2022 Program

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Wiro Niessen

Wiro Niessen is full professor at both Erasmus MC University Medical Center Rotterdam and Delft University of Technology. He is founder and scientific lead of Quantib an AI company in medical imaging. In 2015 he received the Simon Stevin Meester Award from the Netherlands Organization for Scientific Research. From 2016 to 2019 he was president of the Medical Image Computing and Computer Assisted Interventions Society. In 2017 he was elected to The Netherlands Royal Academy of Arts & Sciences. He is director of the AI platform of the European Organization for Biomedical Imaging Research. His research foci include computer vision biomedical image analysis and computer assisted interventions.

Vincent Vandewalle

Vincent Vandewalle is Full Professor at Université Côte d'Azur since September 2022. He is part of the Inria MAASAI team and is also affiliated with the J.A. Dieudonné lab. His research interest is statistical learning and in particular classification (unsupervised, semi-supervised, supervised) based on generative models. He has proposed models for clustering various types of data and is also interested in the fundamental study of model-based clustering. A part of his research has been directly motivated by applications such as medicine. He is also interested in the dissemination of his research as packages. 

He holds a 3IA chair on « Finding structures in heterogeneous data »  where he will focus on designing generative models able to reveal several clustering viewpoints in the data and adapt them to the deep-learning setting. He will also collaborate with doctors and companies.

Previously, he was Assistant Professor at University of Lille (2010-2022) and member of two research teams: the ULR METRICS on the evaluation of health technologies and medical practices, on the other hand, the Inria MODAL team on the design and study of generative models for learning. He is graduated from the AgroParisTech and University Paris XI (2006), and holds a PhD in applied Mathematics of the University of Lille on Semi-supervised learning (2009).

Daniel Rückert

Daniel Rückert is Professor of Visual Information Processing and former Head of the Department of Computing at Imperial College London.^[2]

He received a Diploma in Computer Science from the Technical University of Berlin and a PhD in Computer Science from Imperial College London entitled Segmentation and tracking in cardiovascular images using geometrically deformable models and templates.^[2]

He is a Fellow of the Royal Academy of Engineering, a Fellow of the Institute of Electrical and Electronics Engineers (IEEE),^[3] and a Fellow of the Academy of Medical Sciences.^[2]

He has an h-index of 111.^[4]

Maxime Sermesant

Maxime Sermesant is a permanent researcher at Inria. He is Head of Computational Cardiology at Inria Epione and Head of Multimodal Data Science at IHU Liryc. He is also the co-founder and scientific advisor of inHEART and co-founder of Therapixel. His research interests include: biomedical image processing organ modelling and machine learning. Since 2005 he is a visiting Lecturer at King’s College London Division of Imaging Sciences St Thomas’ Hospital.

Emmanuel Gobet

Emmanuel Gobet graduated from Ecole Polytechnique - Paris in 1995, he got a PhD degree in probability at University Paris Diderot. He took different academic positions at University Pierre et Marie Curie, Grenoble Institute of Technology and he is currently Professor at Ecole Polytechnique.
He is an expert in Monte Carlo simulations, Machine learning and data science, extremes, risk management, stochastic modelling with applications in Climate change, Energy, Finance. He has written more than 100 papers in international journals and 3 books. He is the scientific leader of the Chair Stress Test, between BNPP Paris and Ecole Polytechnique, which includes a research program on climate change. He is the IP Paris Pedagogy Coordination Director at Hi!PARIS, the center for Artificial Intelligence and Data Science at Institut polytechnique de Paris and HEC. He is also a Scientific Advisor to Kaiko, a major digital finance data provider.

Ioannis Brilakis (Digital Twins-Cambridge)

 

