The Computational Optimization Methods (COMET) Lab is a research group led by Dr. Changhyun Kwon in the Department of Industrial and Systems Engineering at KAIST.

Core Cultural Values of COMET

  • Diversity Fuels Innovation: We embrace diverse perspectives, fostering an inclusive environment where creativity thrives.
  • Curiosity Knows No Bounds: We celebrate curiosity as the driving force behind discovery and progress.
  • Nerdiness is Our Superpower: A passion for learning and a love for intellectual exploration define who we are.
  • We Rise by Lifting Others: Sharing knowledge, mentoring, and fostering a strong community are central to our mission and joy.

Current Members

Changhyun Kwon

Changhyun Kwon (권창현)

Principal Investigator
Website Google Scholar GitHub LinkedIn YouTube

Changhyun Kwon is leading the COMET Lab. His research interests include computational methods for solving strategic and operational problems arising in urban logistics, mobility, and services. His current focus is to integrate methods from machine learning and operations research for improving computational efficiencies. He received his PhD and MS in Industrial Engineering from the Pennsylvania State University, and BS in Mechanical Engineering from KAIST.

Yoonju Sim

Yoonju Sim (심윤주)

Ph.D. Student ISE
Website Google Scholar GitHub LinkedIn

Yoonju Sim is a Ph.D. student in the ISE Department at KAIST. She received a BS degree in Industrial Engineering from Korea University. Her current research interests include large-scale optimization, vehicle routing problems, and LLMs. She joined COMET in 2023.

Merve Doganbas

Merve Doganbas (Merve Doğanbaş, 메르베 도안바시)

Ph.D. Student ISE
LinkedIn

Merve Doganbas is a Ph.D. candidate in the ISE Department at KAIST. She received her MS in ISE from KAIST and her BS in Industrial Engineering from Bilkent University in Turkey. She is interested in combinatorial optimization, reinforcement learning, and deep learning. Her primary advisor is Professor Hayong Shin and has been co-advised by Professor Changhyun Kwon since 2023.

Co-advised by Professor Hayong Shin

Jae Hyeok Lee

Jae Hyeok Lee (이재혁)

Ph.D. Student ISE
LinkedIn

Jae Hyeok Lee is a Ph.D. student in the ISE Department at KAIST. He received a BS degree in Industrial Engineering from Korea University. His current research interests include neural combinatorial optimization, GPU computing and quantum computing. He joined COMET in 2024.

Jihye Na

Jihye Na (나지혜)

Master's Student ISE
LinkedIn

Jihye Na is a master's student in the ISE Department at KAIST. She received a BS degree in Industrial Engineering from Hanyang University. Her current research interests include mathematical optimization, machine learning, and Monte Carlo methods. She joined COMET in 2024.

Sohyun Jeong

Sohyun Jeong (정소현)

Ph.D. Student GSDS
LinkedIn

Sohyun Jeong is a Ph.D. candidate in the GSDS at KAIST. She received her MS in CBE from KAIST and her BS in Chemical Engineering from Rutgers University. She is interested in combinatorial optimization, scheduling, and reinforcement learning. Her primary advisor is Professor Hyun-Jung Kim and has been co-advised by Professor Changhyun Kwon since 2024.

Co-advised by Professor Hyun-Jung Kim

Taekang Hwang

Taekang Hwang (황태강)

Ph.D. Student ISE
LinkedIn

Taekang Hwang is a Ph.D. student in the ISE Department at KAIST. He received a BS degree in Industrial Management Engineering from Hankuk University of Foreign Studies. His current research interests include mathematical optimization, integer programming and polyhedral combinatorics. He joined COMET in 2024.

Junhak Lee

Junhak Lee (이준학)

Master's Student GSDS
LinkedIn

Junhak Lee is a master's student in the GSDS at KAIST. He received a BS degree in Industrial & Systems Engineering from KAIST. His current interests include combinatorial optimization and graph neural network. He joined COMET in 2025.

Jaehwan Lee

Jaehwan Lee (이재환)

Ph.D. Student GSDS
LinkedIn

Jaehwan Lee is a Ph.D. student in the GSDS at KAIST. He received a BA degree in Applied Statistics from Yonsei University. His current research interests include OR-based Quantum Computing Enhancement and Quantum Computing-based Optimization Acceleration. He joined COMET in 2025.

