Oxford University Press)

I am a seasoned PhD researcher with extensive experience in project management and a specialization in the applications of AI in UAVs. I am deeply passionate about exploring the ethical dimensions of AI, particularly in relation to UAV technology.

I earned a PhD in Neuorscience from the University of Bordeaux, France in 2020. I have been fascinated by the human brain and intelligence since the beginning of my scientific training. However, in recent years I have become even more fascinated by our ability to make computers learn human-like reasoning and problem-solving abilities to solve many of our daily life problems, even out-performing us on many tasks. That is why I pursued postdoc and industry positions at the interface of natural and artificial intelligence for the past few years. Now, I work as a data scientist at the Bordeaux Bioinformatics Center mainly focused on the European EOSC4Cancer project. I am bringing my passion and expertise in AI, machine learning and data analytics to the mission of fighting cancer at the grand European (and global) stage.

My ultimate goal is be become part of the European AI community, and bring the power of AI to healthcare and biomedicine…eventually preserving human lives and societies.

I am chief assistant professor at Sofia University. My activities there are in the department of Physical Chemistry but my research interests are mainly oriented to intelligent measurement equipment for Industrial and Laboratory purposes.
I am CEO of Metrology-LAB an R&D company with strong relations to the university.

Artificial Intelligence (AI) Expertise
AI Expertise: Standards
ISO SC42 Artificial Intelligence: KERA, OKER, etc.
IEEE Std 1872.2-2021 Autonomous Robotics (AuR) Ontology
AI Expertise: Projects
ACCRA project (robotics for Ageing). Knowledge Engineering Framework for IoT Robotics Applied to Smart Healthcare and Emotional Well-Being. Amelie Gyrard, Kasia Tabeau, Laura Fiorini, Antonio Kung, Eloise Senges, Marleen De Mul, Francesco Giuliani, Delphine Lefebvre, Hiroshi Hoshino, Isabelle Fabbricotti, Daniele Sancarlo, Grazia D’Onofrio, Filippo Cavallo, Denis Guiot, Estibaliz Arzoz-Fernandez, Yasuo Okabe, Masahiko Tsukamoto. International Journal of Social Robotics 2021. Springer Nature. Special Issue “Behavioral Model for Robot based on brain-inspired AI Cognitive Architecture”. Impact factor: 5.126 in 2020
AI4EU project (via open call). Knowledge Extraction for the Web of Things (KE4WoT) Challenge Owner and ontology catalog for IoT
Designer of the Linked Open Reasoning: http://linkedopenreasoning.appspot.com/
AI Expertise: Ontology-based Reasoning, Semantic Reasoning, etc.
Book Chapter: Reasoning Over Personalized Healthcare Knowledge Graph: A Case Study of Patients with Allergies and Symptoms. Amelie Gyrard, Utkarshani Jaimini, Manas Gaur, Saeedeh Shekarpour, Krishnaprasad Thirunarayan, and Amit Sheth. Elsevier Book: Semantic Models in IoT and e-Health Applications 2022.
SAREF-Compliant Knowledge Discovery for Semantic Energy and Grid Interoperability. Amelie Gyrard, Antonio Kung, Olivier Genest, Alain Moreau. IEEE World Forum on Internet of Things (WF-IoT 2021).
Book Chapter: A Review of Tools for IoT Semantics and Data Streaming Analytics. Martin Serrano and Amelie Gyrard. Book: The Building Blocks of IoT Analytics – Internet-of-Things Analytics. 2016
Sensor-based Linked Open Rules (S-LOR): An Automated Rule Discovery Approach for IoT Applications and its use in Smart Cities. Amelie Gyrard, Martin Serrano, Soumya Kanti Datta, Joao Bosco Jares, Muhammad Intizar Ali. International ACM Smart City Workshop (AW4city) in conjunction with International World Wide Web Conference (WWW 2017).
Multi-Layer Cross Domain Reasoning over Distributed Autonomous IoT Applications Muhammad Intizar Ali, Pankesh Patel, Soumya Kanti Datta, Amelie Gyrard. International Workshop on Very Large Internet of Things (VLIoT 2017) in conjunction with 43rd International Conference on Very Large Data Bases (VLDB 2017), August 28 – September 1 2017, Munich, Germany. Published within the Open Journal of Internet of Things (OJIOT). Research Online Publisher (RonPub). VLDB is ranked as A* conference according to Core conference Portal
Demo paper: Helping IoT application developers with Sensor-based Linked Open Rules. Amelie Gyrard, Christian Bonnet and Karima Boudaoud. International Workshop on Semantic Sensor Networks, in conjunction with the International Semantic Web Conference (ISWC 2014).
AI Expertise: Scientific event coordination/organizer
Scientific event coordination/organizer: Web Intelligence 2019 Demo Track, Applications of Knowledge Representation and Semantic Technologies in Robotics (AnSWeR19) workshop co-located with IROS 2019 (IEEE/RSJ International Conference on Intelligent Robots and Systems) (A Conference), SmartIoT Workshop at Association for the Advancement of Artificial Intelligence (AAAI) 2018, Knowledge Extraction for Web of Things (KE4WoT) Challenge at WWW 2018.

Postdoctoral Researcher in Artificial Intelligence (AI) and Guest Professor at VUB, Academic AI Expert at VAIA.

Member of Slovak Economic Association (SEA, Member @ EEA/European Economic Association & IEA/International Economic Association), IEEE Computer Society (Member, #IEEE, #IEEECS), Slovak Research Center for Artificial Intelligence/Slovak.AI (#SlovakAI), European AI Alliance (European Commission/Futurium), Trustworthy AI – Integrating Learning, Optimisation and Reasoning (TAILOR network), UDSC (United Data Science Communities)/X-Europe Webinars Series & The Python Software Foundation (PSF).

I am a Professor in Computer Science at the University of Naples Federico II, since 2010. My research activities are grounded in the Artificial Intelligence and Formal Methods areas, leading fundamental research in formal methods for the strategic reasoning of reactive and multi-agent systems. One of my main contributions in this area is Strategy Logic, a powerful formalism to reasoning about concurrent multi-agent systems, as well as algorithms and tools to specify, verify and synthesize agents’ strategies.
I am the author of more than 200 scientific publications, most of which appear in top conferences/journals, and collected more than 3000 citations and H-index 31(Google Scholar). I carry out several editorial activities for high-level journals. I have initiated/organized editions of Artificial Intelligence and Formal Methods conferences and workshops, as well as I get regularly invited to participate program committees (more than 100 so far). I have been the principal coordinator of more than 20 research projects under international competitive calls.
I am the founder and the scientific director of the ASTREA (Automated Strategic Reasoning) Laboratory}. Since 2010, ASTREA has had a fundamental role in the dialogue between the communities of Formal Methods, Artificial Intelligence, and Game Theory for what strategic reasoning concerns. In ASTREA, I have supervised Internship, Master, and PhD students, as well as post-doc and Marie-Curie researchers (more than 30 people in total). Many of them are nowadays professors in prestigious university in Italy and abroad.
I have got several awards during my career, including the JPMorgan Faculty Research Award, the Royal Society Award, the Vigevani Research Prize, and Best Paper Awards. Also, some of my PhD and Master students have got prestigious thesis awards, under my supervision.

Kindly provide information for Green Membership for my institution/research group.

After graduation as electrical & electronics engineer (EEE) in 2009, he received his Master’s degree in EEE from Eskisehir Osmangazi University (ESOGU) in 2012. He received his Ph. D. in Control and Command program in EEE from ESOGU in 2018. After his Ph. D. he started to work on in H2020-ECSEL2019-RIA VALU3S project as project manager. In 2021, he started working in the department of software engineering ESOGU as Assistant Professor. He is also vice-director of IFARLAB-DIH and director of ESOGU Software Reliability Laboratory (ESOGU – SRLAB). He finished 3 ROSin Focused Technical Cascade Funding Projects.
He has many experiences as evaluator on Industrial and Academic Open Calls for Turkish Funding Agencies like TUBITAK and KOSGEB. Furthermore, he works several EU Funding project as independent evaluator.
Areas of interest; remaining useful life estimation, manufacturing, robotics, route planning, digital twins, artificial intelligence, software testing, simulation-based testing etc.

Sociologist, Director of the Observatory of Technology Assessment (OAT), member of the Topics Group “Ethical, Legal and Socio-Economic Issues” from the European euRobotics platform. Was invited scientist at Brown University (US), Franhofer ISI, KIT (Germany), McMaster University (Canada) and University of Lorraine (France).

Adjunct Lecturer @ Athens University of Economics & Business. School of Economic Sciences, Department of International & European Economic Studies
I am currently working as:
Postdoctoral Researcher in AI & Bioinformatics @ Department of Fisheries & Aquaculture, School of Agricultural Sciences at the University of Patras
Digital Marketing Director @ OWEB Digital Experience

Areas of interest:
AI
Machine Learning
Data Mining
Digital Strategy
E-Business Development
E-Commerce
Internet of Behaviors (IoB)
User Behavior

I am currently an Associate Professor (Maitre de conférences) at the Engineering School Polytech Nancy,
and associated to research lab: Centre de Recherche en Automatique de Nancy (CRAN) at Université of Lorraine, France since 2018.
I received his MSc. Degree in 2012 and Ph. D degree in Automatic control and Signal Processing in 2015 from Ecole Centrale de Lille, France.
Between 2015 and 2017 I pursued my post-doctoral studies at INSA Toulouse, France and Rolls Royce Technology Centre at University of Sheffield, United Kingdom.
My current research interests include hybrid prognostics, adaptive dynamic programming, reinforcement learning and deep neural networks.

Research area: Image Processing, Machine learning, Pattern recognition, Knowledge Modeling

Generation AI Fellow at the World Economic Forum
W@Privacy Awards 2022 Rising Star nominee
Responsible AI; design justice; participatory design; AI ethics; child participation; children’s rights; data protection
Ethical and responsible design implications within children-AI interactions

https://www.cienciavitae.pt/461F-BC85-69B6

– PI of the ERC ADG COHUBICOL: ‘Counting as a human being in the era of computational law’
– Co-founder of the Journal for Cross-Disciiplinary Research in Computational Law www.journalcrcl.org
– author of OA publication: Law for Computer Scientists and Other Folk (Oxford University Press): https://academic.oup.com/book/33735
– Co-Director of the VUB Research Group on Law Science Technology and Society studies
= In the Hall of Fame of Women in AI Ethics: https://womeninaiethics.org/the-list/hall-of-fame/

With a Bachelor’s Degree in Biomedical Engineering (UVIC-UCC) and a Master’s Degree in Computer Security Engineering and Artificial Intelligence (URV), I have worked for +3 years in R&D EU projects as an AI researcher and, more recently, technical project manager of AI EU projects. I have work in different AI research areas, including circular economy and industry 4.0.

