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Michael Kim
PhD Candidate @ Stanford ME
Monte Carlo & Molecular Dynamics

I am a third year Ph.D. candidate in Micronano Mechanics Group at Stanford University. I am privileged to be advised by Prof. Wei Cai.

My primary research interest lies in rare events, particularly in developing theories and algorithms to (1) accelerate rare events and (2) estimate their dynamic properties.

I am also interested in prediction of mechanical behaviors of massive polymer networks through molecular dynamics (MD) simulations and statistical analysis.

Recently, I have been working on accelerated kinetic monte carlo simulation in discretized phase space; utilizing branching random walk algorithm and neural network bias potentials.

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 and 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)

  • 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 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 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

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

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

    Portland, OR (2025) Link

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

    Gordon Research Conference, Multifunctional Materials and Structures

    Ventura, CA (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

Accelerated Langevin Dynamics Simulation

Accelerated Langevin Dynamics Simulation

Brief description of research on rare events.

Accelerated MCMC

Accelerated Markov Chain Monte Carlo Simulation

Brief description of research on rare events.

Notes

  • 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