LEOPARD: Linking Experimental Observations with Predictive Algorithms to reveal Response Dynamics for the single cell
- Vibha Anand
- Akira Koseki
- et al.
- 2025
- ISMB 2025
James Kozloski joined IBM Research in May 2001 where he's worked on AI and Biomedicine at the T.J. Watson Research Center in Yorktown Heights, NY. He was named an IBM Principal Research Scientist in 2022 and leads initiatives in Biomedical AI and Modeling, working with external collaborators across multiple fields, all of which are benefiting from improvements to models of cellular function driven by AI, agentic, and algorithmic innovation.
As a manager and strategist, James helps oversee the use of AI to solve problems in stochastic complex systems for improving predictive biophysical models of disease and drug mechanism. His team focuses on applying algorithm-informed foundation models and generative AI to model-based therapeutic design and discovery.
In 2017 he was inducted into IBM's Academy of Technology. Beyond publishing scientific discoveries, James has authored over 300 patents issued for IBM in areas such as neurotechnology, biomedical AI, and computer science. In 2010, he was named an IBM Master Inventor.
He joined IBM after completing a postdoctoral fellowship at Columbia University, and he received his PhD. in Neuroscience and Biomedical Graduate Studies from the University of Pennsylvania in 1999. In 1992, he received a B.A. from the University of Virginia, having double majored in English and Biology as a Jefferson Scholar. Prior to graduate school, he worked in the Laboratory of Human Genetics in New York City, studying the rare genetic disorder Bloom Syndrome, and contributing to the discovery of the gene responsible for it.
A printable version of his Curriculum Vitae is available here.
Exploring the power of BMFM technologies to drive critical tasks in drug discovery