Harvard Catalyst Profiles

I am the Director of the Applied Neuroimaging Statistics Research Lab at McLean Hospital, which focuses on developing and applying novel machine learning and statistical methods for multimodal neuroimaging data analysis for research on Alzheimer's Disease, drug use and psychiatric disorders. Current research involves combining large-scale open access neuroimaging datasets including HCP, CRHD, ADNI and others with computational approaches such as tensor and matrix decomposition methods, including ICA and linked ICA for data fusion, normative modeling and other techniques to investigate brain structure and function. Current funding includes a five-year R01 to utilize the Human Connectome Project (HCP) Lifespan and Connectomes Related to Human Disease datasets to investigate neuropsychiatric symptoms in Alzheimer's Disease. I provide statistical support, training, and mentoring for students and junior scientists, and I teach seminars and courses on imaging statistics, resting state and task fMRI data processing, multivariate data-driven methods and other imaging analysis topics at Harvard and MIT. I am also a biostatistics consultant for the Harvard Catalyst, a faculty member of the Harvard Mind Brain Behavior and the Harvard Data Science Initiatives and act as mentor to students and post-docs through the HDSI MIND project. My lab is currently accepting new student trainees and I am currently seeking a post-doctoral fellow for a NIDA T32 position for training in neuroimaging of substance use and a post-doctoral fellow to work on an NIA-funded R01 on Multimodal Computational Neuroimaging: Big Data, Neuropsychiatric Symptoms and Alzheimer’s Disease.

• Neuroimaging
• Biostatistics
• Machine Learning
• Addiction, Substance
• Mental Disorders
• Brain Networks
• Functional Connectivity
• Alzheimer's Disease