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Our mission is to create methods to fit the science and not make science fit the methods.

Specifically, we are interested in the following questions that have clinical relevance:

1. Neurodegeneration – How can we develop software frameworks that can assist neurology practitioners in various real-world settings?
2. Digital pathology – How can we build clinical-grade software tools to complement the pathologist workflow?

We are also interested in the following frameworks that have computational relevance:

1. Multimodal machine learning – Efficient design of AI agents for multimodal data processing with incomplete information.
2. Representation learning – Construction of efficient neural networks on high resolution data to process local and contextual information.

Joining our laboratory

We form small teams comprising individuals with complementary expertise and work persistently to build comprehensive solutions.

Important: If you are interested in joining us, then we encourage you to contact an active lab member (click on Team) and talk about your interests.

Funding

We are grateful for funding from the American Heart Association, the National Institute on Aging, the National Heart, Lung, and Blood Institute, the National Cancer Institute, the Artificial Intelligence and Technology Collaboratories (AITC) for Aging Research program, and the National Institute of Diabetes and Digestive and Kidney Diseases. We also thank the Karen Toffler Charitable Trust, Gates Ventures, Pfizer, Johnson & Johnson Enterprise Innovation Inc., and Visterra Inc., for funding our work.

Teaching

– Machine learning (MS650)

– Guest lectures (BF831; HM817; FC713; EC500)