BrIAS Public Forum: Responsible AI

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This is a one-day public forum organised in collaboration with the Brussels Responsible AI Network (BRAIN). The forum brings together researchers, practitioners and policymakers from Belgium and abroad to discuss the latest advances in AI and its societal implications. More information here

Program

Speakers

Jerzy Stefanowski

Jerzy Stefanowski works as a full professor at Poznan University of Technology, Institute of Computing Science. He received his Ph.D and Habilitation degrees from the same University. In 2021 he was elected as a corresponding member of Polish Academy of Sciences, where he also plays a role of a Chair of Scientific Council of Institute of Computer Science (IPI PAN) in Warsaw. His research interests include data mining, machine learning and XAI. Major results are concerned with: ensemble classifiers, learning from class-imbalanced data, online learning from evolving data streams, explainable AI, induction of various types of rules, data preprocessing, generalizations of rough set theory, descriptive clustering of texts and medical applications of data mining. He is the author and co-author of over 170 research papers and 2 books, which are highly cited. Moreover, he was a visiting professor or researcher in several universities, mainly in France, Italy, Belgium, Spain and Germany.

In addition to his research activities, he served in a number of organizational capacities: including positions in bodies of Polish Academy of Sciences, current vice-president of Polish Artificial Intelligence Society (vice-president since 2014); co-founder and co-leader of Polish Special Interest Group on Machine Learning. Moreover, he is the Editor in Chief of Foundations of Computing and Decision Science journal since 2012 and Action Editor of other journals.

More information can be found at http://www.cs.put.poznan.pl/jstefanowski/.

Eirini Ntousi

Prof. Eirini Ntoutsi is Professor for Open Source Intelligence at the Department of Computer Sciences of the University of the Bundeswehr Munich. Her research interests lie in the fields of Artificial Intelligence (AI) and Machine Learning (ML). She has been focusing on designing intelligent algorithms that learn from data continuously following the cumulative nature of human learning, while ensuring that what has been learned helps driving positive societal impact. Her current research areas include continuous learning over non-stationary data and data streams, responsible AI and in particular fairness-aware machine learning and explainable AI, and generative AI, that is using machines to generate new plausible data and artifacts.

Prof. Ntoutsi is an active member of the research community serving regularly as a program committee member for several conferences and workshops. She was for instance co-chair or co-organizer multiple times for essential conferences and workshops such as CIKM, ICDM, ECMLPKDD or AAAI on topics like bias and fairness in AI, evaluation and experimental design in data mining and machine learning, or business applications of social network analysis. In 2018 she was co-organizer of the Dagstuhl perspectives workshop 18262 “10 years of Web Science: Closing the Loop" and is currently guest editor for the special issue on bias and fairness in AI in the Data Mining and Knowledge Discovery journal. Prof. Ntoutsi is a member of ACM, IEEE and German Informatics Society (GI). Her research is supported by several national (DFG, Volkswagen Foundation, BMWi, BMBF) and EU funds (ITN, H2020).

Kostas Stefanidis

Kostas Stefanidis is a Professor on Data Science at the Faculty of Information Technology and Communication Sciences of the Tampere University in Finland, where he also leads the Data Science Research Centre and the Group on Recommender Systems. He has more than 10 years of experience in different roles at ICS-FORTH in Greece, NTNU in Norway and CUHK in Hong Kong. He got his PhD in personalized data management from the Univ. of Ioannina in Greece. His research interests are in the broader area of big data. His work focuses on personalization and recommender systems, entity resolution, data exploration and data analytics, with a special focus recently on socio-technical aspects in data management like fairness and transparency, and published in more than 100 papers in top-tier conferences and journals. He has been involved in several international and national research projects, and he is also actively serving the scientific community. Currently, he is the General co-Chair of ADBIS 2025, TPDL 2025, and EDBT/ICDT 2026.

Asia Biega

Asia Biega is a computer scientist and a tenure-track faculty member (W2) at the Max Planck Institute for Security and Privacy (MPI-SP). She is also a principal investigator of the Cluster of Excellence CASA and of the interdisciplinary and intersectoral consortium FINDHR. At MPI-SP, she leads the interdisciplinary Responsible Computing group. To date, her team has included brilliant students, postdocs, and visitors with backgrounds ranging from Computer Science, Information Science, and Engineering to Psychology, Philosophy, Law, and Public Policy.

