Jill Rubinstein, MD, PhD

Computational Oncology studies that integrate clinical, genomic, and imaging data to explore the dynamics of tumor heterogeneity and evolution in response to treatment.

Tumors are continually evolving collections of cells, characterized by a dynamic interplay among heterogeneous sub-clonal populations that expand and contract under innate and imposed selective pressures. My research couples deep learning imaging techniques with high-resolution molecular assays and matched clinical information to analyze tumors through a framework of evolution. We study the impact of treatment on the dynamics of the tumor ecosystem to elucidate resistance mechanisms and identify potential targets for intervention.

Jill Rubinstein on ORDID

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Education and experience

Education

Yale College
B.A., Architecture
1994-1999

Stockholm University
M.S., Computer and Systems Sciences
2002-2004

Yale University
M.S., Computational Biology & Bioinformatics
Ph.D., Computational Biology & Bioinformatics
M.D.
2004-2012

Experience

Yale-New Haven Hospital
General Surgery Resident
2012-2018

Memorial Sloan Kettering Cancer Center
Complex Surgical Oncology Fellow
2018-2020

Hartford Healthcare
Surgical Oncologist
2020-present

University of Connecticut
Assistant Professor of Surgery
2021-present