research
I study how lifelike behaviors such as memory, adaptation, coordination, sensing, and intelligence emerge from physical biological systems.
My work sits at the intersection of computational modeling and biological systems. I’m interested in building computational frameworks that make complex biological behavior more predictable, interpretable, and engineerable.
Ultimately, I want to develop systems that help us understand how life organizes itself and how we might build new forms of programmable biological intelligence.
lines of inquiry
How do physical forces drive coordinated behavior in living systems?
the bahmila lab | biomechanics and biomimetics with spirostomum
Studied ultrafast contraction in Spirostomum ambiguum, examining hydrodynamic signaling, mechanosensation, and collective synchronization in single-celled organisms.
How can memory and learning exist without a nervous system?
NSF center for cellular construction | intelligence in stentor
Investigated learning and habituation in Stentor coeruleus through behavioral experiments, RNA transfer studies, and microscopy.
How can computation make biology more programmable and discoverable?
scheminger | computational research fellow
Built computational workflows for molecular docking, protein analysis, and biological simulation.
update log
05.26 CRIS Bio-It Hackathon first place
04.26 accepted to present at SCIPY 2026
03.26 accepted to neurotam fellowship
03.26 project proposal accepted to bio-it world
