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.

The COMET Lab is seeking new students to join the group; see here for details.

Current Members

Introducing the current members of the COMET Lab.

Changhyun Kwon

Dr. Changhyun Kwon (권창현) 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.

(Personal Page) (Google Scholar) (GitHub) (s.t. interview)

Hyeonah Kim

Hyeonah Kim (김현아) is a Ph.D. candidate in the ISE Department at KAIST. She received her MS in Industrial Engineering from Seoul National University and her BS in Industrial Engineering from Hanyang University. She is interested in combinatorial optimization with deep learning. Her primary advisor is Dr. Jinkyoo Park and has been co-advised by Professor Changhyun Kwon since 2023.

(Personal Page) (Google Scholar)

Doyoung Lee

Doyoung Lee (이도영) is a master’s student in the ISE Department at KAIST. He received his BS in Industrial Engineering from KyungHee University. His main research interest is Neural Combinatorial Optimization (NCO), leveraging neural networks to develop novel heuristic methods for vehicle routing problems. He joined COMET in 2023.

Junpyo Lee

Yoonju Sim

Merve Doganbas

Merve Doganbas (Merve Doğanbaş, 메르베 도안바시) 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.

Jae Hyeok Lee

Jae Hyeok Lee (이재혁) 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

Sohyun Jeong

Sohyun Jeong (정소현) 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.

Taekang Hwang

Taekang Hwang (황태강) 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 opitmization, contextual stochastic optimization, and polyhedral combinatorics. He joined COMET in 2024. –>

Junhak Lee

Jaehwan Lee

Jaehwan Lee (이재환) 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 quantum-classical hybrid algorithms, quantum combinatorial optimization, and neural combinatorial optimization. He joined COMET in 2025.

Suyeon Choi

Suyeon Choi (최수연) 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 was previously advised by Professor Seungki Min and has been advised by Professor Changhyun Kwon since 2025. She joined COMET in 2025.

Abhay Sobhanan

Abhay Sobhanan is a PhD Candidate at the IMSE department, USF. He received his BS-MS dual degree in Mathematics from National Institute of Technology Agartala, India in 2019. His research interests include combinatorial optimization and machine learning. His doctoral research focuses on optimizing large-scale vehicle routing problems, incorporating methodological advancements, and addressing concerns like equitable workload allocation. His primary advisor is Dr. Hadi Gard.

Undergraduate Researchers

Past Members

University of South Florida

  • 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 (web) (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