Her team and she study questions at the intersection of computing and society, particularly in the context of data-driven systems. Their current research centres around developing, examining, and computationally interpreting principles of responsible computing, data protection and governance, and digital well-being.

Pierre Geurts

Pierre Geurts is a full professor at the Systems and Modeling research unit at University of Liège. He carries out research in machine learning. He is mainly interested in the design of (computationally and statistically efficient) supervised and semi-supervised learning algorithms to exploit structured input and output spaces (sequences, images, time-series, graphs), with applications in bioinformatics, computer vision, and computer networks.

More information can be found at https://people.montefiore.uliege.be/geurts/.

Sabine Demey

Sabine Demey is the director of the Flanders AI Research Program (FAIR). She brings together researchers from 11 research partners in Flanders (universities and research centres). Together they tackle challenging AI Research Challenges and apply the new AI methods in healthcare, in industry 5.0, for the energy transition, in society. She believes it is important for technological developments such as AI to have a meaningful impact on people, industry and society. Sabine is a computer scientist and holds a PhD in robotics. Prior to leading the AI Research Program in Flanders since 2020, she has 20+ years industrial experience in research, product and business development, software for the manufacturing industry and for healthcare.

Panagiotis Germanakos

Panagiotis Germanakos is a Principal User Experience Research Scientist and Instructor at SAP SE, leading and supporting user research initiatives of product teams for delivering usable, high quality, human-centred solutions. As an SAP University Alliances Ambassador, he acts as a liason between industry and academia, consulting and sharing knowledge to inspire innovation. For many years, he has been exploring the human-machine interaction, striving to understand their evolving symbiosis. His research focuses on the coexistence of human-, artificial-, and quantum- intelligence in developing optimal, adaptive, and personalized solutions tailored to individual users. In 2021, he co-founded PulseX Non-Profit Research Institute, dedicated to promoting responsible scientific research, knowledge, and innovations that enhance human experiences and improve lives. He holds a PhD in Human-Centered Computing from the National & Kapodistrian University of Athens (2008) and has authored over 140 publications in top-tier conferences and journals, including nine books. His work has received multiple awards, along with seven patents. Additionally, he is a co-founder of international scientific events such as the ACM HAAPIE and HUMANIZE workshop series. He actively serves on editorial boards, program committees, and advisory panels for leading conferences and journals, including ACM UMAP, IUI, INTERACT, and CHI. He is also a member of international research networks and professional organizations such as ACM SIGCHI, AIS, and the Expert Network of HCI-KDD.

More information can be found at http://pgermanakos.com/.

Vincent Ginis

Vincent Ginis received his B.Sc. degree in engineering, summa cum laude, in 2007, and the M.Sc. degree in Photonics Engineering, summa cum laude, in 2009 from the Vrije Universiteit Brussel (Belgium). In May 2014, he received the degree of doctor in applied sciences, summa cum laude and felicitations of the exam committee. Currently, Vincent is appointed as an assistant professor at the Vrije Universiteit Brussel. He also works as a visiting professor in the group of Prof. Federico Capasso at Harvard University.

To date, Vincent has published his research in around 20 international publications with a high impact factor, including 1 article in the Proceedings of the National Academy of Sciences, several letters in Physical Review Letters–among which 2 cover articles–and many publications that were highlighted as Editor’s Suggestion. He has presented his work in more than 40 international conference proceedings and he was invited or plenary speaker at 9 international conferences.

Vincent has received many national and international awards, including Agathon De Potter Award in Physics (2018), the Solvay Award for PhD dissertations (2016), the Vocatio fellowship (2015), the FWO/BCG Best Paper Award (2014), the international SPIE Scholarship in Optical Science and Engineering (2013), the IEEE Photonics Graduate Student fellowship (2012), the KVIV engineering award (2010), and the FWO/Barco Award (2010). Vincent also serves as an editor of the journal Applied Metamaterials and as a reviewer for several important journals in his field, including Nature Photonics, Physical Review Letters, Nature Communications, and New Journal of Physics. He is also member of the scientific committee of several international conferences, including SPIE Photonics Europe and META. Vincent regularly appears in the general media to discuss research breakthroughs. In 2017, he was elected as one of the 10 new members of the Young Academy of Belgium and as one of the top 50 tech pioneers in Belgium.