I am a computer scientist working on AI/ML tackling real world challenges and responsible aspects. In particular, my work currently focuses on adaptive learning, fairness-aware learning and explainable AI and on generative AI.

I work mostly in assistive robots with people under rehabilitation. I’ve got a PhD on autonomous robots and a second one on AI. Among other awards, I won the Best European dissertation on AI (ECCAI) and the Best spanish dissertation on Assistive Technologies (COIT/AEIT).

Areas of interest/expertise:
– Multi-Agent Systems
– Organizations, Institutions and Norms
– Deep Learning
– Explainability in Reinforcement Learning

I am an assistant professor (German ‘Juniorprofessor’) of Digital Linguistics at Bielefeld University. In my research I focus on interactive computational models of spoken dialogue and multimodal interaction between humans and humans and machines. I am interested in both theoretical (taking a cognitive science perspective on linguistics interaction) as well as applied aspects of my fields (creating and deploying conversational agents).

My work on ‘communicative listener feedback in human–agent interaction’ received the ‘AAMAS 2018 Best Socially Interactive Agents Track Paper‘ of the 17th International Conference on Autonomous Agents and Multiagent Systems, Stockholm, Sweden.

With over 5 years of experience developing research projects in Data Science and Computer Vision, my career goal is to master best practices, trends, and new technologies, bringing creative ideas to life. This background offers an enormous versatility, showed by an easy adaptation to any innovation project in the Industry 4.0. My main activities include: supervise the Machine Learning team, develop and implement Machine Learning and Decision Support Systems, Data Analysis, write funding proposals for R&D projects with major national companies and research-focused ones.

I am currently a postdoctoral researcher at the ULB in Belgium under a FNRS postdoctoral grant. In my research am investigate collective decision making in social dilemmas that are related to key global problems such as climate change, sustainability, fairness, etc. I combine Evolutionary Game Theory, Behavioral Econmics and Machine Learning to collect data and model how humans behave when facing such high risk problems, and look into how socio-technical systems may steer our decisions, and possible improve our social coordination.

Previously I did my PhD under an FWO SB grant in the Artificial Inteligence Laboratory (VUB, Belgium).

Probability and statistics

I am leading the Learning and Machine Perception group at the computer vision center at the Universitat Autonoma de Barcelona. I have a h-index of 60 and over 15.000 citations. My research areas include incremental learning, lifelong learning, domain adaptation, transfer learning, active learning, computer vision.

I am Assistant Professor in Computer Science at Sapienza University of Rome.

My research interests regard many aspects of formal methods for Artificial Intelligence. In particular, I work on verification and synthesis problems for multi-agent systems, knowledge representation, strategic reasoning, logic, games, and automata theory.

I am a Research Associate at the Dipartimento di Ingegneria Informatica, Automatica e Gestionale. Sapienza University of Rome, working with Prof. Giuseppe De Giacomo on his Advanced ERC project WhiteMech.

I received my Ph.D. degree in 2020, at East China Normal University (ECNU), Shanghai, China, under the supervision of Prof. Geguang Pu.

During my Ph.D., I got the scholarship from Chinese Scholarship Council (CSC) and studied as a visiting Ph.D. student (August 2016 to Feb 2018) at Rice University, under the supervision of Prof. Moshe Y. Vardi.

My main interests are in automated reasoning and formal verification.

BIO
Jurgen Goossens is Associate Professor of Constitutional and Administrative Law at Tilburg University. He is leader of the interdisciplinary NWO-MVI CHAIN project: ‘Blockchain in the network society: transparency, trust and legitimacy by design’ (2020-2024).

Before, he was Assistant Professor of Constitutional Law at Erasmus University of Rotterdam and Postdoctoral Research Fellow at Ghent University. Goossens holds an LL.M. degree from Yale Law School.

His research agenda focuses on constitutional resilience in our hyper-complex and hyper-connected society. He primarily researches the ability of constitutional values, principles, and procedures to cope with the challenges, transformations and threats that come with the increased use of algorithms in administrative decision-making processes and digital network governance. Goossens also regularly embarks on legal educational innovation endeavors .

EXPERTISE
Jurgen’s research agenda includes the identification, design and implementation of the conditions and mechanisms that contribute to constitutional resilience of the legal order to cope with transformations and threats in our hyper-complex and hyper-connected society.

Currently, he focuses on the ability of constitutional values, principles, and procedures to cope with the challenges, transformations and threats that come with the increased use of algorithms in administrative decision-making processes and digital network governance. Goossens pays particular attention to the relation between citizens and public bodies.

AI research (with focus on machine learning and, more specifically, in metalearning) since 1994, as part of the ML group in Porto.

Innovative, Entrepreneurial and Strategy-driven Management Professional and Digital Transformation Evangelist with 18 years of experience. Get thrills in leading large complex global projects to get awarded for my invention of petrol drones.

Research Interests:
AutoML, Machine Learning, Deep Learning, Evolutionary Computation, Signal Processing, Neural Architecture Search, Computer Vision.

SURREY INSTITUTE FOR PEOPLE-CENTRED ARTIFICIAL INTELLIGENCE

Putting people at the heart of AI

Our pan-university institute brings together Surrey’s core AI-related expertise in vision, speech and signal processing, computer science, and mathematics, with its domain expertise across engineering and physical sciences, human and animal health, law and regulation, business, finance and the social sciences.

I am a Professor of AI working also on responsible AI aspects (Fairness, XAI).

* Industrial Senior Software Developer AI for MLOps and Edge AI with focus on computer vision (especially semantic segmentation)
* Self-Employed machine learning researcher in the field of biomedical image data

I fully support Claire network and the philosophy behind it. It is key for Europe to nurture such a community and help it leading to innovative and world-scale companies. As an executive working on Ai projects and an actor of technology financing, I will be honored to help some ideas from Claire network and seed them for the creation of some European startups implementing Human-centric Ai products or any other Ai products that augment human intelligence instead of replacing it.

https://adockhorn.github.io/

IEEE senior member

I’am currently a PhD student at Scuola Normale Superiore and my work will be focused on developing AI tools to tackle problems in biology and bioinformatics and computational chemistry.

I’m enthusiast about the idea of applying what I learned so far about Deep Learning, Graph Neural Networks and social systems to a new set of problems. I hope this experience will produce new insights and methodologies able to foster scientific research and, possibly, impact therapy and diagnosis of cancer. Chiefly, I look forward to deepen my knowledge in topics such as pharmacogenomics, drug discovery and protein design.

Angelo Genovese was born in Benevento, Italy, on February 19th, 1985. He received the B.Sc., M.Sc., and Ph.D. degrees in Computer Science in 2007, 2010, and 2014 respectively, from Università degli Studi di Milano, Italy. From 2014 to 2019 he was a Postdoctoral Research Fellow and since 2015 he is a member of the Industrial, Environmental, and Biometric Informatics Laboratory (IEBIL) at the Università degli Studi di Milano, Italy. He was a Visiting Researcher at the University of Toronto, ON, Canada from June 2017 to August 2017 and from December 2019 to March 2020. Since 2019 he is Assistant Professor at Università degli Studi di Milano, Italy, Department of Computer Science.

His research interests include signal and image processing, pattern recognition, three-dimensional reconstruction, artificial intelligence technologies, design methodologies, and algorithms for self-adapting systems, applied to industrial and environmental monitoring systems and biometric recognition. In the biometrics field, his focuses are on highly usable touch-based and touchless recognition based on palmprint and fingerprint, as well as recognition based on soft biometric traits.

He is an Associate Editor of the Springer Journal of Ambient Intelligence and Humanized Computing (AIHC) and Elsevier Array. He was a Member of the Editorial Committee for the Elsevier Book Trends in Deep Learning Methodologies. He has served as Program Chair/Co-Chair for the IEEE Int. Conf. on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA) (2020, 2019, 2018) and the IEEE Workshop on Environmental, Energy, and Structural Monitoring Systems (EESMS) (2018, 2017).

He is a Member of the IEEE, the IEEE Biometrics Council, the IEEE Computational Intelligence Society Task Force on Deep Learning, and the GRIN (Gruppo di Informatica). He is the Chair of the IEEE Italy Section Systems Council Chapter and the Co-Chair of the IEEE Instrumentation and Measurement Society Technical Commitee TC-22 – Intelligent Measurement Systems.

Dario Rossi is Director of Huawei AI4NET Lab and Director of the DataCom Department at the Paris Research Center, France. Before joining Huawei in 2018, he held Full Professor positions at Telecom Paris and Ecole Polytechnique and was holder of Cisco’s Chair NewNet@Paris. He has coauthored 20+ patents and 200+ papers in leading conferences and journals, that received 9 best paper awards, a Google Faculty Research Award (2015) and an IRTF Applied Network Research Prize (2016). He is a Senior Member of IEEE and Senior Member of ACM.

Filipa Correia received a Ph.D. in Computer Science from the University of Lisbon, Portugal, 2021. She is currently a postdoctoral researcher at LARSYS and INESC-ID. Her multidisciplinary research tackles the intersection of robotics, computer science and social psychology (i.e., human-robot interaction), and it is particularly focused on group dynamics between humans and robots in collaborative scenarios. In the past, she was a teaching assistant in the courses of Artificial Intelligence, Multi-Agents Systems, Society and Computing, and Social Robots & Human-Robot Interaction. She had also been part of two EU Projects, EMOTE and iv4XR. Filipa has scientific contributions as book chapters, journal papers and top-tier conference papers (e.g., RSS, AAMAS, IROS, HRI, ASSETS), and she also did community service as a reviewer and a Program Chair of the HRI Pioneers Workshop. Her work has been widely acknowledged by the scientific community especially within the topics of human-robot group interactions and human-robot teamwork. Two examples of such recognition are her current citation stats and h-index, 324 and 11 respectively, and her attendance at an invitation-only Dagstuhl Seminar (19411).

