Kim Lab members Sumin Song, Sabari Kumar, and Hojin Jung presented their research at the American Chemical Society Fall 2026 Meeting, held August 23–27 in Chicago, Illinois.

Sumin presented two projects on machine learning approaches for predicting reaction yields in medicinal chemistry. At the COMP Poster Session, Sumin presented “Predicting reaction yields across multiple reactions: a mechanism-aware graph neural network for ultrahigh-throughput medicinal chemistry.” Later, Sumin gave an oral presentation titled “Versatile mechanism-aware yield prediction model of ultrahigh-throughput medicinal chemistry reactions” in the Machine Learning in Chemistry: Property Prediction session.

Sabari presented “Sculpting chemical space enables novel photocatalyst generation” during the Chemical Computing Group (CCG) Poster Session. Sabari was also selected as a recipient of the Chemical Computing Group Excellence Award for Graduate Students, which recognizes outstanding graduate student research presented through the ACS Division of Computers in Chemistry.

Hojin presented “Target-Agnostic Machine Learning Pipeline for Property-Guided Molecular Design” in the Future Pharma Innovators session. Hojin was selected for the 2026 ACS Future Pharma Innovators cohort, a program that recognizes graduate students interested in careers in the pharmaceutical industry and provides opportunities for research presentation, networking, and mentorship from industry scientists.

Congratulations to Sumin, Sabari, and Hojin for representing the Kim Lab at ACS Fall 2026, and special congratulations to Sabari and Hojin on their well-deserved recognition!