Prof Ioannis Brilakis is a Laing O'Rourke Professor of Construction Engineering and the Director of the Construction Information Technology Laboratory at the Division of Civil Engineering of the Department of Engineering at the University of Cambridge. He completed his PhD in Civil Engineering at the University of Illinois, Urbana Champaign in 2005. He then worked as an Assistant Professor at the Departments of Civil and Environmental Engineering, University of Michigan, Ann Arbor (2005-2008) and Georgia Institute of Technology, Atlanta (2008-2012) before moving to Cambridge in 2012 as a Laing O’Rourke Lecturer. He was promoted to Reader in October 2017 and to Professor in 2021. He has also held visiting posts at the Department of Computer Science, Stanford University as a Visiting Associate Professor of Computer Vision (2014) and at the Technical University of Munich as a Visiting Professor, Leverhulme International Fellow (2018-2019), and Hans Fischer Senior Fellow (2019-2022). He is a recipient of the 2019 ASCE J. James R. Croes Medal, the 2018 ASCE John O. Bickel Award, the 2013 ASCE Collingwood Prize, the 2012 Georgia Tech Outreach Award, a 2010 NSF CAREER award, and a 2009 ASCE Associate Editor Award. Dr Brilakis is an author of over 200 papers in peer-reviewed journals and conference proceedings, an Associate Editor of the ASCE Computing in Civil Engineering, ASCE Construction Engineering and Management, Elsevier Automation in Construction, and Elsevier Advanced Engineering Informatics Journals, and the lead founder of the European Council on Computing in Construction.

Philippe Despres

Professeur titulaire, Faculté des sciences et de génie, Université Laval Directeur, Centre de recherche en données massives (CRDM) Co-responsable de l’axe Santé durable, OBVIA Conseiller en architecture de données, PULSAR.
Philippe Després est professeur titulaire au Département de physique, de génie physique et d’optique de l’Université Laval. Il est également membre du Centre de recherche sur le cancer de l’Université Laval, ainsi que physicien médical au CHU de Québec – Université Laval.
Après une maîtrise à l’Université Laval (2000, Physique) et un doctorat à l’Université de Montréal (2005, Physique), il a réalisé un stage postdoctoral (2005-2007) à University of California, San Francisco dans le domaine du génie biomédical et de l’imagerie moléculaire. Ses projets de recherche portent sur les aspects matériels et logiciels de l’imagerie médicale, notamment sur la reconstruction tomographique. Il a été un pionnier du calcul informatique de pointe sur processeurs graphiques (GPU), menant au développement d’applications innovantes en physique médicale, notamment un code de transport radiatif Monte Carlo ultra-rapide basé sur GPU (GPUMCD). Il s’intéresse aussi à la valorisation des données dans le milieu médical, en particulier aux infrastructures, aux normes et aux bonnes pratiques (incluant les principes FAIR) nécessaires à l’exploitation responsable de l’information clinique.

Ernesto Damiani

Ernesto Damiani is Full Professor at Università degli Studi di Milano, Director of Center for Cyber Physical Systems (C2PS) within the Khalifa University, leader of the Big Data area at Etisalat British Telecom Innovation Center, and President of the Consortium of Italian Computer Science Universities (CINI). He is also part of the ENISA Ad-Hoc Working Group on Artificial Intelligence Cybersecurity, where he serves as Rapporteur.

According to DBLP (January 2021), Ernesto Damiani has authored 137 journal papers, 336 refereed articles in proceedings of international conferences, and published 57 books and chapters as an author or editor. According to Google Scholar, Ernesto’s work has been cited more than 18,200 times and his h-index is 57; 291 of his papers have at least 10 citations. On Scopus he has 616 documents and more than 7,100 total citations by more than 5,600 documents. His Scopus h-index is 36. With 542 publications listed on DBLP, he is considered among the most prolific European computer scientists.

His areas of interest include cyber-physical systems, Big Data Analytics, Edge/Cloud security and performance, Artificial Intelligence, and Machine Learning. Ernesto Damiani has pioneered model-driven data analytics. Ernesto has been a recipient of the Stephen Yau Award from the Service Society, of the Outstanding contributions Award from IFIP TC2, of the Chester-Sall Award from IEEE IES, and of a doctorate honoris causa from INSA – Lyon (France) for his contribution to Big Data teaching and research.

Cesar A. Hidalgo

Cesar A. Hidalgo directs the Center for Collective Learning at the Artificial and Natural Intelligence Institute (ANITI, University of Toulouse. Prior to joining ANITI, he directed the Collective Learning group at MIT. Hidalgo holds a PhD in Physics from the University of Notre Dame, and is the author of dozens of peer-reviewed papers and three books. His latest book is How Humans Judge Machines (MIT Press, 2021).
 

