Confirmed Speakers
Day 2: AI for Health Sciences
Ramesh Raskar
Associate Professor of Media Arts & Sciences, Massachusetts Insitute of Technology
Who will keep the Agentic Web Open and Neutral? The NANDA architecture at MIT
Bio
Ramesh Raskar is an Associate Professor at the Massachusetts Institute of Technology (MIT), leading pioneering research at the intersection of distributed AI agent architectures, health technology, and computational imaging. As a founding architect of Nanda, he focuses on agentic web infrastructure that empowers decentralized decision-making in complex systems, including health data platforms. He received the National Academy of Inventors award (2024), Lemelson Award (2016), ACM SIGGRAPH Achievement Award (2017), DARPA Young Faculty Award (2009), Alfred P. Sloan Research Fellowship (2009), TR100 Award from MIT Technology Review (2004) and Global Indus Technovator Award (2003). He has worked on special research projects at Google [X], Apple and Facebook and co-founded/advised several companies. He holds 100+ US patents.
Edward Jung
Co-Founder and CTO, Intellectual Ventures
Towards Realizing Health Value Model with Supercomputers
Bio
Edward Jung is a global expert in innovation ecosystems, with 40 years of experience in software, R&D, entrepreneurship, and startups in multiple countries, with scientific expertise in mathematical physics and biophysics. An avid inventor and entrepreneur, Edward holds more than 1,200 issued patents and founded more than 40 organisations in the areas of biomedicine, computing, networking, energy, and material sciences. Edward founded Intellectual Ventures in 1999 after leaving Microsoft Corporation, where he was chief architect and co-founder of Microsoft Research. His biomedical research in the 1980s in protein structure and function was published in journals including the Proceedings of the National Academy of Sciences and the Journal of Biochemistry. Edward has served as an advisor to numerous non-commercial organisations, including the National Academy of Sciences, Harvard Medical School, the Bill and Melinda Gates Foundation and World Health Organization.
Jordi Cabot
FNR Pearl Chair and Head of the Software Engineering RDI Unit, Luxembourg Institute of Science and Technology
Sandbox for Multi-Agent Systems
Bio
Jordi Cabot is the FNR Pearl Chair and head of the Software Engineering RDI team at the Luxembourg Institute of Science and Technology (LIST). He is also an Affiliate Professor in Computer Science at the University of Luxembourg. Previously, he has been an ICREA Research Professor at Internet Interdisciplinary Institute, the Research center of the Open University of Catalonia (UOC) where he led the SOM Research Lab. He was also Visiting Professor at the Western Norway University of Applied Sciences, associate professor at École des Mines de Nantes as part of an Inria International Chair, postdoc at the University of Toronto, researcher at the Politecnico di Milano and the Technical University of Catalonia and co-founded two startups. He received his PhD degree in Computer Science from Universitat Politècnica de Catalunya (UPC) in 2006 and his Habilitation (French HdR) from the École Doctorale in Nantes in 2012. His research interests include software modeling and low-code technologies, pragmatic formal model verification, analysis of open source/open data communities and the role AI can play in software development (and vice versa). For more information, visit https://jordicabot.com
Rajat Mani Thomas
Assistant Professor of Research in Systems and Computational Biomedicine, Weill Cornell Medical College
Designing Agentic AI Workflows Through the Lens of Systems Thinking
Bio
Rajat is a distinguished faculty member in AI at Weill Cornell Medicine in Qatar. He leads the Thomas Lab for AI in Healthcare where his team focuses on translational AI working alongside major hospitals in Qatar. Holding a PhD in computational astrophysics, Rajat’s early work explored the structures of the early universe. His interests later shifted to Neuroscience and subsequently to machine learning and AI. Rajat has authored numerous peer-reviewed papers in Astrophysics, Neuroscience, and Machine Learning. Currently, he focuses on applying AI solutions in clinical settings and everyday life. Additionally, Rajat co-founded a successful AI company in agriculture, demonstrating his versatility and impact in various fields.
