Session 3 - Can AI, Data and Robotics Research be Open and Accessible to All? Exploring the challenges

11:00 AM to 12:30 PM
Studio 5

This session examines whether AI, data and robotics research can be open and accessible to all. Participants will explore the challenges of making advanced research universally available, including issues related to intellectual property, data privacy and equal access. The discussion will draw on insights from experts on how to overcome these obstacles and promote a more inclusive approach to technological progress. Join us to engage in a critical dialogue on democratizing research and ensuring that the benefits of AI, data and robotics are shared by all.

Meet the speakers

  • Gianluca Bontempi

    MODERATOR

    Co-director of Machine Learning Group at Unversité Libre de Bruxelles

    Gianluca Bontempi is Full Professor in the Computer Science Department at the Université Libre de Bruxelles (ULB) and co-head of the ULB Machine Learning Group. He has been Director of (IB), the ULB/VUB Interuniversity Institute of Bioinformatics in Brussels from 2013-2017. His main research interests are big data mining, machine learning, bioinformatics, causal inference, predictive modeling and their application to complex tasks in engineering and life science. He was Marie Curie fellow researcher. He was awarded in two international data analysis competitions and took part to many research projects in collaboration with universities and private companies all over Europe. He is Belgian (French Community) national contact point of the CLAIRE network, co-leader of the CLAIRE COVID19 Task Force and IEEE Senior Member. He is also co-author of several open-source software packages for bioinformatics, data mining and prediction.

  • Judith Berniaux

    SPEAKER

    Research Data Officer at University at RISE ULiège

    Judith Biernaux completed a PhD in Space Sciences in 2018 at ULiège. After a few industry R&D positions, she returned to ULiège as Research Data Officer. Her mission is to support researchers from all ULiège’s 11 Faculties in complying with demands, regulations, and recommendations on research data management. Her tasks include designing educational resources, collective or individual training, and developing university-wide data management tools, promoting the FAIR data principles. Through interuniversity projects, including the FWB Data Ambassadors community management, she hopes to help defining responsible research data standards to enhance openness, reproducibility, and integrity.

  • Mélanie Marcel

    SPEAKER

    Expert in Responsible Research & Innovation and CEO of SoScience

    Mélanie Marcel is the founder and CEO of SoScience, a startup she established following her research in brain-machine interfaces as an engineer specializing in wave physics and neuroscience at ESPCI. SoScience is renowned for its expertise in responsible research and innovation (RRI), which integrates social and environmental impacts from the outset of the innovation process. Melanie's deep knowledge of RRI led to her selection as an expert by the European Commission to help shape this pioneering concept. She advises both private and public sector entities on cutting-edge practices in research and innovation. In 2017, Melanie authored "Science et Impact Social: vers une innovation responsable" published by Editions Diateino, highlighting her commitment to sustainable and ethical innovation practices.

  • François Terrier

    SPEAKER

    Deputy Director for Programs of CEA-List Institute Director of PEPR IA, national priority research on AI

    François Terrier is the head of the System and Software Engineering department at the LIST Institute of CEA Tech. He focuses on developing open tool chains for trustworthy software and systems, covering the entire development cycle from requirements to integration. François has been instrumental in advancing modeling standards such as OMG MARTE, SysML, and AUTOSAR WG, and has led the CEA's involvement in these areas. His current research includes combining domain-oriented modeling with formal methods for high-quality, safety-critical systems. He also spearheads CEA List's program on Trustworthy Artificial Intelligence.