Dr. Gege Gatt is the CEO of London-based company EBO.AI, an Artificial Intelligence enterprise which enables the automation and personalisation of engagement. He is a digital entrepreneur and IT-Law specialist. He serves as the Vice President of the Malta IT law Association and a specialist examiner at the University of Malta. He’s a Board Member of Humanity 2.0 developed by the Holy See in Rome and a consortium of thought-leaders to identify impediments to human flourishing and then work cross-sector to remove them.

AI expertise in combining logic-based methods with deep learning.
Faculty advisor for an honor society of excellent CS/AI students (http://upe.cvut.cz/)

KR2021 best student paper award

In 2011 I got my PhD with honors at UJI and my Dr.-Ing. title at Universität Bremen (UBremen), Germany (double Dr. degree). At the last stage of my PhD (2010-2011) I carried out industry technology transfer: I was a research engineer at the enterprise Cognitive Robots SL where I applied some results of my PhD thesis to the automation of scrubber machines and automatic mosaic assembling.

In 2012, as a postdoc, I got a position in open competition funded by the Excellent Initiative at the University of Bremen. In 2013, I was awarded a Marie Curie Intra-European Fellowships for Career Development based on scientific CV and research proposal which I conducted at Bremen Spatial Cognition Center (BSCC). In 2015, I got a 4-year Independent Post-Doc position funded by the Excellent Initiative at University of Bremen. At University of Bremen, 80% of my time was dedicated to research and 20% to teaching seminars about „Qualitative Descriptors and Computational Applications (QDCA)” and “Ethics for social robotics“. I developed teaching materials, gave lectures, supervised practical courses and evaluated exams. At BSCC I started and directed the Spatial Reasoning Games research team. I was also Junior Fellow at Hansewissenschaftkolleg of Advanced Studies at Delmenhorst, Germany (2015-2017).

In 2020, I was awarded a tenure-track Ramon-y-Cajal professorship by the Spanish Ministry of Science, and currently I am carrying out research and teaching courses at University Jaume I (UJI), Castellón, Spain.

My research expertise lies in Qualitative Spatio-Temporal Reasoning (QSTR) applied to robotics and to ambient intelligent systems. Recently I lead a new research line on defining qualitative models for solving spatial reasoning challenges to help people to improve their spatial cognition skills. Through all my research experience, I developed a multidisciplinary background which, apart from Qualitative Reasoning, Knowledge Representation techniques and Human-Machine Interaction, also includes Machine Learning, Colour Cognition, Bioinformatics, Geographic Information Systems and Creative and Spatial Problem Solving.

I am a member of the European Association for Artificial Intelligence (EURAI) and secretary at the main board of Catalan Association for Artificial Intelligence (ACIA).

Director of KIT-Lab (Knowledge and Information Technology Laboratory, founded in 2004
Recipient of Informatics Europe Prize Best Practices in Education Award 2019
Senior IEEE Member

Former Executive Committee Member of European Network of Excellence in AI Planning
Former Executive Committee Member of AI*IA, the Italian Association for Artificial Intelligence, AIxIA

Areas of interest:
Machine Learning & Deep Learning
Evolutionary Computation & Optimization
Affective Computing
Complex Network Analysis
AI Planning
Education and AI

I’m leading the institute of Electrical engineering, that is active in applied research related to digital sustainable energy systems, edge AI, active assisted living, AI for vision systems and robotics. My personal research area is in the digitalization of power systems.

I am Postdoctoral Researcher in the Social web, intelligent and distributed systems engineering (SoWIDE) Group at the Department of Engineering and Architecture (DIA) of the University of Parma.

Since September 2021 I serve as an adjunct professor at the Department of Engineering and Architecture teaching Big Data and Business Intelligence/ Introduction to Artificial Intelligence.

I received the Ph.D in Information Technologies (2021) and the Master Degree in Computer Engineering (2017) both at the University of Parma.

In 2019 I have been Visiting Researcher at the Center for Applied Optimization (CAO) at the Herbert Wertheim College of Engineering of the University of Florida (United States)

My research activity is focused on:

Machine Learning and Deep Learning

Natural Language Processing

Network Science and Graph Data Mining

Fintech technologies

Social Networks

Predictive Maintenance

I’m an enthusiast technologist with nearly 20 years of sales and business development experience. At the beginning of my career I began working as computer engineer for several multinationals and organisations, such Telefonica or the Spanish Economic and Commercial Office in Warsaw. During the last 15 years I’ve been developing management functions at Indra, both nationwide and internationally.

Academically I’ve been focused on combining technical and executive training, having a Master in International Business Management (MBA) from the Autonomous University of Barcelona, leadership courses from IESE Business School and recently a MSc in Research in Advanced Artificial Intelligence (AI).

I’m interested in the contribution that technologies such AI, Big Data or IoT cause in the digital transformation in many different and diverse areas, including Transport, Defence or Logistics among others.

I’m motivated to assume professional challenges, contributing with my experience in the achievement of business objectives, especially in the technological field.

Engineer of bimedical electronics, specialised in fractal and nonlinear analysis of electrophysiological data, turned PhD Neuroscientist, focused on data-driven computational psychiatry, mailnu depression early detection and prediction, CVD risks detection and remote monitoring of outpatients. I strongly advocate for early detection, prevention and personalized approach, together with Bayesian approach, and active inference applications.

Victoria López is Associate Professor at Cunef University in Madrid, Spain. She has received her PhD in Computational Mathematics and Artificial Intelligence from Polytechnic University of Madrid. She has also received her bachelor degree in Mathematics from Complutense University of Madrid.
She served as head of the G-TeC research group at Faculty of Informatics at Complutense University in Spain. Her research interests are Big Data in Healthcare and Social Sciences. In this way, she served as head of WAP Madrid Salud Project (among others) and at present, she is leading the project Bip4Cast (a big data integration for prediction of a crisis of bipolar patients https://bip4cast.org/). She is also head of the analytics group G-TeC within the project SocialBigData-CM devoted to monitoring and analysis of social change from Big Data (http://socialbigdata.transyt-projects.com/objetivos/english/).

Dr Monique Calisti, CEO of Martel Innovate, is a passionate entrepreneur and ICT expert featuring a digital soul and consolidated hands-on experience in research and innovation funding, strategic consulting, training, communication, social media marketing, as well as business development of sustainable and innovative software solutions across several industry segments.

Specialized in European Commission funding, with extensive domain knowledge in Artificial Intelligence and Next Generation Internet technologies (IoT, 5G, Cloud/Edge, etc.), Monique helps our customers and partners in developing effective and agile innovation strategies and plans. She has been recently appointed as member of the Board of Directors of ADRA – the AI, Data and Robotics European Partnership.

Monique has recently founded the non-profit association Digital for Planet – D4P that works to support the design, development and adoption of innovative and sustainable digital technologies, systems and solutions empowering people, communities and both public and private organisations to address the major social, economic and environmental challenges humanity must face.

Dr Calisti has been serving the European Commission as expert evaluator and reviewer for many years, and is currently the Director of the EU Next Generation Internet Outreach Office and Coordinator of the European Next Generation Internet of Things project.

In the last 20 years, Monique has been speaker and moderator at several major scientific, technology and policy events, she authored and edited many professional publications and many R&D project proposals and served as Program Committee member of several international conferences.

Monique holds a Ph.D. in Artificial Intelligence from the Swiss Federal Institute of Technology of Lausanne, Switzerland, and a Ph.D. in Telecommunications Engineering from the University of Bologna, Italy.

Sebastiano Panichella is a passionate Computer Science Researcher at the Zurich University of Applied Science (ZHAW). He received the PhD in Computer Science from the University of Sannio (Department of Engineering) in 2014 defending the thesis entitled ”Supporting Newcomers in Open Source Software Development Projects” (PDF). For more information have a look on his short CV or long CV.

His main research goal is to conduct industrial research, involving both industrial and academic collaborations, to sustain the Internet of Things (IoT) vision, where future “smart cities” will be characterized by millions of smart systems (e.g., cyber-physical systems such as drones, and other autonomous vehicles) connected over the internet, composed by AI-components, and/or controlled by complex embedded software implemented for the cloud.

His research interests are in the domain of Software Engineering (SE), cloud computing (CC), and Data Science (DS): DevOps (e.g., Continuous Delivery, Continuous integration), Machine learning applied to SE, Software maintenance and evolution (with particular focus on Cloud, mobile, AI-based, and Cyber-physical applications), Mobile Computing. Moreover, he is promoting DS research on “Summarization Techniques for Code, Changes, and Testing”. He authored or co-authored more than seventy papers appeared in International Conferences and Journals. These research works involved studies with industrial and open projects and received best paper awards or best paper nominations . He supervised (or co-supervised) 11 undergrad students, 12 MSc students and currently/recently 9 PhD students (6 of them during the postdoctoral experience at the University of Zurich), and 5 research assistants. He serves and has served as a program committee member of various international conference (e.g., ICSE, ASE, FSE, ICSME, etc.). Dr. Panichella was selected in 2019 as one of the top-20 (second in Switzerland) Most Active Early Stage Researchers Worldwide (results reported by the JSS journal) in SE.
Dr. Panichella was selected In 2021 as one of the top-20 Most impactful SE researchers Worldwide (results reported by the JSS journal) He is Editorial Board Member of Journal of Software: evolution and process (JSEP). He is also Review Board member of the EMSE journal. See the blogpost dedicated to the event.

Economics of AI, Ethics and Governance of AI

Dr. Hervé PANETTO is a Professor of Enterprise Information Systems at the University of Lorraine, TELECOM Nancy. He is member of the Academy of Europe (Academia Euroaea) and Fellow of the AAIA (Asia-Pacific Artificial Intelligence Association). He conducts research at the Research Centre for Automatic Control (CRAN), Joint Research Unit with CNRS, where he is managing a project on the use of ontology and other AI-based techniques for formalising models related to the interoperability of cyber-physical production systems. He has been involved in European projects including IMS FP5-IST Smart-fm project (awarded by IMS) and the FP6 INTEROP NoE. He is author or co-author of more than 150 papers in the field of Automation Engineering, Enterprise Modelling and Enterprise systems integration and interoperability. He is Vice-Chair of the IFAC Technical Committee 9.3 on Control for Smart Cities. He received the IFAC France Award in 2013, the INCOSE 2015 Outstanding Service Award and the IFAC 2017 Outstanding Service Award. He is General Co-chair of the OTM Federated conferences. He is member of the Editorial Board or Associate Editor of various journals of the domain. He is the Chairman of the IFAC French National Member Organization (NMO).