Huazhu Fu
Principal Scientist, A*STAR, Singapore
Trustworthy Medical AI: Addressing Reliability and Explainability in Vision-Language Models for Healthcare
Bio
Dr. Huazhu Fu is a Principal Scientist at the Institute of High Performance Computing (IHPC), A*STAR, Singapore. His research focuses on medical image analysis, AI for healthcare, and trustworthy AI. With over 200 publications in leading conferences and prestigious journals, including Nature Communications, Cell Reports Medicine, and IEEE TPAMI. His works have garnered more than 33,000 citations on Google Scholar. Dr. Fu has received numerous accolades, including Best Paper Awards at ICME 2021, MICCAI-OMIA 2022, MICCAI-DeCAF 2023, and MICCAI-OMIA 2024. He has been recognized as a "Highly Cited Researcher" by Clarivate and among the "Top 2% Scientists Worldwide" by Stanford. He serves as an Associate Editor for several distinguished journals: IEEE TMI, IEEE TNNLS, and IEEE JBHI.
Mohammad Yaqub
Associate Professor of Computer Vision, MBZUAI
The Medical Multimodal Mind: Building Foundation Models for Health
Bio
Dr Yaqub is an associate professor at Mohamed bin Zayed University of Artificial Intelligence (MBZUAI), Abu Dhabi, UAE. Dr. Yaqub leads the BioMedIA group at MBZUAI. He completed his PhD in Biomedical Engineering from the University of Oxford. His domain knowledge is Artificial Intelligence (AI), machine learning, and biomedical health & image analysis. He has published over 80 peer-reviewed articles, has 6 patents, co-edited 2 books, and secured many national and international grant funding. He is also an honorary research fellow at the Nuffield Department of Clinical Neurosciences (NDCN), University of Oxford. Dr. Yaqub founded Labib AI, MBZUAI's first start-up based in Abu Dhabi. Finally, Dr. Yaqub is the general chair for MICCAI 2026, the world's top AI in medical imaging conference that will be held in Abu Dhabi.
Miguel Hernan
Kolokotrones Professor of Biostatistics and Epidemiology and Director of CAUSALab, Harvard University
Decentralized AI and Multi-Agent Systems
Bio
Professor Miguel Hernán uses health data and causal inference methods to learn what works. As Director of the CAUSALab at Harvard, he and his collaborators repurpose real world data into scientific evidence for the prevention and treatment of infectious diseases, cancer, cardiovascular disease, and mental illness. His work shapes health policy and research methodology worldwide. Professor Hernán joined the Harvard School of Public Health in 1999, becoming a professor in 2011 before being appointed Kolokotrones Professor of Biostatistics and Epidemiology, Harvard T.H. Chan School of Public Health in 2016. In 2021, Prof Hernán was named Director, CAUSALab, Harvard T.H. Chan School of Public Health, and he is also an Associate Member, Broad Institute of MIT and Harvard. He is currently as Associate Editor of Annals of Internal Medicine, and Editor Emeritus of Epidemiology, and previously as Associate Editor of Biometrics, American Journal of Epidemiology, and Journal of the American Statistical Association. Professor Hernán has been awarded the Rousseeuw Prize for Statistics, Rothman Epidemiology Prize, and the MERIT award from the National Institutes of Health and has been elected Fellow of the American Association for the Advancement of Science and of the American Statistical Association.
Francisco "Paco" Herrera
Professor of Computer Science and AI, DaSCI Research Institute, University of Granada. Member of the Royal Academy of Sciences (Spain).
Operationalizing Responsible AI: The Responsible AI Systems Framework and Emerging Challenges
Bio
Professor Herrera received his M.Sc. in Mathematics in 1988 and Ph.D. in Mathematics in 1991, both from the University of Granada, Spain. He is an academician of the Royal Academy of Engineering (Spain). He has published over 600 journal papers, received more than 130,000 citations (Scholar Google, H-index 173), and is an editorial member of a dozen academic journals. Professor Herrera has been nominated as a Highly Cited Researcher in Computer Science, Engineering, and Clarivate Analytics). His current research interests include computational intelligence, information fusion and decision-making, explainable artificial intelligence, and data science (including data preprocessing, prediction, and big data).