Jimin PARK

📚 Education

Ph.D. Candidate in Industrial and Systems Engineering, KAIST

• Mar. 2023 - Feb. 2028 (Expected)

• Advisor: Prof. Hyun-Jung Kim

B.S. in Industrial and Systems Engineering, KAIST

• Mar. 2019 - Feb. 2023

• Minor in Science and Technology Policy

• Excellence in Leadership and Volunteering

Sejong Academy of Science and Arts

• Mar. 2016 - Feb. 2019

• Awarded the Jang Yeongsil Award for excellence in research

🖊️ Working Papers

Graph-based Reinforcement Learning with Permutation-Invariant Resource Encoding for Resource-Constrained Unrelated Parallel Machine Scheduling

• with Yong Jae Kim, Minju Jang, Min Geon Kim, Yeo Reum Kim, Soyoung Lee, Jihyun Jo, Iksoo Song, Hyunsoon Park, and Hyun-Jung Kim

• Collaborative work with LG Electronics

A Multi-Agent Framework with Large Language Models for User-driven Rescheduling via In-Context Learning

• with Karen Seojin Kim, Zuhdi Faturrahman, and Hyun-Jung Kim

Fine-Tuning Large Language Models for Algorithm Selection in the Flexible Job Shop Scheduling Problems

• with Zuhdi Faturrahman, and Hyun-Jung Kim

Multi-Objective Batching-Dispatching Framework for Parallel Machine Scheduling with Job Families

• • Under review in Computers and Industrial Engineering (C&IE), Submitted in 2025

  • Karen Seojin Kim †, Minju Jang †, Sang-Wook Lee, Jimin Park, and Hyun-Jung Kim  (†: co-first authors)

Learning Local Search with Theoretical Indicators for Job Shop Scheduling

• • Under review in The Fourteenth International Conference on Learning Representations (ICLR 2026), Submitted in 2025

  • Je-Hun Lee, Jimin Park, and Hyun-Jung Kim

📑 Publications

📄 Journals

1. A Multi-View Attention-Based Encoder-Decoder Framework for Clustered Traveling Salesman Problem [paper]

• • Jimin Park †, Inguk Choi †, and Hyun-Jung Kim (†: co-first authors)

  • IEEE Robotics and Automation Letters (IEEE RA-L), vol.11, no.1, pp.137-144, 2026.

📃 Conference Papers

1. Graph-based Reinforcement Learning for Dynamic Photolithography Scheduling [paper]

• • Sang-Hyun Cho, Sohyun Jeong, Jimin Park, Boyun Choi, Paul Han, and Hyun-Jung Kim

  • Winter Simulation Conference (WSC), Seattle, USA, 2025.

  • Collaborative work with Samsung Display

🎙️ Conference Presentations Only

International

1. Fine-Tuning Large Language Models for Algorithm Selection in the Flexible Job Shop Scheduling Problem

• • Z. Faturrahman, J. Park, S.-H. Cho, and H.-J. Kim

  • Asia-Pacific Industrial Engineering and Management Systems Conference (APIEMS), Hangzhou, China, 2025.

  • Awarded Excellent Paper

2. In-Context Learning for User-specified Constraint Enforcement in Discrete Event Simulation

• • J. Park, K. S. Kim, Z. Faturrahman, and H.-J. Kim

  • IEEE International Conference on Automation Science and Engineering (IEEE CASE), Los Angeles, USA, 2025.

3. Variable Neighborhood Search with Reinforcement Learning for Parallel Machine Batching Scheduling

• • J. Park, S.-W. Lee, S. Jeong, J. Li, S.-I. Mun, and H.-J. Kim

  • IEEE International Conference on Automation Science and Engineering (IEEE CASE), Bari, Italy, 2024.

  • Collaborative work with LG Electronics

4. A Hybrid VNS-RL Approach for Parallel Machine Batch Scheduling in Air Conditioner Manufacturing

• S. Jeong, S.-W. Lee, J. Park, and H.-J. Kim

• 22nd Triennial Congress of the International Ergonomics Association (IEA), Jeju, Korea, 2024.

5. Tree-based Dispatcher for Job Shop Scheduling

• • J.-H. Lee, J. Park, and H.-J. Kim

  • IEEE International Conference on Automation Science and Engineering (IEEE CASE), Bari, Italy, 2024.

Domestic

1. In-Context Learning for User-driven Rescheduling

• • J. Park, K. S. Kim, Z. Faturrahman, and H.-J. Kim

  • The Autumn Conference of Korea Institute of Industrial Engineers (KIIE), Daejeon, South Korea, 2025.

2. Fine-Tuning Large Language Models for Algorithm Selection in the Flexible Job Shop Scheduling Problem

• • Z. Faturrahman, J. Park, and H.-J. Kim

  • The Autumn Conference of Korea Institute of Industrial Engineers (KIIE), Daejeon, South Korea, 2025.