Philosophy of Law

ASR, NLP, multilingual, multiplatform, multimodal information retrieval, disaster communication, security/defense-related aspects of AI

Member of the Commission Expert Group on Artificial Intelligence (AI) and Data in Education and Training
https://ec.europa.eu/transparency/expert-groups-register/screen/expert-groups/consult?do=groupDetail.groupDetail&groupID=3774

Interests in machine learning for image, video, genome and speech analysis

Image recognition techniques, deep learning architectures, expert systems, AI for sustainability, AI ethics

I am a researcher in data science and artificial intelligence. My interests encompass data representations for artificial intelligence and responsible data science, including aspects such as responsible data management, transparency and explainability, with a human-centred focus.

machine learning in graphs, founding co-chair of computational social science working group of German Informatics Society (GI e.V.)

I lead a research group on the topic of public interest AI. We investigate the this topic as a political concept but also produce several AI prototype to proof our concept and reiterate in the process.

I major in optimization in the field of engineering, such as transportation, and vessel routing problem for marine debris collection.

Andrea Renda is a Senior Research Fellow and Head of the CEPS Unit on Global Governance, Regulation, Innovation and the Digital Economy (GRID). He is Part-Time Professor of Digital Policy at the School of Transnational Governance of the European University Institute, in Florence (Italy), where he teaches a course on AI Policy. He is a non-resident Senior Fellow at Duke University’s Kenan Institute for Ethics and was Adjunct Professor of Law and Economics at Duke Law School (United States) for Academic Year 2016/2017. He is also Visiting Professor of Competition Policy and the Digital Economy at the College of Europe in Bruges (Belgium). He is a Fellow of the World Academy of Arts and Science, a CITI Fellow at Columbia University’s Centre for Tele-Information and a member of the European Parliament’s STOA International Advisory Board. His current research interests include regulation and policy evaluation, regulatory governance, innovation and competition policies, sustainable development, innovation policy, and the ethical and policy challenges of emerging digital technologies, in particular Artificial Intelligence. A very prolific author and keynote speaker, Andrea provides regular advice to several institutions, including the European Commission, the European Parliament, the OECD, the World Bank, the Inter-American Development Bank, and many more. He was the main author of key studies on better regulation for the European Commission, the OECD, the ILO and the World Bank. He sits in the Board of the journals Telecommunications Policy (Elsevier), and European Journal of Risk Regulation (Cambridge). He was a member of the EU High Level Expert Group on Artificial Intelligence; member of the advisory group on Economic and Societal Impacts of Research (ESIR), for the European Commission, DG Research and Innovation; and member of the Expert Group on “Smart Specialisation Strategies for Sustainability” (S4) at the European Commission, DG Joint Research Centre. He is the Co-director of the Brookings/CEPS Forum for Global Cooperation on AI. Andrea is a member of the STOA International Advisory Board, supporting the new Centre4AI at the European Parliament. He is also a member of the OECD Network of Experts on AI; and a former member of the Task Force on AI of the Italian Ministry of Economic Development.

My research activity focuses mainly on the themes of Artificial Intelligence and Data Management about techniques and applications of machine learning and recommender systems. Recently, my attention has shifted to exploiting the information encoded within Big Data datasets, such as those available thanks to the Linking Open Data initiative, to create content-based recommendation engines (content-based) or hybrid ones. On personalized information access and the modeling of user preferences, I have recently proposed innovative solutions that combine and integrate different aspects, solutions, and techniques from Artificial Intelligence.
Of great interest to my research is the security of Artificial Intelligence systems with particular reference to Adversarial Machine Learning.
Initially, my research was dedicated to solving theoretical and practical problems in distributed scenarios of resource retrieval and automatic reasoning. In order to verify the validity of the obtained results, these have consistently been implemented and tested in different application domains such as e-commerce, business process management, Web Service discovery, and decision support systems for skills management in recruitment agencies. Subsequently, guided by the results achieved in electronic commerce, my attention shifted to studying new ways to combine knowledge representation techniques and automatic reasoning, both to automatic negotiation between rational agents with preferences and to ubiquitous scenarios and protocols.

I am an auditor for national and international research projects related to my research topics, for high-level international journals and conferences in the fields of Artificial Intelligence, Machine Learning, Semantic Web, and Recommender Systems.

Awards
– Recipient of the Best Paper Award at the 3rd Workshop on Adversarial Learning Methods for Machine Learning and Data Mining @ KDD 2021 with the paper “Understanding the Effects of Adversarial Personalized Ranking Optimization Method on Recommendation Quality”
– Recipient of the Best Research Student Paper Award at the 18th International Semantic Web Conference (ISWC 2019) with the paper “How to make latent factors interpretable by feeding Factorization machines with knowledge graphs”
– Reference tutor for the international IBM Ph.D. Fellowship award for the year 2015.
– Winner of the HP Labs Innovation Research Program 2011 Award with the “Semantic Expert Finding for Service Portfolio Creation” project. The project also obtained funding for the year 2012.
– Recipient of the Best Paper Award at the 8th International Conference on Semantic Systems (I-Semantics 2012) with the paper “Linked Open Data to support Content-based Recommender Systems”
– Recipient of the Best Workshop Paper Award at the 10th International Conference on Web Engineering (ICWE 2010) with the paper “Semantic wonder cloud: exploratory search in DBpedia”
– The paper “A unified framework for non-standard reasoning services in description logics” was selected in a shortlist of seven articles for the Best Paper Award (607 submissions – acceptance percentage: 22%) at the 19th European Conference on Artificial Intelligence – ECAI 2010
– Second place in the Business Idea Contest co-located with the 2nd Annual European Semantic Technology Conference (ESTC 2008)
– Recipient of the Best Theme Paper Award at the 9th International Conference on Electronic Commerce (ICEC 2007) with the paper “RFID meets Bluetooth in a semantic-based u-commerce environment”
– Recipient of the Best Paper Award at the Joint 8th IEEE Conference on E-Commerce Technology (CEC ’06) and 3rd IEEE Conference on Enterprise Computing, E-Commerce and E-Services (EEE’ 06) with the paper “Concept covering for automated building blocks selection based on business processes semantics “
– Recipient of the Best Paper Award at the 6th International Conference on Electronic Commerce (ICEC 2004) with the paper “Concept Abduction and Contraction for Semantic-based Discovery of Matches and Negotiation Spaces in an E-Marketplace”

Invited reports
– Tutorial at the 13th ACM International Conference on Web Search and Data Mining with the talk “Adversarial Machine Learning in Recommender Systems”.
– Tutorial at the 14th Extended Semantic Web Conference with the talk “Linked Open Data for Semantics-Aware Recommender Systems”.
– Keynote Speaker at the 3rd International Workshop on Knowledge Discovery in the Web with the talk “Recommender Systems: Models, Challenges, Solution”.
– Keynote Speaker at the 1st International Workshop on Keyword-based Access and Ranking at Scale with the talk “From Text to Knowledge Graphs to Recommender Systems”.
– Tutorial at the 16th International Conference on Web Engineering with the talk “Recommender Systems meet Linked Open Data”.
– Tutorial at the 10th Summer School on Ontology Engineering and the Semantic Web with the talk “Feeding Recommender Systems with Linked Open Data”.
– Keynote Speaker at the 6th International Conference on Web Reasoning and Rule Systems (RR 2012) with the speech “Semantic Matchmaking and Ranking: Beyond Deduction in Retrieval Scenarios”.
-Invited seminar at HP Labs in Palo Alto with the talk “Handling preferences in the Semantic Web”.
-Keynote Speaker at the 11th International Conference on Electronic Commerce and Web Technologies (EC-Web 2010) with the talk “Electronic Markets, a look behind the curtains: how can semantic matchmaking and negotiation boost e-commerce?”

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We support and lead you all the way on your AI journey. From initial AI opportunity mapping to development and implementation of models, offering you full lifecycle support in our AI platform Grace. We help you regardless of your organization’s AI maturity level and ambitions. Real business value is achieved only once an organization has its models in production, delivering insights and predictions to all corners of the organization.

immunogenetics / immunoinformatics

Head of AI Research Group

https://scholar.google.co.uk/citations?user=-tI15hMAAAAJ&hl=en

Faculty, AI and Machine Learning, Northeastern University – Silicon Valley campus USA
Board Director – BigML Inc (Machine Learning Platform technology company)
Board Director – Arowana International ASX:AWN

Professor of Public Administration and Digitalisation

We develop electronics smart device with embedded Deep Learning Algorithms

I am a researcher in the field of AI, mostly working on the theory side of multi-agent learning and its applications to AI for Social Good. I am also a dedicated educator whose goal is to bring AI to a wider audience, with a focus on its topics related to safety, ethics, fairness, and human-agent collaboration.

