Bio

As a postdoctoral scholar at the Aghaeepour Lab, I research machine learning applications in longitudinal medical records to uncover insights that enhance both short-term and lifelong health outcomes, including healthy aging. Previously, I earned an MD from Tehran University of Medical Sciences, where my research focused on the molecular mechanisms underlying neurological and psychiatric conditions such as depression, post-traumatic stress disorder, epilepsy, stroke, and multiple sclerosis, aiming to identify novel pharmacological treatments in animal models. I also collaborated with the Radiology AI Lab at Johns Hopkins University to develop a machine learning–driven diagnostic platform that used resting-state fMRI data to distinguish healthy individuals from those with frontotemporal dementia or Alzheimer’s disease with 91% accuracy.

Beyond research, my passion for equitable education led me to create an online platform for high school students aspiring to compete in the International Biology Olympiad. This initiative has helped cultivate first-time Olympiad medalists from underrepresented regions, broadening access to high-level scientific education in my home country.

Interests

Longitudinal EHR modeling, causal artificial intelligence

Play

I enjoy reading, playing basketball, hiking, and cycling. I’m also a motor racing aficionado, drawn to both its technical precision and strategic depth.