More information can be found at https://ai.vub.ac.be/team/vincent-ginis/.

Yves Moreau

Yves Moreau is a professor at the University of Leuven, Belgium. His team develops machine learning methods for clinical genetics and drug discovery: (1) privacy-preserving analysis of clinical genetic data, (2) data fusion algorithms for the identification of candidate disease genes and variants in rare genetic disorders, and (3) data fusion for drug discovery and drug design. Methodologically, he focuses on the development of novel artificial intelligence methods (Bayesian matrix factorization and deep learning) for the fusion of heterogeneous, sparsely observed data, and on privacy-preserving implementations of such methods. He aims at demonstrated clinical or industrial applicability of those methods and proven effectiveness in human genetics research and drug discovery. He is a tech innovator interested in identifying relevant business models for emerging technologies and developing projects up to the precompetitive stage and the startup of university spin-offs. He was a co-founder of Data4S, a data mining company specialized in fraud detection and anti-moneylaundering, which is now part of BAE Systems. He was also a co-founder of Cartagenia, specialized in ICT solutions for clinical genetic diagnosis, now part of Agilent Technologies. He is also engaged in a reflection on how information technology and artificial intelligence are transforming our world and on how to make sure this transformation is beneficial for all.

More information can be found at https://ai.kuleuven.be/members/00012794.

Milena Machala

Milena Machała is an Antitrust Lawyer, and a Legal and Policy Officer in the European AI Office.

Gregory Lewkowicz

Former representative of the National Fund for Scientific Research (F.R.S.-FNRS), Gregory Lewkowicz is a professor at the Université libre de Bruxelles, a member of the Perelman Centre, and the director of the SMART Law Hub within the Faculty of Law and Criminology. He is also the academic director at the Institute of Artificial Intelligence for the Common Good (FARI) in Brussels. He teaches the course “Smart Law: Algorithms, Metrics & Artificial Intelligence” at Sciences Po Law School in Paris. Additionally, he lectures at Paris II Panthéon-Assas University and the University of Liège. He is a Koyré Senior Research Fellow in Economic Law and Artificial Intelligence as part of the 3IA Chair at Université Côte d’Azur. He is also a recurring professor in the executive education programs on digital transformation and law at HEC-Paris.

His research pragmatically examines the interactions between law and digital technologies (SMART Law), global and transnational law, as well as the contemporary transformations of law and legal professions. He leads several research programs on algorithmic law and the application of artificial intelligence techniques to the development, analysis, implementation, and enforcement of legal or related norms. He is also involved in multiple research and development projects with public and private partners. Gregory Lewkowicz frequently advises public authorities and companies on digital strategy and regulation.

Gregory Lewkowicz oversees the “Penser le droit” collection at Bruylant Publishing. He serves on the board of directors of the European Academy of Legal Theory and the Brussels Academic Higher Education Pole. He is a member of the advisory board of AI4Belgium and the European Committee on AI (AI Board). He established the Brussels Bar Observatory and chaired the European Incubator of the Brussels Bar from 2017 to 2022.

Benoit Frenay

Benoît Frénay is an associate professor at the Faculty of Computer Science of the Université de Namur. He completed a degree in computing science engineering (specialising in artificial intelligence) in 2007 at the Université catholique de Louvain. Then, he obtained a PhD in the UCL Machine Learning Group in 2013. The topic of his thesis was Uncertainty and Label Noise in Machine Learning. In parallel, he also completed a master’s in pedagogy in 2010 with a focus on problem-based learning. Additionally, he had the opportunity to undertake research stays at Aalto University, Radboud University Nijmegen, and the CITEC centre of excellence at Bielefeld University. In 2014, he received the Scientific Prize IBM Belgium for Informatics for his PhD thesis.

His main research interests in machine learning include support vector machines, label noise, efficient learning, graphical models, classification, clustering, density estimation, interpretability, visualisation, and feature selection. He enjoys collaboration and is open to new topics, including projects in partnership with enterprises (industry, IT, etc.).

More information can be found at https://bfrenay.wordpress.com.