Some of my awards and recognitions:

Research:
IJCAI 2019 Early Career Spotlight Talk (invited)
Vice-Chancellor’s Award 2018 (Southampton)
Royal Society’s Kan Tong Po Visiting Fellowship 2017
University of Southern California’s CAIS Visiting Fellow 2017
Runner-up – CPHC/BCS PhD Dissertation Award (Best Computer Science PhD thesis in the UK) in 2012/2013
Honourable mention – ECCAI PhD Dissertation Award (Outstanding European PhD thesis in artificial intelligence) in 2012
Honourable mention – AAAI 2012 Outstanding Paper Award
Runner-up – ECAI 2012 Best Student Paper Award

Teaching:
Dean’s Award 2017 (Faculty of Physical Sciences and Engineering, Southampton)
Most Engaging Lecturer in 2016 (Southampton)

– Professor of Finance and machine learning at IESEG
– Expertise in neural networks (time series analysis) with CNN, LSTM, ResNet…

AI in healthcare

Hi,
I am a legal consultant specialised in data (copyright, blockchain and data protection) with a strong interest on AI. I hope i can help CLAIRE.
Axel Beelen

Prof.dr.ir. Wil van der Aalst is a full professor at RWTH Aachen University leading the Process and Data Science (PADS) group. He is also part-time affiliated with the Fraunhofer-Institut für Angewandte Informationstechnik (FIT) where he leads FIT’s Process Mining group. His research interests include process mining, Petri nets, business process management, workflow management, process modeling, and process analysis. Wil van der Aalst has published over 800 articles and books and is typically considered to be in the top-15 of most cited computer scientists with an H-index of over 155 and more than 110.000 citations. Next to serving on the editorial boards of over ten scientific journals, he is also playing an advisory role for several companies, including Celonis, Fluxicon, and UiPath. Van der Aalst is an IFIP Fellow, IEEE Fellow, ACM Fellow, and received honorary degrees from the Moscow Higher School of Economics (Prof. h.c.), Tsinghua University, and Hasselt University (Dr. h.c.). He is also an elected member of the Royal Netherlands Academy of Arts and Sciences, the Royal Holland Society of Sciences and Humanities, the Academy of Europe, and the North Rhine-Westphalian Academy of Sciences, Humanities and the Arts. In 2018, he was awarded an Alexander-von-Humboldt Professorship.

Sebastian Trimpe is a Full Professor at RWTH Aachen University, where he heads the newly founded Institute for Data Science in Mechanical Engineering (DSME) since May 2020. Research at DSME focuses on fundamental questions at the intersection of control, machine learning, networks, and robotics. Before moving to RWTH, Sebastian was a Max Planck and Cyber Valley Research Group Leader at the Max Planck Institute for Intelligent Systems in Tübingen/Stuttgart, where he keeps a side appointment at present. Sebastian obtained his Ph.D. degree in 2013 from ETH Zurich with Raffaello D’Andrea at the Institute for Dynamic Systems and Control. Before, he received a B.Sc. degree in General Engineering Science in 2005, a M.Sc. degree (Dipl.-Ing.) in Electrical Engineering in 2007, and an MBA degree in Technology Management in 2007, all from Hamburg University of Technology. In 2007, he was a research scholar at the University of California at Berkeley. Sebastian is recipient of the triennial IFAC World Congress Interactive Paper Prize (2011), the Klaus Tschira Award for achievements in public understanding of science (2014), the Best Paper Award of the International Conference on Cyber-Physical Systems (2019), and the Future Prize by the Ewald Marquardt Stiftung for innovations in control engineering (2020).

Short Bio:

Sarit Kraus (Ph.D. Computer Science, Hebrew University, 1989) is a Professor of Computer Science at Bar-Ilan University. Her research is focused on intelligent agents and multi-agent systems (including people and robots) integrating machine-learning techniques with optimization and game theory methods. In particular, she studies the development of intelligent agents that can interact proficiently with people and with robots. She has also contributed to the research on machine learning, agent optimization, homeland security, autonomous vehicles, adversarial patrolling, social networks and nonmonotonic reasoning.
For her work she received many prestigious awards. She was awarded the IJCAI Computers and Thought Award, the ACM SIGART Agents Research award, the ACM Athena Lecturer, the EMET prize and was twice the winner of the IFAAMAS influential paper award. She is an ACM, AAAI and ECCAI fellow and a recipient of the advanced ERC grant. She is a member of the Israel Academy for Sciences. She also received a special commendation from the city of Los Angeles, together with Prof. Tambe, Prof. Ordonez and their USC students, for the creation of the ARMOR security scheduling system. She has published over 400 papers in leading journals and major conferences and co-authored five books. She is a member of the board of directors of the International Foundation for Multi-agent Systems (IFAAMAS) and was IJCAI 2019 program chair.

I am an Open Access publisher with special interest in AI and based in Paris. I just sold my company Atlantis Press to Springer and looking for new opportunities via Claire. Would love to meet people in your team and discuss how we can define some common interests.

An enthusiastic PhD Control System engineer with both academic and industrial experience in the field of Renewable Energy Integration, Smart Cities and Water Treatment.
My research activities focused on:
– integration of renewable energy sources,
– applications for battery energy storage systems (BESS),
– hierarchical power plant control,
– Smart City grid operation optimization (Model Predictive Control),
– Big Data, Machine Learning & Industry 4.0

Main research domain Machine learning, Artificial Intelligence, Cybersecurity and Natural Language processing.

ACM Fellow
AAAI Fellow

To whom it may concern,
My names is Prof. Dr. Thomas ho*ren and I am a law professor at the University of Muenster, Germany, and head of the Institute for Information, Telecommunications and Media Law.

For almost 25 years, I have been a professor of IT law with a special focus on the legal issues of blockchain, algorithms and AI. Thus, I have already supervised several interdisciplinary projects in this area (e.g. “GOAL-Governance of and by Algorithms”, “Blockchain and Law”, and “Assessing Big Data -ABIDA” . In addition, I am an adjunct professor at the Fraunhofer Institute for Applied Information Technology (FIT).

In the past, I also served as an international visiting scholar at the University of Amsterdam (Institute for Information Law), Kyushu University (f*ckuoka/Japan), Harvard Law School (Boston), Stanford University, and Oxford Internet Institute/Balliol College, among others. These programs have allowed me to focus on international contexts and differences when considering IT law and the legal assessment of artificial intelligence.

I am co-editor of several renowned journals in the field of IT law, such as “Multimedia und Recht” (C.H.Beck), “International Journal of Law and Information Technology” (Oxford University Press) and the “Zeitschrift für Datenschutz” (C.H.Beck). All of these journals focus on the interaction of technological progress and the shaping of law. The discussion of artificial intelligence is also comprehensively addressed here. In addition, my research team and I are regularly publish on IT legal topics in renown law journals.

So far, this commitment has been honored, among other things, with the award “for German-Dutch scientific cooperation” (2018), the award of the “Daidalos-Silbermünze der Studienstiftung des deutschen Volkes” (2018) and honor with the ALCATEL-SEL Research Award „Technische Kommunikation“ (2005).

I would like to contribute my professional expertise to your research network and at the same time participate in the innovative ideas of the numerous members. In addition, I would like to join the research network with the Institute for Information, Telecommunications and Media Law in order to be able to contribute our competences even more comprehensively and profitably to the research network.

Best regards,
Thomas ho*ren

Founder and CEO of Textkernel, Zeta Alpha.

AI in biomedical image analysis

Dr Heinz Mayer, Director of JOANNEUM RESEARCH DIGITAL since 2013, graduated from the Graz University of Technology with a master degree in Telematics and a doctoral degree respectively. After several years at Magna Steyr, he is ramping up the research unit Machine Vision Applications since 2007 at JOANNEUM RESEARCH. Heinz Mayer is member of the professional organizations IEEE and ACM and member of the Austrian strategic community. He is start-up founder and holds several patents.

Ph.D. in AI from Telecom Paris, ENST
10 years co-developping Mila as Director AI for Humanity, Executive Director and Director of Technology Transfer under the supervision of Prof. Yoshua Bengio, Turing Award Laureate 2018.
Interests: contribute to build a better world with a responsible and sustainable use of AI.

complete CV is available at https://homes.di.unimi.it/piuri/pages/cv_support/cv.pdf

Data Mining, Machine Learning, Business Intelligence/analytics, Intelligent Decision Support Systems applied to Healthcare/Medicine

I lead product development for Bitfury AI. At Bitfury AI, we are developing disruptive hardware technology to accelerate efficient machine learning in the edge. I am interested in machine learning and contributing back to the community.

https://www.researchgate.net/profile/Alvaro-Figueira

Researcher in Spoken communication and AI. Participating in EU project AI4EU and HumaneAI-Net.
Expert in multimodal data acquisition and processing, audiovisual speech synthesis, ..

Applying AI in food safety to keep and make food safe

Sarolta is boosting cutting-edge research collaborations across the ICT and Creative Industries sectors. Her focus is on university-industry partnerships with technology providers to harness Oxford research strengths in AI/machine learning and immersive technologies.

Dr Argyro Karanasiou is the Director of LETS Lab at the School of Law & Criminology and a leading expert in Information Technology Law. Her work has been at the forefront of nurturing ‘law and emerging technologies’ as a sub-field of legal and interdisciplinary scholarship and has earned her visiting research affiliations with Yale Law School (ISP Alumna), NYU Law (ILI Alumna 2016), Harvard Law (affiliate Faculty staff 2014), Complutense Madrid (ITC). She is actively involved in several technology policy and related initiatives in the UK and worldwide, including those concerned with the governance of AI, one of her key research interests. In particular, she has contributed invited expert insights on a number of occasions, most notably for the Equality and Human Rights Commission (AI in recruitment – 2020), the Chatham House (Internet Governance – 2018), the US Air Force (AI & Augmented Cognition – 2018), the Royal Society (Machine Learning – 2016), and the Electronic Frontiers Foundation (Free Trade Agreements and Human Rights – 2016). Furthermore, she has served as a contracted consultant for the Council of Europe (regional South Eastern Europe expert in Media), and as an OSCE expert for Online Media. In recognition of her work, Dr Karanasiou has been appointed a Privacy-by-Design Ambassadorship by the Information Commissioner in Ontario, Canada, and has been awarded twice the Internet Society IGF Ambassadorship, in 2013 (Indonesia) and in 2015 (Brazil). She has also as an served expert evaluator for the Swiss National Foundation and for the Newbreed doctoral programme in Sweden and as an expert reviewer for the Oxford University Press Information Technology & Communications Law series.

Hybrid AI for predictive maintenance, smart buildings and personalized healthcare

IT pro by mistake, innovator by passion.
Simone began his professional career 15 years ago providing assistance and support to SMB companies and then continuing as a technical specialist on Microsoft and VMware technologies for enterprise companies.

In 2013 he discovers and falls in love with the open source world and at the same time expands his skills towards presale, service management, business organization and strategy.

Today, as Digital Transformation Officer and Sales&Marketing Director, he leads the path of E4 Computer Engineering by combining the company’s renowned and historical background in the HPC market with the potential of OpenStack cloud and Kubernetes containers technologies.

