Bohak Yoon
Bohak Yoon is a chemical engineer and AI-for-science researcher whose work applies machine learning and multiscale modeling to energy and materials. He earned chemical engineering degrees at Lehigh in 2016 and the University of Texas at Austin in 2022, then completed a postdoctoral fellowship at the University of Chicago and held a faculty post at Baylor. His research includes two Journal of the American Chemical Society papers on carbon dioxide capture by amino acid ionic liquids and a 2025 paper on quantum chemistry-guided machine learning for solvent design. Since February 2026, he is an assistant professor in KAIST’s Graduate School of Green Growth and Sustainability. Since March 2026, he is also affiliate faculty in its Department of AX in the College of AI, where his work includes scientific machine learning and AI for science.
- Now at
- KAIST
Timeline
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2016
A Lehigh engineering degree
His interests in chemistry, physics, and mathematics grow at The Masters School in Dobbs Ferry, New York. He earns a B.S. in chemical engineering at Lehigh University in 2016.
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2022
A UT Austin doctorate
He earns a Ph.D. in chemical engineering at the University of Texas at Austin in 2022, working with G. S. Hwang. His 2022 work at UT Austin is titled “First-principles studies on degradation of aqueous amines for carbon dioxide capture.”
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July 2022–December 2024
Postdoctoral work in Chicago
He conducts a postdoctoral fellowship in theoretical chemistry at the University of Chicago under Gregory A. Voth from July 2022 to December 2024.
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July 2023
A molecular study of carbon capture
In July 2023, he coauthors a Journal of the American Chemical Society study with Gregory A. Voth on the molecular mechanism of carbon dioxide capture by amino acid ionic liquids.
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January 2024
Amino acid ionic liquid anions
In January 2024, he coauthors a Journal of the American Chemical Society paper with Sijia Chen and Gregory A. Voth on amino acid ionic liquid anions and carbon dioxide capture.
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December 2024–January 2026
Assistant professor at Baylor
He holds an assistant professorship in Baylor University’s Department of Chemistry and Biochemistry, with a joint appointment in Materials Science and Engineering, from December 2024 to January 2026.
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June 2025
Machine learning for solvent design
With Dingkai Hu, Dezhi Cao, Shi-jian Lu, and Qiang Wang, he coauthors a June 2025 paper on quantum chemistry-guided machine learning for the design of CO2-solubilizing deep eutectic solvents.
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Since February 2026
Assistant professor at KAIST
He joins KAIST’s Graduate School of Green Growth and Sustainability as an assistant professor in February 2026 and becomes affiliate faculty in KAIST’s Department of AX in the College of AI in March 2026. His research applies AI/ML and multiscale modeling to energy and sustainability, with areas that include scientific machine learning, AI for science, and AI-driven molecular and materials modeling.
Career
- Since 2026KAISTAssistant Professor
- 2024–2026Baylor UniversityAssistant Professor
- 2022–2024University of ChicagoPostdoctoral Fellow
Education
- 2022University of Texas at AustinPh.D.
- 2016Lehigh UniversityB.S.
Colleagues
Sources and credits
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