The cohort
Meet the 2026 cohort
40 late-stage PhD students and early-career postdocs in machine learning for health, selected from a competitive applicant pool to spend the week together. Explore their work below.
Guilherme Imai Aldeia
Interpretable AI for brain-disorder diagnosis
Boston Children's Hospital, Harvard Medical School
Tahmina Sultana Priya
Explainable patient subtyping for precision medicine
Department of Computer Science, Virginia Polytechnic Institute and State University
Zhongyu Li
Machine learning for hidden cancer risk in diabetes
Emory University, Rollins School of Public Health
Hangyul Yoon
Physician-scientist building medical vision-language AI
Korea Advanced Institute of Science and Technology (KAIST)
Ben Fox
Foundation models for sleep and physiological signals
Icahn School of Medicine at Mount Sinai
Sameer Neupane
Multimodal AI for mental health and neurodevelopmental screening
University of California San Francisco
Chase Fensore
Generative AI for personalized clinical care
Emory University, Department of Computer Science
Ferdaous Idlahcen
Computational pathology for gynecologic oncology
Mohammed VI Polytechnic University – Faculty of Medical Sciences & UM6P Hospitals
Anders Gjølbye
Trustworthy EEG foundation models for neurodiagnostics
Technical University of Denmark / Stanford University
Dipendra Pant
Causal decision support for youth mental health
Norwegian University of Science and Technology (NTNU)
For accepted students
Getting ready for the week
Start with the Before you arrive checklist — readings, your specialty track, and what to bring. Session materials and the day-by-day curriculum live alongside it.