I am an assistant professor in School of Computing and Augmented Intelligence at Arizona State University. I am generally interested in deep learning, representation learning, and dynamical systems.
Open positions: I am looking for self-motivated Ph.D. research assistants. Email me with your CV and a brief introduction of your research interests to kookjin.lee@asu.edu.
Research Highlights
Structure-preserving dynamics modeling
A Gruber, K Lee, N Trask, Structure preserving reversible and irreversible bracket dynamics for deep graph neural networks, NeurIPS 2023 (to appear) [Preprint]
K Lee, N Trask, P Stinis, Structure-preserving sparse identification of nonlinear dynamics for data-driven modeling, MSML 2022 [Paper][Code]
K Lee, N Trask, P Stinis, Machine learning structure preserving brackets for forecasting irreversible processes, NeurIPS 2021 Spotlight [Paper]
Implicit Neural Representations (INRs)
INRs for PDE solutions or Physics-informed Neural Networks (PINNs)
W Cho, K Lee, D Rim, and N Park, Hypernetwork-based Meta-Learning for Low-Rank Physics-Informed Neural Networks, NeurIPS 2023 Spotlight (to appear) [Preprint] [Code]
J Kim, K Lee, D Lee, SY Jhin, and N Park, DPM: A novel training method for physics-informed neural networks in extrapolation, AAAI, 2021 [Paper]
INR-based reduced-order modeling
- T Wen, K Lee, and Y Choi, Reduced-order modeling for parameterized PDEs via implicit neural representations, NeurIPS 2023 Workshop on Machine Learning and the Physical Sciences
News
Nov 2024: One paper accepted by Journal of Geophysical Research: Machine Learning and Computation
Oct 2024: Two papers accepted at NeurIPS workshops (Machine Learning and the Physical Sciences and Foundation Models for Science)
Sep 2024: One paper accepted by Materials Today [Paper]
Sep 2024: One paper accepted at NeurIPS 2024
Sep 2024: Gave a talk at DoMSS seminar in the School of Math and Stats (SoMSS) at ASU
Jul 2024: Gave a talk at MINDS seminar in Dept of Math at Postech
Jul 2024: One paper accepted at CIKM 2024 (The first author, Fan Wu, received SIGWEB and NSF Travel Grant!)
May 2024: One paper accepted at ICML 2024 (selected for an Oral presentation)
Apr 2024: Received NSF CAREER award [Award description] [ASU article]
Mar 2024: One paper (Unsupervised Physics-informed Multimodal Learning) accepted by Foundations of Data Science (FoDS)
Mar 2024: One paper accepted at ICLR Workshop (Workshop on AI4DifferentialEquations in Science)
Feb 2024: Selected as one of the first teams for the inaugural ASU AI Innovation Challenge (in collaboration with OpenAI)
Jan 2024: One paper accepted at TheWebConf 2024
Jan 2024: Two papers accepted at ICLR 2024.
Dec 2023: One paper accepted at AAAI 2024.
Dec 2023: Presented two papers (one splotlight) and two workshop papers at NeurIPS 2023.