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Leonid TSAP

Leonid Tsap
Title: Health Scientist Administrator
Office(s): Division of Aging Biology (DAB)
Email Address: leonid.tsap@nih.gov

Biography

Leonid Tsap, Ph.D., joined the Cell Biology Branch in the Division of Aging Biology in 2021 as a program officer managing a research portfolio focused on emerging technologies for aging, including computational and informatic tools, artificial intelligence and machine learning, imaging modalities and visualization tools, systems and synthetic biology. Dr. Tsap is also a DAB point of contact for small business grants. See full description of DAB-supported small business grants here.

Before coming to NIA, Dr. Tsap has contributed to NIH as a Scientific Review Officer at CSR and NLM, and has been recognized with several awards. His areas comprise many emerging technologies, including medical imaging (all modalities), biocomputing, artificial intelligence and machine learning, modeling, biomarkers, robotics, software, analysis and interfaces.

He received a Ph.D. in computer science and engineering with specialization in medical image analysis from the University of South Florida and was awarded the Graduate Council's Outstanding Dissertation Prize. Dr. Tsap had postdoctoral training at the University of California Lawrence Livermore National Laboratory. He was a member of the Editorial Board of the Pattern Recognition journal, and conference program committees. Dr. Tsap’s research resulted in more than 30 refereed publications, a book chapter and a patent.

Research Interests/Portfolio

Emerging Technologies Program

  • Applications of artificial intelligence, machine learning, or health monitoring technologies to the study of aging, including “digital twins” in aging research
  • Bioinformatic, statistical, and computational approaches in aging biology research
  • Technology development for imaging modalities and visualization tools as applied to aging
  • Novel sensors and biomarkers for monitoring age-related changes and diseases
  • Less invasive and more ubiquitous ways of collecting biological and diagnostic data
  • Systems biology of aging
  • Other emerging technologies that may benefit aging research and reflect new directions, such as new imaging technologies or novel biophysical approaches
  • Tissues-, organs- and organ systems-on-a-chip technologies

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