Christos Kyrkou is a Senior Research Associate at the KIOS Research & Innovation Center of Excellence at the University of Cyprus. Dr. Kyrkou received his Ph.D. degree in Computer Engineering from the University of Cyprus in 2014. He is an author/co-author of more than 45 scientific publications in international peer reviewed conferences and journals. He has experience in several National and European funded research and innovation projects. His research interests lie in the areas of Computer Vision and Deep Learning with emphasis on real-time performance. In particular embedded deep vision (efficient convolutional network architectures and techniques), visual object recognition and detection, vision applications, vision for robotics and autonomous vehicles.

I am interested in knowledge representation and reasoning related to actions, observations and uncertainty.

Our research group is specialized in computational intelligence, with focus on applications in data(base) management.

Celestijnenlaan 200a – box 2402
3001 Leuven, Belgium

•Applications of machine (deep) learning
•Anomaly detection
•(Semi-)supervised learning strategies
•Automated interpretation of time-series signals such as acoustic, radar and accelerometer signals
•Real-time machine learning on resource constrained devices

I am a part-time assistant professor at the IDLab research group of Ghent University (since October 2019) and a full-time research manager and senior scientist at the imec research hub for nanotechnologies and digital technologies.

I received my PhD in Computer Science in August 2013 pertaining to knowledge discovery and management for eHealth applications by using ontologies and semantic reasoning. During this time, I worked on several eCare projects to improve the continuous care of patients in institutionalized care settings.

As a professor at Ghent University, I lead the Knowledge Management team. This team performs research into a) expressive semantic stream and distributed reasoning, b) the incorporation of expert knowledge in data analytics algorithms, c) hybrid AI, fusing semantic models and machine learning, and d) explainable AI by leveraging Knowledge Graphs. I am also particularly interested in methodologies for capturing domain knowledge from experts & using this knowledge to optimize intelligent agents and the way we interact with them. This research is mainly applied to the domains of predictive healthcare and industry 4.0 in order to realize context-aware and personalized decision support systems.

One of my passions is fostering collaboration with societal and industrial partners in interdisciplinary projects to valorize our research toward truly impactful applications. This is realized through a number of (government sponsored) projects, for which I set up and lead the trajectory from proposal, into project management and valorization and dissemination afterwards.

With others, I am informally developing the the RefPerSys symbolic artificial intelligence free software system (with a few people from India). It is for Linux, GPLv3+ licensed.

You could be interested by the works of the late Jacques Pitrat (1934 – oct. 2019) who was the director of my PhD jury, defended in 1990 in Paris. I strongly recommend reading Pitrat’s blog on http://bootstrappingartificialintelligence.fr/WordPress3/ and his last book
Artificial Beings: the Conscience of a Conscious Machine
ISBN-13: 978-1848211018

I am currently working on cybersecurity at CEA LIST in France on the Bismon static source code analyzer (funded by CHARIOT & DECODER European projects). However, these fundings will soon stop, and I have to find another funding.

Hence I am seeking some applications and some funding for this RefPerSys AI software, and trying to get be funded (perhaps thru some HorizonEurope project proposal) to be able to work more on RefPerSys.

If you are an academic or industrial interested in RefPerSys, please contact me by email

The RefPerSys website is an amateur website, see http://refpersys.org/

For those speaking French, see also the talks on
on https://afia.asso.fr/journee-hommage-j-pitrat/

B.Sc. Physics (Imperial College, London), M.Sc. Applied Mathematics (ST. Catherine’s College, Oxford, UK), MSc. Physics (University of Rome Tor Vergata), PhD Natural Sciences (Ludwig Maximilian University of Munich, max Planck Institute of Psychiatry), Specialization School in Medical Physics (University of Rome Tor Vergata).

Nicola Toschi is an Associate Professor in Medical Physics at the University of Rome “Tor Vergata” and Research Staff and Faculty at the Athinoula A. Martinos Center for Biomedical Imaging (Harvard Medical School). He has previously worked as a strategy consultant at McKinsey & Company, as a facilitator for the United Nations convention on Climate Change, with the Italian National Television (RAI) and as a project coordinator with AMREF. His research is interdisciplinary, with a focus on scientific and technological solutions for the deployment of advanced physical and mathematical techniques in order to extract quantitative information of investigative, diagnostic and prognostic value in a clinical context. He is a senior member of the IEEE society, an active member of ISMRM and OHBM, a founding member of the Alzheimer’s Precision Medicine Initiative (AMPI) a member of the Technical Committee on Cardiopulmonary Systems.

Lead, AI Global Taskforce, FTI Consulting

Sense (Societal impact of gENetic SciencE) is the Dutch consortium of bringing genetic science to citizens. The consortium consists of partners in Dutch Academic Hospitals, Primary Care specialists, Patient organisations, other NGO’s, Education (academic and applied science) and Industry. The consortium strengthens the momentum created by European initiatives like the 1-million genome initiative to bring genetic information and science to the public. SENSE addresses the strong societal, clinical and individual demand for a personalized, preventive and autonomous healthcare system in which the individual has control. Personal Genetic Locker, 4WeCooperate, 4MedBox, Bio-Informatics

Already heavily involved in both academic and industrial AI projects

Rua Alves Redol nº9 piso 7

I am currently working on my PhD at the Doctoral School of Regional- and Business Administration Sciences of Széchenyi István University of Győr in Hungary. My research work is supported by Cooperative Doctoral Programme of the National Research, Development and Innovation Office of Hungary.

In the last 13 years:
* 47 Funded research projects
* Coordinator in 16 of them
* More than 13 million euros in funding
* Numerous paper awards
* Yearly participation in the Program Committees of top conferences

My position in CETIC requires designing and defining the Research and Innovation Strategies for the whole organisation, driving its implementation and validating its applicability and usefulness for Industry. (CETIC is a Belgian RTO specialised in Digital Technologies responsible for digital transformation of companies in several sectors, notably, Smart Industry, Transport and Mobility, Health, Logistics, and Energy. CETIC assists companies with deveopping safe and secure autonomous complex systems relying on artificial intelligence thanks to its expertise in a wide range of areas: data engineering, data analysis, combinatorial algorithms and optimisation, model based engineering for CPS, for distributed Cloud systems and for the programmability of heterogeneous hardware and IoT in Edge networks.)

Directly related to AI research, we actively work on constraint based local search, federated machine learning, transformation of AI models for embedding on heterogenous hardware, and certifiability of AI-based systems.

I lead CETIC’s participation as core partner of TRAIL (Trusted AI Labs), an initiative supported by the Walloon Region through the ARIAC project involving 5 universites and 4 RTOS started in Jan21.

In general, my position enables me acting as a middleman for synthesising Industry needs in AI for developing amitious collaborative research and innovation projects with industrials partners (Large and SME) centered on real-world problems and datasets.

I am coordinating FZJ’s Helmholtz AI Local Unit at the Institute of Neuroscience and Medicine (INM-1) and Jülich Supercomputing Center (JSC) and its interaction and cooperation with the Helmholtz wide AI platform. –> helmholtz.ai
Closely related to that, I am also coordinating the Helmholtz International BigBrain Analytics and Learning Lab (HIBALL), a collaboration between McGill university (MNI, BIC) and Forschungszentrum Jülich (INM-1, JSC) –> bigbrainproject.org

Juan Manuel Ahuactzin is the Research & Development Director at Promagnus Company. He has over 20 years’ experience driving top scientific and technological research projects and over 10 years’ experience in systems analysis, design, and industry development. He has a solid background as a teacher and mentor in higher education. He has acquired experience in Bayesian technology, data mining, machine learning, optimization techniques, and geometric reasoning along in his career. J.M. Ahuactzin has extensive and applicable knowledge in diagnosis and prediction under uncertainty, decision and risk analysis, smart cities, the internet of things, robotics, and health informatics. Besides, he is interested in the techniques of creativity, innovation, and Design Thinking. He is the author and co-author of several journal articles and book chapters, mainly in robotics and applied Bayesian reasoning. Along with his colleagues at INRIA, he is co-author of the book “Bayesian Programming” published by CRC Press.

He received his Bachelor’s degree in computer systems engineering from Universidad de las Américas Puebla (UDLAP) Mexico in 1989. He obtained the M.S. and Ph.D. degrees in Computer Science from the Institut National Polytechnique de Grenoble, France, in 1991 and 1994. During 1994-95, he worked as a postdoctoral fellow in the robotics group at Simon Fraser University (SFU), Canada. He continued to be an associate researcher at SFU during the summers from 1996 to 1999. From 1995 to 1999, J.M. Ahuactzin had a permanent Computer Systems Engineering Department position at UDLAP. From January 2000 to 2005, he was a researcher at INRIA Rône-Alpes, France, where he participated in several European research projects. J.M. Ahuactzin is cofounder of Probayes (spin-offs of INRIA) in France and Probayes Americas in Mexico (now Promagnus). At the first company, he was the Research Director from 2005 to February 2011; at Probayes Americas, he was CEO from 2010 to May 2015. Probayes was acquired by La Poste (France) in 2016. From May 2015 to June 2020, he was the innovation program manager at T-Systems Mexico. Dr. Ahuactzin is passionate about academia; he is a part-time course lecturer at Universidad de las Américas Puebla. Juan Manuel Ahuactzin is a founding member of the Mexican Academy for Computing.

http://natalie.uno/

Passionate about people and technology, I am the CEO of ReliaSol.ai a successful scale up company headquartered in The Netherlands.

We developed a Digital Platform for Predictive Maintenance based on Artificial Intelligence (Deep Learning) that helps our customers to optimise their industrial processes, increase their production uptime and decrease their maintenance costs.

Customers like Bühler, Opel, Volkswagen, EDF, Howden, GE Power among others have already trusted in our expertise and experience.

Interest on AI and Machine Learning and their applications in Healthcare.

european ai framework for cross correlation of scientific data – made for H2020 projects and interdisciplinary science. Financed by the euroean community.

it infrastructure for multi user cloud storage and analysis

ICT Lawyer | EU Observatory Expert | Member of the European AI Alliance | Chair of the Online Arbitration Court CODR.PL | Juris Doctor | IT Project Manager | Assistant Professor

Member of the Competence Unit Data Science & Artificial Intelligence at AIT; responsible for applied artificial intelligence; member of the Austrian Standardization Committee for Artificial Intelligence; co-organizer of the very successful Vienna Deep Learning Meetup;

Ulises Cortés is a Full-Professor and Researcher of the Technical University of Catalonia (UPC) since 1982 (tenured since 1988 and habilitated as Full-Professor since 2006) working on several areas of Artificial Intelligence (AI) in the Software Department including knowledge acquisition for and concept formation in knowledge-based systems, as well as on machine learning and in autonomous intelligent agents.
Since 2017 Professor Cortés is the scientific manager of the High-Performance Artificial Intelligence group at the Barcelona Supercomputing Center.
Since 1989 Professor Cortés and his group have been applying for their work in Artificial Intelligence to Environmental Sciences in special to Wastewater Treatment Plants with the financial support of CICyT and CIRIT and the European Union.
He is a co-founder of SISLTECH and member of its Board of Directors from 2011 until 2016.