Alexandre M. BAYEN

Alexandre Bayen received the Engineering Degree in applied mathematics from the Ecole Polytechnique, France, in July 1998, the M.S. degree in aeronautics and astronautics from Stanford University in June 1999, and the Ph.D. in aeronautics and astronautics from Stanford University in December 2003. He was a Visiting Researcher at NASA Ames Research Center from 2000 to 2003. Between January 2004 and December 2004, he worked as the Research Director of the Autonomous Navigation Laboratory at the Laboratoire de Recherches Balistiques et Aerodynamiques, (Ministere de la Defense, Vernon, France), where he holds the rank of Major. He has been an Assistant Professor at UC Berkeley since January 2005, and an Associate Professor since 2010.

Bayen has authored one book and over 100 articles in peer reviewed journals and conferences. He is the recipient of the Ballhaus Award from Stanford University, 2004, of the CAREER award from the National Science Foundation, 2009 and he is a NASA Top 10 Innovators on Water Sustainability, 2010. His projects Mobile Century and Mobile Millennium received the 2008 Best of ITS Award for ‘Best Innovative Practice’, at the ITS World Congress and a TRANNY Award from the California Transportation Foundation, 2009. Bayen is the recipient of the Presidential Early Career Award for Scientists and Engineers (PECASE) award from the White House, 2010. Mobile Millennium has been featured more than 100 times in the media, including TV channels and radio stations (CBS, NBC, ABC, CNET, NPR, KGO, the BBC), and in the popular press (Wall Street Journal, Washington Post, LA Times).

Learn more about Alexandre Bayen

Anna KRESHUK

Anna Kreshuk joined EMBL in July 2018 as a Group Leader in the Cell Biology and Biophysics Unit. Her research focuses on machine learning-based methods for the analysis of biological images. Right now, she is especially interested in large-scale image and volume segmentation, using sparse or weak supervision. Besides, Anna is leading the development of the ilastik software, aiming to make such methods available to life scientists without computational expertise. Previously, she was a PostDoc at the Heidelberg Collaboratory for Image Processing and a visiting scientist at the HHMI Janelia Research Campus. Anna holds a PhD in Computer Science from the University of Heidelberg and a Diploma in Mathematics from Lomonosov Moscow State University. In between the two degrees, she worked at CERN in Geneva as a scientific programmer for the ROOT framework.

Joshua GANS

Joshua Gans is a Professor of Strategic Management and holder of the Jeffrey S. Skoll Chair of Technical Innovation and Entrepreneurship at the Rotman School of Management, University of Toronto (with a cross appointment in the Department of Economics). Joshua is also Chief Economist of the University of Toronto's Creative Destruction Lab. Joshua holds a Ph.D. from Stanford University and an honors degree in economics from the University of Queensland. In 2012, Joshua was appointed as a Research Associate of the NBER in the Productivity, Innovation and Entrepreneurship Program.
At Rotman, he teaches MBA students entrepreneurial strategy. He has also co-authored (with Stephen King and Robin Stonecash) the Australasian edition of Greg Mankiw's Principles of Economics (published by Cengage), Core Economics for Managers (Cengage), Finishing the Job (MUP), Parentonomics (New South/MIT Press) and Information Wants to be Shared (Harvard Business Review Press) and The Disruption Dilemma (MIT Press, 2016); Scholarly Publishing and its Discontents (2017), Prediction Machines: The Simple Economics of Artificial Intelligence (HBR Press, 2018) and Innovation + Equality (MIT Press, 2019) and The Pandemic Information Gap: The Brutal Economics of Covid-19 (MIT Press, 2020). His most recent book is The Pandemic Information Solution: Overcoming the Brutal Economics of Covid-19 (2021).

Lucilla SIOLI

Ms Lucilla Sioli is the Director for "Artificial Intelligence and Digital Industry" within Directorate-General CONNECT at the European Commission. She is responsible for the coordination of the European digitisation of industry strategy and for policy development in the area of artificial intelligence (AI). The directorate also supports R&D&I in key digital industrial technologies including microelectronics, photonics, robotics and AI. Lucilla holds a PhD in economics from the University of Southampton (UK) and one from the Catholic University of Milan (Italy) and has been a civil servant with the European Commission since 1997.

