Photo of Patricia Kovatch

Patricia Kovatch, BS Email Patricia Kovatch

    • Positions
    • RESEARCH PROFESSOR | Genetics and Genomic Sciences
    • RESEARCH PROFESSOR | Pharmacological Sciences
    • Language
    • English

Patricia Kovatch is the Senior Associate Dean for Scientific Computing and Data Science at the Icahn School of Medicine at Mount Sinai (ISMMS), founding the division in October 2011. In her work at ISMMS and in her national and international collaborations, she emphasizes a collaborative approach, partnering computational and data experts with basic and translational scientists to tackle complex scientific questions to better diagnose and treat disease. To these ends, she established a scalable and sustainable high-performance computing infrastructure and scientific support staff, and oversees the Mount Sinai Data Warehouse that houses clinical records on over 8 million patients and clinical database groups. She serves as a PI for several NIH equipment grants. She provides vision and strategy for data science and sharing at ISMMS, and nationally as the Core Director for the Data Repository and Management Core for NIEHS's Human Health Exposure Analysis Resource, and as the Data Sharing Lead for Sinai’s Cancer Immune Monitoring and Analysis Core, funded by NCI. She was awarded a training grant for the Community Research Education and Engagement for Data Science. To leverage her experience at the intersection of multiple domains with her passion for researcher productivity, she works to build bridges between researchers and technologists with her NCI, NIH, DOE and NSF colleagues through avenues such as joint workshops at the annual International Conference for High Performance Computing, Networking, Storage, and Analysis. She previously served as the director of an institute for computational science for the National Science Foundation at a Department of Energy national laboratory.

Research Topic

Biomedical Informatics, Computational Biology, Computer Simulation, Education

Multi-Disciplinary Training Area

Genetics and Data Science [GDS]