Our team consists of post-docs, students, research scientists, and clinical collaborators. For information about how to join us, see our FAQ section.
My research focuses on advancing machine learning and artificial intelligence, and using these to transform health care.
Rebecca’s research interests include developing methods to learn disease progression models and discover new biological insights for precision medicine applications. She works on machine learning algorithms that can utilize clinical and genomic data for this purpose, with a particular focus on single cell RNA-sequencing data and cancer.
Hunter’s research focuses on understanding and improving the performance of machine learning algorithms in the wild, with particular applications in MAP inference for graphical models, stochastic optimization, and weak supervision.
My research lies at the intersection between NLP and HCI. I am interested in understanding languages in scientific, legal, or clinical text from documents that are authored and used by domain experts. With newly developed NLP approaches, I study how they can enable better Human-AI collaboration to assist experts in these high-stake settings.
Ilker focuses on developing reliable causal inference methods that can leverage rich and heterogeneous sources of data and can be applied in practice.
Lab roles and post-lab positions are respectively shown.
Barbara’s research focuses on how machine learning-augmented electronic health records can engage patients and support clinical decision making, particularly in the field of Hematology and Oncology.
Harvard medical student
PhD Student, University of Copenhagen
Citadel
Private Investment Firm
Google Brain
Apple
Internal Medicine Resident, Stanford University
Master’s student, Stanford
PhD student, Brown