University of Chicago, Dinner Group

 During a summer research appointment at the University of Chicago, I worked as an Artificial Intelligence Research Assistant studying the relationship between protein-ligand binding behavior and simulation confidence metrics.

I conducted over 200 computational simulations using Google DeepMind’s AlphaFold framework to analyze structural predictions and their reliability. I processed and analyzed large datasets using Python, leveraging NumPy and Pandas to identify correlations between molecular interactions and model confidence values.

My work contributed to a better understanding of how AI-generated structural predictions can be evaluated and interpreted in biochemical research contexts. I presented my findings to the research group, summarizing trends and limitations observed in the dataset.