Modeling solutions: Student advance medicine, carbon capture with computational science

The Cornell Graduate School recently spotlighted two of these students.

Deepanjali Chowdhury, a doctoral student in the Hanrath Group, utilizes machine learning to enhance electrochemical carbon reduction processes. Her research focuses on optimizing voltage and current pulses to improve the efficiency of converting carbon dioxide into valuable products like ethanol and methane, contributing to advancements in carbon capture and recycling technologies.

Read more: https://gradschool.cornell.edu/spotlights/student-spotlight-deepanjali-chowdhury

George Padilla, a doctoral student in the Dshemuchadse Group, develops computational models to understand the physics of protein condensates—dense liquid droplets formed by enzymes. His work aims to elucidate how these condensates regulate essential cellular processes and how their unique material properties can inspire the design of bio-inspired materials with applications in medicine and microrobotics.

Read more: https://gradschool.cornell.edu/spotlights/student-spotlight-george-padilla

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