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.