3. A Multi-Objective Scheduling Framework for Batching and Dispatching in Parallel Machine Scheduling with Job Families

• • K. S. Kim †, M. Jang †, S.-W. Lee, J. Park, and H.-J. Kim  (†: co-first authors)

  • The Autumn Conference of Korea Institute of Industrial Engineers (KIIE), Daejeon, South Korea, 2025.

4. Deep Reinforcement Learning-based Encoder-Decoder Framework for The Clustered Traveling Salesman Problem

• • J. Park †, I. Choi †, S.-H. Cho, and H.-J. Kim  (†: co-first authors)

  • The Autumn Conference of Korea Institute of Industrial Engineers (KIIE), Seoul, South Korea, 2024.

5. Dynamic Batching for Multi-Objective Parallel Machine Scheduling

• • K. S. Kim †, M. Jang †, S.-W. Lee, J. Park, and H.-J. Kim  (†: co-first authors)

  • The Spring Conference of Korea Institute of Industrial Engineers (KIIE), Yeosu, South Korea, 2024.

6. Routing Algorithm for Enhancement of Semiconductor Chip Quality

• • S. Joo, J. Ahn, H.-Y. Kim, J. Park, and H.-J. Kim

  • The Autumn Conference of Korea Institute of Industrial Engineers (KIIE), Ulsan, South Korea, 2023.

🛠️ Industrial Projects

1. 강화학습/LLM을 활용한 가공라인 스케줄링 엔진 개발

• (ENG) Scheduling Algorithm for a Production Line with Reinforcement Learning and LLM

• with LG Electronics

• as Project Manager

• May. 2025 — Dec. 2025

2. LLM기반 공급사슬망 운영 최적화 방법론 개발

• (ENG) Optimization of Supply Chain Network Operations with LLM

• with Samsung Electronics

• Apr. 2025 — Mar. 2026

3. 강화학습 기반 OLED FAB Multi-Agent 생산스케줄링 연구

• (ENG) Renforcemet Learning-based OLED FAB Multi-Agent Scheduling

• with Samsung Display

• Mar. 2024 — Feb. 2025

4. 생산계획 최적화를 위한 AI기반 방법론 개발

• (ENG) Production Planning with AI

• with LG Electronics

• Jul. 2023 — Feb. 2024

5. DRAM 제품 설계 품질 향상을 위한 Router 개발

• (ENG) Routing Algorithm for DRAM Circuit Design

• with SK Hynix

• Mar. 2023 — Oct. 2023

🏆 Honors and Awards

1. Excellent Paper Award, APIEMS 2025

• APIEMS 2025, Nov. 2025

• Awarded for the research titled "Fine-Tuning Large Language Models for Algorithm Selection"

2. Gold Prize (2nd place), National Defense Competition for Graduate Students

• Korea National Defense University and KAIST, Nov. 2024

• Awarded for the research titled "UAV Mission Planning for Clustered Targets with Deep Reinforcement Learning"

3. Best Counseling Assistant, KAIST

• KAIST, Dec. 2024

4. CoE Leadership Award, KAIST

• KAIST College of Engineering, Fall 2022

• Honored as one of top 11 undergraduate students with excellent achievements in research and leadership

5. Bronze Prize (5th place), 18th Industrial Engineering Project Competition for Undergraduate Students

• Korea Institute of Industrial Engineers (KIIE), Nov. 2022

• Awarded for the research titled "Operating Room Scheduling with Reinforcement Learning"

6. Gold Prize (2nd place), 17th Industrial Engineering Project Competition for Undergraduate Students

• Korea Institute of Industrial Engineers (KIIE), Nov. 2021

• Awarded for the research titled "Visiting Nurse Scheduling with Reinforcement Learning"

7. Best Prize (1st place), KAIST IE Frontier

• Dept. of Industrial and Systems Engineering, KAIST, Nov. 2021

• Awarded for the research titled "Visiting Nurse Scheduling with Deep Q Learning"

8. National Academic Excellence Scholarship in Science and Engineering

• Spring 2019 — Fall 2022

• Merit-based scholarship awarded by the Korean government

🧑‍🏫 Teaching Experience

Scheduling Theory and Application (IE536)

• Teaching Assistant at KAIST (Instructor: Prof. Hyun-Jung Kim)

• Spring 2025

🚩 Services

Counseling Assistant of the Dept. of Industrial and Systems Engineering

• Provided comprehensive campus life information and peer counseling for KAIST ISysE students

• Head Counseling Assistant since Sep. 2023

• Mar. 2023 — 

Student Council Representative of the Dept. of Industrial and Systems Engineering

• Managed academic/non-academic events for KAIST ISysE undergraduate students

• Finance team lead from Mar. 2021 to Feb. 2022

• Mar. 2020 — Feb. 2022