Keynote Speakers

Bio: Prof. Anita Burgun is a full professor of biomedical informatics and statistics at Université Paris Cité. She leads the Departments of Medical Informatics at Georges Pompidou European Hospital and Necker Children's Hospital. She holds a Chair at the Institut 3IA Prairie and is a senior researcher in the Clinical Bioinformatics team at the Imagine Institute of Genetic Diseases. Her research focuses on clinical and translational biomedical informatics, large-scale health data integration, and data-driven approaches for precision medicine. Prof. Burgun is an internationally recognized expert in biomedical informatics, serving as a reviewer for the European Research Council and as an expert evaluator for the Canada Foundation for Innovation. She has represented France at the International Medical Informatics Association since 2011 and has been a Fellow of the International Academy of Health Sciences Informatics since 2023.

Bio: Dr. Hoifung Poon is the General Manager at Microsoft Research, where he leads the Real-World Evidence (RWE) research group to advance AI in precision health. His research interests focus on developing next-generation AI technology to accelerate progress in access, safety, and preventative care. He leads biomedical AI research and incubation at Microsoft, with a particular focus on scaling real-world evidence generation by structuring all medical data, including biomedical large language models (LLMs), multimodal learning, and causal learning. Dr. Poon has been recognized as the "Technology Champion" of 2024 by the Puget Sound Business Journal. His work spans diverse topics in machine learning and natural language processing (NLP), earning Best Paper Awards at top conferences such as NAACL, EMNLP, and UAI. He is among the first to develop and apply large language models in biomedicine (e.g., PubMedBERT, BioGPT). He received his Ph.D. in Computer Science and Engineering from the University of Washington and his B.S. in Computer Science from Sun Yat-Sen University. He is also an affiliated faculty member at the University of Washington Medical School.

Abstract: Alzheimer’s disease and related dementias (ADRD) remain a critical public health challenge, demanding new strategies to elucidate disease mechanisms, identify biomarkers, and improve support for patients and caregivers. Advances in AI and informatics now enable the integration of large-scale genetics, multi-omics, brain imaging, and clinical data, providing unprecedented opportunities to uncover genetic factors, mechanistic pathways, and multimodal endophenotypes underlying ADRD. This talk will highlight recent progress in brain imaging omics and the development of AI methods that support reliable diagnosis, individualized risk stratification, and data-driven disease staging. We will also explore the growing role of trustworthy multimodal and generative AI, including interpretable and responsible models and large language models augmented with domain knowledge, in accelerating discovery. Finally, emerging work that analyzes conversational data and social media offers new opportunities to understand caregiver needs and to build intelligent, scalable support tools. Together, these advances illustrate how AI-driven informatics can deepen understanding of ADRD while strengthening care for aging adults and their caregivers.

Bio: Dr. Li Shen is a Professor of Informatics, Radiology, and Computer and Information Science at the University of Pennsylvania. He serves as Interim Director of the Informatics Division in the Department of Biostatistics, Epidemiology and Informatics, Associate Director for Bioinformatics at the Penn Institute for Biomedical Informatics, and Co-Director of the Penn Center for AI and Data Science for Integrated Diagnostics. Dr. Shen is a pioneer in brain-wide genome-wide association studies for Alzheimer’s disease. His research spans artificial intelligence and machine learning, biomedical and health informatics, NLP and large language models, medical image computing, network science, and multi-omics and systems biology, with broad applications to complex diseases. His work focuses on developing and applying trustworthy AI and informatics methods to analyze large-scale biobank and healthcare datasets, with the goal of improving disease understanding, early detection, prevention, and care. Dr. Shen has served on numerous journal editorial boards, grant review panels, and conference organizing committees. He is a Fellow of AIMBE, ACMI, and AMIA, an ACM Distinguished Member, and a Distinguished Contributor of the IEEE Computer Society.