Assistant Professor, Data Science, UBC Department of Psychiatry
Email: haoting.wang@ubc.ca
Short Biography
Dr. Hao-Ting Wang is a tenure-track Assistant Professor in Data Science in the Department of Psychiatry, and a member of the Djavad Mowafaghian Centre for Brain Health. Dr. Wang completed her PhD in Cognitive Neuroscience at the University of York, UK, under Professors Jonathan Smallwood and Elizabeth Jefferies. She subsequently held fellowships at the University of York, the Sackler Centre for Consciousness Science at the University of Sussex, and CRIUGM in Montréal, where she worked with Professor Lune Bellec on neuroimaging software and neurodegenerative biomarker discovery. She is a core developer of Nilearn, a widely used open-source Python library for machine learning in human neuroimaging, and recipient of the 2023 Neuro–Irv and Helga Cooper Open Science Prize.
Research Focus
Dr. Wang’s research sits at the intersection of cognitive neuroscience, machine learning, and transdiagnostic psychiatry, combining methods from data science and neuroimaging to link brain activity to psychiatric phenotypes. Her work addresses a central question: how does the brain support the rich, context-dependent cognition of everyday life, and what does this reveal about psychiatric vulnerability? She studies brain function during naturalistic experiences — such as films, video games, and everyday tasks — that engage continuous, real-world cognition that controlled laboratory tasks deliberately suppress. Pairing these paradigms with experience sampling allows her to anchor brain activity to what people are actually thinking and feeling in the moment. Rather than treating psychiatric conditions as categorically distinct, she seeks shared neurocognitive mechanisms that cut across diagnostic boundaries and are measurable at population scale. A core commitment of her research is open and reproducible science. Drawing from her extensive expertise in large open neuroimaging datasets and benchmark building, she aims to develop brain decoding approaches to evaluate and interpret fMRI-based AI models, producing evaluation frameworks the broader community can use.
Significant Accomplishments & Professional Contribution
- 2023 Neuro–Irv and Helga Cooper Open Science Prize
- Canadian Neuroanalytics Scholars Program (2024–2026)
- IVADO Postdoctoral Scholarship (2022–2024)
Community & Open Science:
Core developer, Nilearn
Co-Chair, OHBM Hackathon 2022
