Distinguished Speakers

Chief of Health Innovation and Roger and Joelle Burnell Professor, Cornell Tech

Tanzeem Choudhury is Chief of Health Innovation and Burnell Professor at Cornell Tech, where she directs the People-Aware Computing Lab. A pioneer of 'Reality Mining,' she developed the Sociometer at the MIT Media Lab and has since created foundational systems for digital mental health including BeWell, StressSense, and MoodRhythm. She co-founded two health AI companies, HealthRhythms and Dapple Health, and her recent research explores how large language models can augment clinical psychotherapy and the reliability of ML tools for mental health prediction across diverse populations. She has published over 190 papers with more than 22,000 citations.

Assistant Professor, Center for Human Genetics & Genomics, NYU Grossman School of Medicine

Nadav Brandes is an Assistant Professor at NYU Grossman School of Medicine with appointments in the Center for Human Genetics & Genomics and the Department of Biochemistry and Molecular Pharmacology. He was among the first researchers to develop protein language models as global predictors of protein structure and function, and his landmark 2023 Nature Genetics paper used ESM1b to predict the effects of all approximately 450 million possible missense variants in the human genome. He also created ProteinBERT, a protein language model cited over 640 times, and collaborated with Jennifer Doudna and Carl June on mitigation of CRISPR-Cas9-induced chromosome loss in primary human T cells, published in Cell.

Professor of Pathology, Molecular and Cell-Based Medicine, Neuroscience, and AI & Human Health; Vice Chair for AI, Department of Pathology, Icahn School of Medicine at Mount Sinai

John F. Crary is a tenured Professor of Pathology, Molecular and Cell-Based Medicine, Neuroscience, and Artificial Intelligence and Human Health at the Icahn School of Medicine at Mount Sinai, where he serves as Vice Chair for Artificial Intelligence in the Department of Pathology and founding director of the Neuropathology Brain Bank and Research CoRE. A board-certified neuropathologist, he led the 2014 international consensus defining Primary Age-Related Tauopathy (PART), cited over 1,130 times, and identified the JADE1 gene as a novel genetic risk factor for tau pathology. He developed HistoAge, the first AI algorithm to predict biological brain age from histopathology slides, and collaborated on an AI system detecting alpha-synuclein pathology in peripheral biopsy tissue with 99% sensitivity and specificity (clinical PD prediction ~71%/65%).

Associate Professor of Biostatistics and Computer Science & Engineering, NYU; Director, Center for Health Data Science

Rumi Chunara is an Associate Professor of Biostatistics at the NYU School of Global Public Health and of Computer Science and Engineering at NYU Tandon, where she directs the Center for Health Data Science. She pioneered the use of social media data for real-time disease surveillance, demonstrated that utilizing big data without domain knowledge impacts public health decision-making (PNAS, 2024), and published research assessing and mitigating algorithmic bias in predictive models at NYC Health + Hospitals (npj Digital Medicine, 2025). Her influential Nature Machine Intelligence paper introduced a framework grounded in the Social Ecological Model for developing equitable health algorithms.

Research Professor, Departments of Population Health and Medicine, NYU Grossman School of Medicine

Yindalon (Yin) Aphinyanaphongs is a Research Professor at NYU Grossman School of Medicine and director of the Division of Applied AI Technologies, Predictive Analytics Unit, and Operational Data Science at NYU Langone Health. He co-led the development of NYUTron, a clinical large language model trained on 7.25 million patient-care notes published in Nature in 2023. His mortality prediction system has been associated with a fivefold increase in goals-of-care conversations and a reduction in the Vizient Mortality Index. Under his leadership, NYU Langone has deployed over 31 AI models in operational use and rolled out GenAI Studio, providing HIPAA-compliant generative AI to over 1,000 applicants.