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.

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. 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) (ORCID) (ResearcherID) (GitHub)

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.

(Google Scholar)

Doyoung Lee

Doyoung Lee (이도영) is a master’s student in the ISE Department at KAIST. He received a BS degree in Industrial Engineering from KyungHee University. His current research interests include the optimization of transportation networks utilizing exact and robust & heuristic methods, as well as reinforcement learning techniques. He joined COMET in 2023.

Junpyo Lee

Junpyo Lee (이준표) is a master’s student in the ISE Department at KAIST. He obtained a bachelor’s degree in industrial engineering at Hanyang University in 2023. His current research interests include optimization and risk management of transportation networks. He joined COMET in 2023.

Yoonju Sim

Yoonju Sim (심윤주) is a master’s student in the ISE Department at KAIST. She received a BS degree in Industrial Engineering from Korea University. Her current research interests include vehicle routing problems, reinforcement learning, and combinatorial optimization. She joined COMET in 2023.

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 master’s student in the ISE Department at KAIST. He received a BS degree in Industrial Engineering from Korea University. His current research interests include mathematical optimization, reinforcement learning, and quantum computing. He joined COMET in 2024.

Jihye Na

Jihye Na (나지혜) 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) 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.

Sasan Mahmoudi

Sasan Mahmoudi is a doctoral student in the IMSE Department at USF. He earned a Bachelor of Science in Industrial Engineering from Sharif University of Technology, Iran in 2011 and a Master of Science in Industrial Engineering from the same institution in 2014. His current research interests include the optimization of transportation networks utilizing exact and heuristic methods, as well as Machine Learning (ML) techniques such as Reinforcement Learning. His primary advisor is Dr. Hadi Gard.

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

  • 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