About me

I am an Instructor at McLean Hospital and Harvard Medical School (I go by Lily). My research develops computational approaches to study brain–behavior relationships under real-world heterogeneity, with a focus on aging, neuropsychiatric symptoms, and Alzheimer’s disease and related dementias (ADRD). I use multimodal neuroimaging, biomarkers, electronic health records (EHR), text-derived phenotypes, and multi-cohort datasets as complementary sources of evidence to identify brain–behavior patterns that are robust across contexts, context-specific, or individualized.

At McLean, I work with Prof. Lisa D. Nickerson in the Applied Neuroimaging Statistics Research (ANSR) Lab at the McLean Imaging Center and Prof. David Harper in the Division of Geriatric Psychiatry. My current work extends and applies multimodal data-fusion approaches—including SuperBigFLICA—to study aging, dementia, and neuropsychiatric symptoms across large, heterogeneous datasets. I conceptualize this broader direction as computational neuroecology: using computational models and multi-source data to study brain–behavior relationships in the heterogeneous real-world settings where cognition, symptoms, and clinical outcomes emerge. This research is supported by an Alzheimer’s Association Research Fellowship (AARF) (2026–2029) investigating network rigidity underlying neuropsychiatric symptoms in Alzheimer disease.

Before joining McLean, I was a Postdoctoral Research Fellow at Massachusetts General Hospital / Harvard Medical School, where I worked with Prof. Sudeshna Das in the MIND Data Science Lab on deep learning and NLP approaches for characterizing dementia from heterogeneous clinical data.

I received my Ph.D. in Cognitive Sciences (Cognitive Neuroscience) from the University of California, Irvine, where I worked with Prof. Elizabeth R. Chrastil studying the neural mechanisms of human spatial navigation—how the brain computes travel direction, trajectory planning, and spatial decision-making—using psychophysics, fMRI, and computational modeling.

Underlying this trajectory is training across experimental psychology, cognitive neuroscience, and geography. That interdisciplinary lens shapes how I approach neuroscience: cognition is situated in context, varies across spatial and demographic scales, and understanding these dimensions is essential for developing equitable approaches to brain health.