Strategies for efficiently instructing AI in scientific disciplines
Strategies for efficiently instructing AI in scientific disciplines
About the speaker
Noseong Park
Noseong Park
Associate Professor and Director at the School of Computing, KAIST. His research lies at the intersection of artificial intelligence and scientific computing, with a particular focus on applying AI techniques to partial differential equations (PDEs). His pioneering work in this domain has been published in top-tier AI conferences such as ICLR, NeurIPS, and ICML.Prior to joining KAIST, he was a tenured Associate Professor at Yonsei University (2020–2024), and held faculty positions at George Mason University and the University of North Carolina at Charlotte. He earned his Ph.D. in Computer Science from the University of Maryland, College Park, under the supervision of Professor V. S. Subrahmanian. He also holds a Master’s degree from KAIST and a Bachelor’s degree from Soongsil University.
Associate Professor and Director at the School of Computing, KAIST. His research lies at the intersection of artificial intelligence and scientific computing, with a particular focus on applying AI techniques to partial differential equations (PDEs). His pioneering work in this domain has been published in top-tier AI conferences such as ICLR, NeurIPS, and ICML.Prior to joining KAIST, he was a tenured Associate Professor at Yonsei University (2020–2024), and held faculty positions at George Mason University and the University of North Carolina at Charlotte. He earned his Ph.D. in Computer Science from the University of Maryland, College Park, under the supervision of Professor V. S. Subrahmanian. He also holds a Master’s degree from KAIST and a Bachelor’s degree from Soongsil University.