Laurent Daudet

Laurent Daudet is currently employed as CTO at LightOn, a startup he co-founded in 2016, where he manages cross-disciplinary R&D projects, involving machine learning, optics, signal processing, electronics, and software engineering. Laurent is a recognized expert in signal processing and wave physics, and is currently on leave from his position of Professor of Physics at the Université de Paris. Prior to that or in parallel, he has held various academic positions: fellow of the Institut Universitaire de France, associate professor at Universite Pierre et Marie Curie, Visiting Senior Lecturer at Queen Mary University of London, UK, Visiting Professor at the National Institute for Informatics in Tokyo, Japan. Laurent has authored or co-authored more than 200 scientific publications, has been a consultant to various small and large companies, and is a co-inventor in several patents. He is a graduate in physics from Ecole Normale Superieure in Paris, and holds a PhD in Applied Mathematics from Marseille University.

Matthias Niessner

Dr. Matthias Nießner is a Professor at the Technical University of Munich where he leads the Visual Computing Lab. Before, he was a Visiting Assistant Professor at Stanford University. Prof. Nießner’s research lies at the intersection of computer vision, graphics, and machine learning, where he is particularly interested in cutting-edge techniques for 3D reconstruction, semantic 3D scene understanding, video editing, and AI-driven video synthesis. In total, he has published over 100 academic publications, including 23 papers at the prestigious ACM Transactions on Graphics (SIGGRAPH / SIGGRAPH Asia) journal and 44 works at the leading vision conferences (CVPR, ECCV, ICCV); several of these works won best paper awards, including at SIGCHI’14, HPG’15, SPG’18, and the SIGGRAPH’16 Emerging Technologies Award for the best Live Demo. Prof. Nießner’s work enjoys wide media coverage, with many articles featured in main-stream media including the New York Times, Wall Street Journal, Spiegel, MIT Technological Review, and many more, and his was work led to several TV appearances such as on Jimmy Kimmel Live, where Prof. Nießner demonstrated the popular Face2Face technique; Prof. Nießner’s academic Youtube channel currently has over 5 million views. For his work, Prof. Nießner received several awards: he is a TUM-IAS Rudolph Moessbauer Fellow (2017 – ongoing), he won the Google Faculty Award for Machine Perception (2017), the Nvidia Professor Partnership Award (2018), as well as the prestigious ERC Starting Grant 2018 which comes with 1.500.000 Euro in research funding; in 2019, he received the Eurographics Young Researcher Award honoring the best upcoming graphics researcher in Europe.In addition to his academic impact, Prof. Nießner is a co-founder and director of Synthesia Inc., a brand-new startup backed by top-tier investors (incl. Marc Cuban, LDV, FirstMark), whose aim is to empower storytellers with cutting-edge AI-driven video synthesis.

Gabriel Peyré

Gabriel Peyré is a research director at the CNRS, in the Department of Mathematics and Applications at the Ecole Normale Supérieure and a lecturer at the ENS. His work is at the interface between applied mathematics, imaging and machine learning. He is involved in reproducible research and code education, in particular through the www.numerical-tours.com platform. He has been awarded 2 ERC grants (starting grant SIGMA-Vision in 2010 and consolidator grant NORIA in 2016), the Blaise Pascal Prize of the Academy of Sciences 2017, the Magenes Prize of the Italian Mathematical Union 2019 and the CNRS Silver Medal 2021. He is the deputy scientific director of the 3IA Prairie Institute, director of the ENS data center and the ELLIS Paris Unit and former director of the GdR CNRS MIA.

Alan Moses

Alan M Moses is currently Professor and Canada Research Chair in Computational Biology in the Departments of Cell & Systems Biology and Computer Science at the University of Toronto. His research touches on many of the major areas in computational biology, including DNA and protein sequence analysis, phylogenetic models, population genetics, expression profiles, regulatory network simulations and image analysis. Dr. Moses and his research team are developing computational and statistical techniques that will use biological data to understand how molecules create cells’ complex behaviours, identify which genetic mutations cause cellular malfunctions, and which lead to evolution.

Francesca Rossi

Francesca Rossi is an IBM Fellow and the IBM AI Ethics Global Leader. She is a computer scientist with over 30 years of experience in AI research, on which she published more than 220 articles in top AI journals and conferences. She co-leads the IBM AI ethics board and she actively participate in many global multi-stakeholder initiatives on AI ethics. She is a member of the board of directors of the Partnership on AI and the industry representative in the steering committee of the Global Partnership on AI. She is a fellow of both the worldwide association of AI (AAAI) and of the European one (EurAI), and she will be the next president of AAAI.

Ricardo Vinuesa

Holger Hoos