Education

• Stanford University

  Ph.D. in Mechanical Engineering

  2023 - Present

  Advisor: Prof. Wei Cai

• Korea Advanced Institute of Science and Technology (KAIST)

  B.S. in Mechanical Engineering

  B.S. in Electrical Engineering

  2019 - 2023

Awards and Honors

• James D. Plummer Graduate Fellowship

  Stanford University (2023 - 2024)

• National Science & Technology Scholarship

  Korea Ministry of Science and ICT (2019 - 2023)

• Global Leadership Award

  KAIST (2023)

• President's Undergraduate Research Award

  Georgia Institute of Technology (2022)

• KSME | SEMES Open Innovation Challenge

  The Korean Society of Mechanical Engineers (KSME) | SEMES (2022)

• Young Engineers Honors Society

  National Academy of Engineering of Korea (2020)

• Guwon Academic Excellence Scholarship

  Guwon Scholarship Foundation (2020)

• KAIST Academic Excellence Scholarship

  KAIST (2020)

Service and Teaching Activities

• Summer Undergraduate Research Fellow Mentor

  Machine Learning Interatomic Potentials for Large Scale Molecular Dynamics (Summer 2025)

• Teaching Assistant

  ME 123: Computational Engineering (Spring 2026)

  ME 346A: Introduction to Statistical Mechanics (Winter 2025)

• Undergraduates Mentored

  Saul Eduardo Perez Herrera (Summer 2025) → National Autonomous University of Mexico

  Eitan Cohen Arazi (Winter 2024) → University of Buenos Aires

Publications

• Accelerated Langevin Dynamics Simulation via Neural Network–Driven Importance Sampling

  Michael Kim, Wei Cai

  ChemRxiv Preprint (2026) Link PDF

• Accelerated Markov Chain Monte Carlo Simulation via Neural Network–Driven Importance Sampling

  Michael Kim, Wei Cai

  ArXiv Preprint (2026) Link PDF

• Smart Filtering Facepiece Respirator with Self-Adaptive Fit and Wireless Humidity Monitoring

  Kangkyu Kwon, Yoon Jae Lee, Yeongju Jung, Ira Soltis, Yewon Na, Lissette Romero, Myung Chul Kim, Nathan Rodeheaver, Hodam Kim, Chaewon Lee, Seung-Hwan Ko, Jinwoo Lee, Woon-Hong Yeo

  Biomaterials (2025) Link

• Stretchable Wearable Wireless Bioelectronics Using All Printed Pressure Sensors and Strain Gauges

  Nathan Zavanelli, Yoon Jae Lee, Myung Chul Kim, Allison Bateman, Matthew Guess, Hyeonseok Kim, Dinesh K Patel, Woon–Hong Yeo

  Advanced Materials Technologies (2024) Link Journal Cover

• Advances in Electrochemical Sensors for Detecting Analytes in Biofluids

  Jimin Lee, Myung Chul Kim, Ira Soltis, Sung Hoon Lee, Woon-Hong Yeo

  Advanced Sensor Research (2023) Link Journal Cover

Conferences

Includes upcoming events

• Accelerated Langevin Dynamics Simulation via Neural Network-Driven Importance Sampling

  ChemAI NYC 2026, Simons Center for Computational Physical Chemistry, New York University

  New York, NY (June 2026)

• Accelerating Langevin Dynamics Simulation of Rare Events

  ICME Research Symposium 2026, Stanford Institute for Computational & Mathematical Engineering

  Stanford, CA (May 2026)

• Accelerating Rare Event Simulations

  AI+Science: Accelerating Discovery, Stanford HAI

  Stanford University (May 2026)

• Neural Network Driven Importance Sampling for Accelerated Kinetic Monte Carlo of Rare Events

  MRS Spring Meeting, Materials Research Society

  Honolulu, HI (Apr. 2026)

• Accelerating Monte Carlo Simulation of Rare Events by Importance Sampling using Neural Network

  DAMOP 2025, The 56th Annual Meeting of the APS Division of Atomic, Molecular and Optical Physics

  Portland, OR (June 2025) Link

• Smart Filtering Facepiece Respirator with Adaptive Fit and Wireless Humidity Monitoring

  BMES 2022 Annual Meeting, Biomedical Engineering Society

  San Antonio, TX (Oct. 2022)

• Stretchable Pressure Sensor using Inter-Digitated Serpentine Structure

  Gordon Research Conference, Multifunctional Materials and Structures

  Ventura, CA (Sept. 2022) Link

Patents

• A method and apparatus for classification of subtypes of cells with morphological and motility features using hybrid learning

  Hyunjong Shin, Chanhong Min, Minwoo Kang, Hyuntae Jeong, Taeyoon Kwon, Myung Chul Kim

  KR Patent 10-2762542 (2025) Link

Research

Theory

Importance sampling that turns biased simulations into estimates of the original transition rates.

Accelerated Langevin Dynamics

A neural-network importance function tilts each Langevin step toward rare transitions, and path weights absorb its errors, so the success-probability estimate stays unbiased for any positive importance function while a branching random walk keeps the weights bounded.

Accelerated MCMC

A neural network learns a bias potential in log space that steers lattice Monte Carlo through rare transitions, while path reweighting and a branching random walk keep the success-probability estimate unbiased; auxiliary failure and success states keep the formulation robust to grid refinement.

Applications

The methods at work on atomistic and biomolecular rare events.

Accelerated Atomistic Simulations

Neural-network importance sampling of Langevin dynamics reproduces reference rates and resolves competing channels, including an unanticipated long jump, for the LJ7 cluster and, in a revised manuscript in preparation, a Pt adatom on Pt(001) and a vacancy in bcc iron.

Agent-Guided Variance Reduction for Protein Kinetics

An agentic search driven by Claude Code selects the weight-control scheme that tames path-weight degeneracy, recovering the alanine dipeptide isomerization rate to within 3–6% of brute-force MD.

Notes

• Reinforcement Learning [Poster]

  Stanford, Winter 2026

• Mathematical Finance [PDF]

  Stanford, Winter 2026

• Computational Methods of Applied Mathematics [PDF]

  Stanford, Winter 2026

• Advanced Physical Chemistry [PDF]

  Stanford, Winter 2025

• Finite Element Analysis [PDF]

  Stanford, Winter 2025

• Introduction to Statistical Mechanics

  Problem Session Notes [PDF]

  Stanford, Winter 2025

• Introduction to Non-Equilibrium Statistical Mechanics [PDF]

  Thermal Activation of Dislocation Glide [PDF]

  Stanford, Fall 2024

• Numerical Linear Algebra [PDF]

  Stanford, Fall 2024

• Defects and Disorder in Materials [PDF]

  Stanford, Spring 2024

• Elasticity and Inelasticity [PDF]

  Stanford, Spring 2024

• Stochastic Differential Equations [PDF]

  Stanford, Winter 2024

• Partial Differential Equations [PDF]

  Stanford, Winter 2024

• Linear Algebra [PDF]

  Stanford, Fall 2023

• Applied Quantum Mechanics [PDF]

  Stanford, Fall 2023

• Waves in Solids and Fluids [PDF]

  KAIST, Fall 2021

• Mechanism Design [PDF]

  KAIST, Fall 2021

Adventures

SURF 2025

Summer Undergraduate Research Fellowship Program

Compfest 2025

Computational Mechanics Festival

Graduation 2023

Graduation Ceremony

Boston 2022

Traveling Boston

GRC 2022

Gordon Research Conference

BMES 2022

Biomedical Engineering Society Annual Meeting