The Center for Computational Immunology is a hub for collaboration among researchers studying cancer, genomics, machine learning, and immunology, with the goal of developing optimal targeted immunotherapies for patients and increasing the number of patients who benefit from immunotherapy drugs that kill cancer. The center utilizes Mount Sinai’s broad expertise in immunology, cancer, and computational sciences to advance immunological studies in cancer and model the interactions between cancers and the immune system in order to help more people benefit from the life-saving potential of immunotherapy.
The center is a joint endeavor of The Tisch Cancer Institute, Ramon Parsons, MD, PhD, Director, and the Precision Immunology Institute at the Icahn School of Medicine at Mount Sinai, Miriam Merad, MD, PhD, Director.
Benjamin Greenbaum, PhD, Assistant Professor of Oncological Sciences, Pathology, and Medicine (Hematology and Medical Oncology) is the director of the center. His research focuses on novel quantitative approaches to studying the rapidly evolving genomes of tumors and viruses and how they interact with the immune system. He studies how the interaction between tumors and the immune system shapes tumor evolution and response to immunotherapy.
Dr. Luksza, recruited from the Simons Center for Systems Biology at the Institute for Advanced Study, is Assistant Professor of Oncological Sciences, and Genetics and Genomic Sciences. She studies how immune interactions drive the evolution of cancers and viruses, with a focus on analyzing large genetic datasets to assess how cancers develop resistance to immunotherapies and how influenza viruses mutate to escape immune surveillance.
Dr. Polak, recruited from the Broad Institute of MIT and Harvard, is Assistant Professor of Oncological Sciences, Genetics and Genomic Sciences, Pathology, and Medicine (Hematology and Medical Oncology). He studies complex features of the tumor environment that improve discovery of cancer genes and reveal the architecture of mutational processes to inform identification of patients who may benefit from specific treatments. He also studies cancer driver events and cancer etiology across understudied populations.