In collaboration with the Hospital de la Santa Creu I Sant Pau from 1999 until 2007, Ulises was working in the development and deployment of CARREL: An Agent-Mediated Institution for the Exchange of Human Tissues among Hospitals for Transplantation”. And in collaboration with Hospital Santa Lucia (Rome) and the University of Málaga since 2001, he is working in the development and deployment of e-Tools: Assistive technologies for the disabled and the new generation of senior citizens.
Since 1991, he is the Coordinator of the Artificial Intelligence PhD program for the Technical University of Catalonia. Since, 2012, Prof. Cortés is Deputy vice-rector for European Research or the Technical University of Catalonia. Since 2007 and until 2012, Professor Cortés was the Academic Coordinator of the Barcelona Supercomputing Center. He is the Academic Coordinator for the Inter-university Master programme on Artificial Intelligence from 2011 (he was from 2005 to 2010) and was appointed vice-dean for International Relations at Barcelona School of Informatics from 1993 to 1998.

Fellow of the Mexican Asociation for Artificial Intelligence (2018). Since 2012 Ulises is a member of the Mexican “Sistema Nacional de Investigadores” with a Nivel III. He was awarded with the Advanced Research Accreditation by Agència per a la Qualitat del Sistema Universitari de Catalunya in 2004 as well as appointed to the CLUSTER chair at the École Polytechnique Fédérale de Lausanne (EPFL) for the academic course1998-1999.

Professor Cortés advised 24 PhD. Thesis, two of them have been awarded the ECCAI AI Dissertation Award, and more than 20 Master Thesis in the field of Artificial Intelligence and has more than 50 papers in international journals and more than 150 papers in Conferences and Workshops in the same period. Several of his former PhD students are now internationally known AI scientists.

I’m Mathematical and Industrial Engineer. Doctor in Science. Member of IEEE, ACM, INFORMS and European Society of Operational Research. I have interest in Machine Learning, Operational Research, Artificial Inteligent, Analytics, Data Science, Data Mining and Simulation.

areas of interest: time series analysis, prediction, data mining, machine learning

I am technologist with experience in managing AI products and projects, gained through quantitative and managerial roles in top tier consulting and industry leading corporates, and by being the founder and CEO of a venture-backed Machine Learning startup. My areas of expertise are Advanced Analytics and Artificial Intelligence, leading cross-functional teams of data scientists, data engineers, developers and designers to build software solutions that unlock real business and social value.

I hold a M.Sc. degree in Computer Science from Saarland University, Germany. I hold a B.Sc. degree in Electronics & Communication Engineering from Ain Shams University, Egypt.
I currently work as a researcher in applied machine learning at DFKI and I previously worked as a research assistant for 1.5 years at HCI group, Saarland University. I also worked for two years as a senior optimization Engineer at Vodafone Egypt.
My research and work interest is HCI (Human Computer Interaction), Multimodal Interaction, Computer Vision, Machine Learning, Deep learning, Embedded systems and Security, Electronics and Telecommunication.

Insurgentes Sur 1685

I’m mostly interested in user modelling, behavior analysis and crowdsourcing.

Leading the research Group Artificial Intelligence and Sparse Modelling (GAIM) at the Department Telecommunications and Information Processing at Ghent University.

Teaching ‘Artificial Intelligence’ , ‘Computer Graphics’ and ‘Probabilistic Graphical Models’ courses at at the Faculty of Engineering at Ghent University.

Room A322
Portland Square
Plymouth
PL4 8AA

Prof. Paolo Soda graduated with honours in Biomedical Engineering at Università Campus Bio-Medico (UCBM), Rome, in 2004 and received a Ph.D Biomedical Engineering (Computer Science area) in 2008 from the same University. Currently he is Associate Professor of Computer Science and Computer Engineering at UCBM, and he is co-responsible of the Collaborative Laboratory of Precision Medicine & BioData Analytics between UCBM and Centro Diagnostico Italiano, Milan.
His research interests include artificial intelligence, pattern recognition, machine learning, big data analytics, and data mining applied to data, signal, 2D and 3D image and video processing and analysis. Practical applications of the research activities have impacted on the biomedical applications, with reference to computer-aided diagnosis and decision support systems. He is member of several Program Committees of international conferences and he serves as referee for several international journals. He has been guest editor of several impacted international journals (e.g. Pattern Recognition, Artificial Intelligence in Medicine, etc.) and, since 2012, he has been associate editor of the Proceedings of the Annual International Conference of the IEEE Engineering in Medicine & Biology Society. Since 2018 he has been chairing the Steering Committee of the IEEE International Symposium of Computer-Based Medical Systems. He has been co-PI of several national and international projects. His research activity is certified by > 100 scientific publications, >1200 overall citations, h-index 19 and an i10-index 36 (Google Scholar data source), further to be co-author of three conference papers receiving an award (IEEE LSC 2018, IEEE BIBM 2018, IEEE ICCI*CC 2019). He is a member of the IEEE, CVPL and SIBIM, and he is chairing the IEEE Technical Committee on Computational Life Sciences.

I work in both pure and applied mathematics. In applied mathematics, I work in Optimisation and applications to Deep Learning. One of my recent publications advances Backtracking Gradient Descent method and allows its implementation in Deep Neural Networks:

https://link.springer.com/article/10.1007/s00245-020-09718-8

In some of my preprints on arXiv, I designed a new modification of Newton’s method which is both fast and can avoid saddle points.

You can check my website for more information.

Zahia Guessoum is “Maître de Conférences” (Associate Professor). She received her doctorship/PhD (1996) and then her “habilitation à diriger des recherches” (2003), both in computer science and from University Pierre & Marie Curie (Paris 6), France. She is member of the Multi-Agent System (MAS) Team of “Laboratoire d’Informatique de Paris 6” (LIP6). Her general research interests are about adaptive agents and multi-agent systems, fault-tolerant MAS, multi-agent oriented software engineering, coordination mechanisms, multi-agent simulation and complex systems.

I am Associate Professor with Habilitation at the Department of Informatics, University of Minho. I am the Director of ALGORITMI Research Centre, the research centre of the University of Minho dedicated to Computer Science, with 102 phD full members, 230 phD associated members and more than 110 phD students. ALGORITMI has 4 laboratories working in related fields of Artificial Intelligence (Robotics, Intelligent Systems, Knowledge Engineering and Data Science). I am the leader of the knowledge Engineering Lab.

Professor for Computer Vision at RWTH Aachen University
Director of the RWTH Center for Artificial Intelligence

– “Cloud & AI Reseacher” @ School of Management of Politecnico Milano
– “Data-Driven Strategy Practice Manager” @Reply
– “Director of Data & AI” @Jakala

Markus Diesmann is one of the two original authors of NEST, the most widely used code for large-scale neuronal network simulations and the central simulation tool for this purpose in the HBP. He is interested in simulation technology and supercomputing and works on the neuroscientific foundations for neuromorphic computing.

My focus is on intelligent agent technologies, decision support concepts, and formal methods for multiagent systems. In particular, modeling the behavior of multiagent systems and logical frameworks to represent and reason about decision processes in multiagent settings.

My Lab is focused on AI applications in Bioinformatics (in particular Machine Learning and Data Mining algorithms). I’m also co-leading the ELIXIR Machine Learning Focus Group, and would be keen to be part of the CLAIRE network, both for exchange of ideas and best practices, as well as potential future collaborations (funded or otherwise).

President of the Romanian Association for Artificial Intelligence (ARIA)

Large experience in management of Artificial Intelligence and Data teams working on systemic approaches applied to industrial value chains. Mainly focused in technology transfer activities with more than 20 years across multiple roles, design engineer; researcher; technical director; R&D director; and CTO. Extensive collaboration with SMEs and large companies, highlighting a smart factories deployment. Currently, leads Eurecat’s technology convergence vision and singular projects, including augmented intelligence solutions across multiple domains. He also collaborates with the EC in the development of digital strategies and collaborates in multiple organizations (BDVA, AIOTI, EFFRA, W3C, ETSI, OGC) .

Area of interest: AI application in fluid simulation and pattern recognition.

– Main research interest: knoweldge representation and reasoning; automated planning and scheduling; application in Health
– Coordinator of the “Scheduling and Resource Management” topic of the CLAIRE Covid-19 Task Force
– Co-author of the most cited article appearning in the Artificial Intelligence journal in the period 2016-19
– Best paper award at the 35th International Conference on Logic Programming (ICLP 2019)

Silvia Martinelli is a lawyer of the Milan Bar Association, Researcher (“Assegnista”) at the University of Milan and PhD Candidate at the University of Turin.

Graduated in Law at the University of Milan, specialized in “Legal Informatic”, she is also Fellow of the Information Society Law Center (ISLC) of the University of Milan and Teaching Assistant (“Cultore della materia”) in both Private Law (University of Turin) and Legal Informatics (University of Milan).

She is also Member of the Editorial Committee of the Law Reviews “Ciberspazio e Diritto”, “Diritto, Mercato e Tecnologia” and “Diritto di Internet”, Fellow of the European Law Institute and of the Italian Academy of Internet Code, Member of the European Law & Tech Network.

She published a book about the right to be forgotten: “Diritto all’oblio e motori di ricerca. Memoria e privacy nell’era digitale“, Giuffrè, 2017 (“Right to be forgotten and search engines. Memory and privacy in the digital age”).

She wrote scientific articles about e-commerce, freedom of expression online, control of the worker through new technologies, domain names, data protection, right to be forgotten, data portability, provider’s liability and platform economy.

The PhD Research Project concerns platform economy and the liability of the intermediary platform. It focuses on Uber, Airbnb, Amazon and Ebay.