Suyeon Choi

Suyeon Choi (최수연)

Ph.D. Student ISE
LinkedIn

Suyeon Choi is a PhD student in the ISE Department at KAIST. She received her M.S. in ISE from KAIST and a B.S. in Industrial Engineering from Yonsei University. Her research interests include mathematical optimization, machine learning and market design. She joined COMET in 2025.

Thi Thao Vy Bui

Thi Thao Vy Bui (Bùi Thị Thảo Vy, 배초위)

Master's Student ISE
LinkedIn

Thi Thao Vy Bui is a master's student in the ISE department at KAIST. She received a BEng degree in Logistics and Supply Chain Management from HCMC University of Technology (HCMUT). Her research interests include optimization, vehicle routing problems, and humanitarian logistics. She joined COMET in 2025.

Undergraduate Researchers

Past Members

KAIST

University of South Florida

  • Abhay Sobhanan, Ph.D., 2025, Pathways to Efficient and Equitable Solutions for Large-Scale Routing Problems (web) (co-advisor Dr. Hadi Charkhgard)

  • Sasan Mahmoudinazlou, Ph.D., 2024, Routing Problems Through the Lens of Hybrid Algorithms (co-advisor Dr. Hadi Charkhgard)

  • Xufei Liu, Ph.D., 2022, Computational Methods for Solving the Combinatorial Optimization Problems in Transportation

  • Aigerim Bogyrbayeva, Ph.D., 2021, Optimization and Machine Learning Methods for Solving Combinatorial Problems in Urban Transportation (web)

  • Zulqarnain Haider, Ph.D., 2020, Using Optimization Methods for Solving Problems in Sustainable Urban Mobility and Conservation Planning (web) (co-advisor Dr. Hadi Charkhgard)

  • Mahdi Takalloo, Ph.D., 2020, Game Theory Approaches for Transportation Problems

  • Kevin Melendez, Ph.D., 2020, On the Convergence of Transportation and Power Systems in Smart and Connected Communities (co-advisor Dr. Tapas Das)

  • Liu Su, Ph.D., 2019, Routing and Designing Networks for Two Transportation Problems

  • Aritra Pal, Ph.D., 2017, Improving Service Level of Free-Floating Bike Sharing Systems

University at Buffalo

  • Anpeng Zhang, Ph.D., 2018, Understanding and Modeling New Transportation Markets with Emerging Vehicle Technologies (co-advisor Dr. Jee Eun Kang)

  • Nan Ding, Ph.D., 2017, Enabling Urban Parcel Pick-up and Delivery using All-Electric Trucks (co-advisor Dr. Rajan Batta)

  • Longsheng Sun, Ph.D., 2016, Designing Regulation Policies for Hazardous Materials Transportation (co-advisor Dr. Mark Karwan)

  • Masoumeh Taslimi, Ph.D., 2015, On the Analysis of Two Problems related to Risk Management in Urban Transportation Networks (co-advisor Dr. Rajan Batta)

  • Tolou Esfandeh, Ph.D., 2015, Regulating Hazardous Materials Transportation by Dual-Toll Pricing and Time-Dependent Network Design Policies (co-advisor Dr. Rajan Batta)

  • Iakovos Toumazis, Ph.D., 2015, Dynamic Chemotherapy Scheduling for Metastatic Colorectal Cancer Patients: Assessments and Improvements (web)

  • Md. Tanveer Ahmed, Ph.D., 2013, Revenue Management for Online Advertisement Services

  • Paul Berglund, Ph.D., 2012, Three Problems in Discrete Network Facility Location

  • Yingying Kang, Ph.D., 2011, Value-at-Risk Models for Hazardous Materials Transportation (co-advisor Dr. Rajan Batta)

  • Ali Sattarzadeh, M.S., 2015, Hazmat Network Design Considering Risk and Cost Equity

  • Zulqarnain Haider, M.S., 2014, Inventory Rebalancing through Pricing in Public Bike Sharing Systems

  • Chelsea Greene, M.S., 2013, OR/MS Approaches to Problems involving Hazardous Materials Risk and Impacts from a Natural Disaster (co-advisor Dr. Rajan Batta)

  • Anand Srinivasan, M.S., 2010, Operations of Online Advertising Services and Publisher’s Options

  • Amod Anand Agashe, M.S., 2010, Stochastic Revenue Optimization in Online Advertising

  • Varun Narayana Kutty, M.S., 2010, Accept-Reject Decision in Online Advertising using Geometric Brownian Motion