Benjamin Greenbaum

Benjamin Greenbaum is an Associate Professor at Weill Cornell Medicine's Graduate School of Medical Sciences, holding appointments in the Department of Epidemiology & Biostatistics and serving as Director of Computational Immuno-Oncology within the Computational Oncology Service at Memorial Sloan Kettering Cancer Center. His research bridges statistical physics, information theory, and evolutionary biology to investigate immune-tumor interactions.

Dr. Greenbaum's primary research focuses on self vs non-self discrimination in the immune system, with pioneering work on viral mimicry—where cancer cells produce RNA from genomic repeat elements that activate innate immunity. His lab developed the first quantitative models for viral mimicry and established the concept of neoantigen quality to predict immune responses. Key discoveries include identifying an immune tradeoff in cancer evolution where high-fitness oncogenic mutations generate potent neoantigens while low-fitness mutations evade immune detection.

His computational approaches have directly impacted clinical translation, contributing to a phase II trial of reverse transcriptase inhibitors in colorectal cancer and a phase I mRNA neoantigen vaccine trial for pancreatic cancer. The Greenbaum Lab leads the CompIO initiative to advance computational methods in cancer immunology through collaboration with the Parker Institute for Cancer Immunotherapy.

Dr. Greenbaum's work is supported by federal and philanthropic grants, with publications in high-impact journals including Nature, Cancer Discovery, and Cell. His lab actively trains computational biologists and collaborates across the Tri-Institutional community (Weill Cornell, MSK, Rockefeller).

• Director, Computational Immuno-Oncology Service
• Halvorsen Center for Computational Oncology Faculty
• Principal Investigator, Greenbaum Lab

His lab advises multiple graduate students and postdoctoral researchers through the Tri-Institutional PhD Programs, with active projects spanning pancreatic cancer immunotherapy, repeat element biology, and computational prediction of immune responses. The team maintains strong collaborations with surgical oncology, immunology, and clinical trial units to translate computational findings into therapeutic strategies.