Minseon Gwak

Biography

Minseon Gwak, PhD, is a Postdoctoral Researcher at ICSI, where she works in Dr. Benjamin Erichson’s group on developing deep learning methods for scientific machine learning. Her research sits at the intersection of machine learning, dynamical systems, and scientific computing, with a focus on building scalable and interpretable AI methods for scientific applications.

Dr. Gwak received her PhD in Electrical Engineering from Pohang University of Science and Technology (POSTECH), where her research focused on sequence modeling and interpretability. Her doctoral work investigated how perspectives from linear dynamical systems could be applied to analyze and optimize state space models for efficient long-sequence modeling while preserving predictive performance.

At ICSI, Dr. Gwak develops novel methodologies in sequence representation learning and generative modeling for scientific machine learning. Her work emphasizes efficiency, stability, and reliability, particularly in applications related to physical simulation and bioinformatics.

Her broader research interests include world models, AI for science, and computational approaches to understanding complex biological systems. Through her research, Dr. Gwak aims to advance scalable and interpretable machine learning methods that can accelerate scientific discovery.

Publications

Areas of Expertise

• Deep Learning and Neural Networks
• Generative AI and Foundation Models
• Planning, Decision-Making, and Intelligent Agents
• Robotics, Autonomous Systems, and Control
• Embedded Systems, IoT Devices, and Cyber-Physical Systems
• Medical Imaging, Diagnostics, and Computational Pathology
• Algorithms, Complexity Theory, and Computability
• Theoretical Foundations of AI and Machine Learning
• Digital Twins for Simulation, Prediction, and Optimization
• Computational Biology, Genomics, and Bioinformatics

ICSI Activity