Aerospace scientist and engineer. Researcher in space plasma physics. Expert in HPC, advanced programming and machine learning.

Dear Sir/Madam,

At HIPSTO we are building the world’s premier open AI information discovery platform where we are pushing the current boundaries of AI/DS/ML/DL. Recent breakthroughs are extending Google BERT in field of related content detection (science paper available) and tests that show our AI “blind vision” technology is vastly superior to “computer vision” in the area of web data feature extraction & labeling. ……..and much more :-). We are here to help!

Inffeldgasse 13, 6th floor

I’m writing you because I’d like that my Acube lab is listed among the ones supporting Claire ntw. In fact I’m already part of the unit associated to the Department of Computer Science in Pisa. Hence I specified the website of the lab.

Statistical and machine learning, genomics, medicine, bioinformatics

Head of AI Bay – regional AI club integrating representatives of academia, industry, public administration and all people interested in AI.

Research and Education Director of DIH4.AI – https://dih4.ai

Head of Biomedical Engineering Department and Faculty of Electronics, Telecommunications and Informatics, Gdansk University of Technology, Poland (www.biomed.edu.pl, https://mostwiedzy.pl/en/jacek-ruminski,11727-1)

Currently involved in 6 projects:
– deep learning for CT image classification (brain hemorrhages)
– machine learning for physical activity analysis and healthy life prognosis
– machine learning for image processing in dental studies
– application of machine learning for biomedical signal analysis to support active assistive living
– support for industry and administration regarding applications of AI – Digital Innovation Hub
– biosignals estimation from thermal and visible light image sequences.

My research topics are focused on machine learning, computer vision and pattern recognition methods applied for healthcare and well-being. I am especially interested in smart methods of information extraction from image sequences and from still images. Examples include: reliable extraction of pulse rate and pulse waveform from visible light, face video, reliable extraction of respiratory rate and respiration waveforms from thermal, face video, emotion recognition based on analysis of facial (visible/infrared) image sequences. Many special research problems and questions are related to these examples. For instance: How to improve the resolution and quality of thermal images (e.g., development of super-resolution models and algorithms)? How to accurately detect facial regions like a nose, mouth in thermal images? And many others. The machine learning algorithms and models are especially useful for these purposes. From the practical point of view, I am interested how such methods could be efficiently implemented in smart glasses, smartphones, or using interactive web applications (e.g., using WebRTC) in different devices. The potential applications include remote medical diagnostics, self-diagnostics, support for tele-rehabilitation, etc.
This is also related with my interest in the development of human-system interaction methods, devices and applications. For example, a physician using smart glasses could automatically recognise a patient, collect information from available health records, measure vital signs and other parameters using a non-intrusive, non-invasive and not disturbing way. All collected data could be automatically integrated.
My interest in human-system interaction methods is also focused on the data processing methods to classify gestures. For example, we are using neural networks to classify data from small optical sensors for the effective hand gesture recognition and to provide an inexpensive touchless interface.
My other research topics are focused on colour processing in images. I am interested in the analysis of the role of colour as an information carrier, especially for colour blinded observers. Recently, I have been analysing how the popular, CNN-based, data classification models like e.g., Inception, VGG, ResNet are sensitive to colour changes, especially in the context of colour degradations related to colour-blinded people.
Finally, we are currently starting a cooperation with the BioBank in Poland (a member of the European BioBank’s network) to use machine learning methods for the processing (classification, recommendation, etc.) of multimodal medical data. First, we will focus on the classification and detections issues related to microscopic images in digital pathology.

I obtained my PhD at the Faculty of Economics and Business of KU Leuven. My research interests are in applied machine learning and data analytics in business areas such as business process management (process mining), marketing (churn prediction), banking and finance (fraud analytics), and education (learning analytics). My most recent research lines focus on representation learning in social networks, predictive process monitoring, trace clustering, and sequential pattern mining. I am main supervisor of 6 PhD researchers all doing research in applied machine learning in line with the topics listed above.

The Swiss AI Lab IDSIA (Istituto Dalle Molle di Studi sull’Intelligenza Artificiale) is a non-profit oriented research institute for artificial intelligence, affiliated with both the Faculty of Informatics of the Università della Svizzera Italiana and the Department of Innovative Technologies of SUPSI, the University of Applied Sciences of Southern Switzerland. We focus on machine learning (deep neural networks, reinforcement learning), operations research, data mining, and robotics.

Das Forschungszentrum „Human-Cyber-Physical Systems: Safety, Acceptance, Social and
Cultural Embeddedness” (FZ HCPS) versteht sich als eine fächerübergreifende Plattform, die Forscherinnen und Forschern der Universität Oldenburg, der Jade Hochschule sowie außeruniversitärer Forschungseinrichtungen die Möglichkeit der Erstellung, Abstimmung und Umsetzung einer gemeinsamen Forschungsstrategie im Bereich Human-Cyber-Physical Systems ermöglicht.

Unter dem Leitbild, technologische Innovationen nicht nur zu erforschen und zu erschaffen, sondern diese systematisch interdisziplinär zu reflektieren und verantwortlich zu gestalten, verfolgt das FZ HCPS die folgenden Ziele:

Die synergetische, interdisziplinäre Vernetzung zur Etablierung international sichtbarer Spitzenforschung im Profil des FZ HCPS
Die Stärkung der Grundlagenforschung in ausgewählten Fragenstellungen des Schwerpunktes des FZ zur Erzielung von hoch sichtbaren Lösungen offener Forschungsherausforderungen der Grundlagenforschung
In Kombination der obigen beiden Ziele und unter Beteiligung der Forschungspartner am Standort die Einwerbung hochkarätiger Forschungsprojekte auf landes-, nationaler und europäischer Ebene
Die Schaffung von nachhaltigen Forschungsinnovationen mit hoher industrieller Relevanz
Der systematische Ausbau und die Bereitstellung von Living Labs als Demonstratorobjekte und Experimentierplattformen für Forschungsinnovationen

I have a PhD in Computer Engineering by Universidade do Porto Faculty of Engineering with the topic “Agent-based Service Reconfiguration for Dynamic and Evolvable Systems”. I was able to successfully validate this innovative approach in flexible manufacturing system located in University of Valenciennes and at real industrial scenario at Whirlpool Factory – Naples, which allowed me to cover an interesting technological readiness from TRL-3 to TRL-7.

I’ve expertise on Industry 4.0; Cyber-Physical Systems; Intelligent Manufacturing; Machine Learning; Self-organization;
I’m an Invited Assistant Professor at Instituto Universitário da Maia and Auxiliar Researcher in the Digital Transformation Colab (DTx).

I’ve receive a Awards: Innovation Awards Technology Industry 4.0 (4k€)

At HD Vision Systems we develop light field based multi-camera systems for quality inspection, robotics and automation. Our AI-based algorithms provide our partners with superior results in an easy-to-use manner.

M.Sc. in electrical engineering (EPFL 2000)
Master’s thesis on AI (EPFL, 2000)
Research Fellowship at MIT Media Lab Europe (2001-2004) on interactive cinema, storytelling, new human-computer interfaces for video manipulation
Adjunct Professor and Visiting Scholar at USC School of Cinematic Arts (2004-2007)
Private research lab at LEV studio (2007-present)
Doctoral school in computer science, robotics and neuroscience at EPFL (2011-2013)
Doctoral school in narratology at University of Lausanne (2013-2015)

Bruno Martins is an assistant professor at the Computer Science and Engineering Department of IST and a researcher at the Information and Decision Support Systems Lab of INESC-ID, where he works on problems related to the general areas of information retrieval, text mining, and the geographical information sciences.

He has been involved in several research projects related to geospatial aspects in information access and retrieval, and he has accumulated a significant expertise in addressing challenges at the intersection of information retrieval, artificial intelligence, and the geographical information sciences.

My research background and interests involves stochastic optimization and control, distributed optimization over networks, reinforcement learning, privacy and security in machine learning, statistical machine learning, signal processing. I have held Professor positions in Australia, Sweden and Ireland and am on editorial boards of multiple IEEE Transactions. Have published 100 journal and over 120 conference papers in high impact journals and conferences, and obtained many nationally competitive grants in Australia and Sweden.

Areas of interest/expertise: Machine Translation, Machine Learning, Image Description, Computer-assisted Translation.

I Study and research in I.A. models for biology and health, to reach improvement in data analysis and disease prediction. In the last time I’ve also explored industrial segment with adopting same approach used to analyze health disease.

BruBotics is the Brussels Human Robotics Research Center of the Vrije Universiteit Brussel, combining 8 research groups striving to improve the quality of life and working conditions of people through Human Robotics. BruBotics uniquely combines expertise on robotics, AI, rehabilitation sciences, movement sciences, social sciences, marketing, ageing and eHealth and is as such one of the only truly interdiscip​linary robotics research centers in Europe. Together with industrial and societal partners we strive to take the next step in Human Robotics by breaking boundaries.

Brubotics is member of VUB AI Experience Center http://experience-center.ai

European projects manager in datascience & AI for Security & Defence

Dr. Jesús López is currently based in Bilbao (Spain) working at TECNALIA as Data Scientist and Researcher in Machine Learning and Artificial Intelligence.

He attended the University of Deusto and the National Distance Education University (UNED), receiving his BSc+MSc in Computer Science and his MSc in Advanced Artificial Intelligence respectively. In 2018 he obtained his PhD in Artificial Intelligence at the University of the Basque Country (EHU/UPV).

His research topics are real-time data mining (stream learning), concept drift, incremental learning, adaptive and evolving systems, anomaly detection, spiking neural networks, and cellular automata for data mining. Some of them as part of real applications in Robotics (planning), Energy, Telecommunications, Transportation Systems, IoT, Industry 4.0, and Smart Water. Also interesed in multi-purpose AI, hoping that AI community builds JARVIS while avoiding Skynet.

Occasionally, he writes data science stories for reputed blogs such as KDnuggets.com or Towardsdatascience.com. Not forgetting the leisure side, he also loves to go outdoors to surf all over the globe.

Technology Planning and Cooperation Manager. Head of DACH coopeartion.
Responsible for the DACH research agenda and academic relations in the DACH region.

EurAI Fellow

I lead an AI/HCI lab with 20 people nworking on AI tools for sound, image, video, gesture, text processing.