- M.D., Shiraz University of Medical Sciences
- M.S., Epidemiology & Clinical Research, University of Maryland School of Medicine
Education & Training
Research Summary
Interpretable machine learning is central to turning rich but largely descriptive spatial and multi-omic data into mechanistic insight. We will develop computational methods that model how molecular regulation shapes cell state within its tissue context, with an emphasis on approaches that generalize across biological contexts and produce hypotheses that can be validated experimentally.
Career Goals
Physician-scientist building a computationally driven translational cancer research program in which clinical questions grounds method development across the dry and wet lab.