Zian Jang
Combinatorial Optimization & Reinforcement Learning
I am an Integrated M.S./Ph.D. student in the Department of Artificial Intelligence at Korea University. My research lies at the intersection of combinatorial optimization and reinforcement learning, where I develop learning-based methods to tackle complex, large-scale decision-making problems.
I am particularly interested in neural combinatorial optimization — using deep generative and reinforcement learning models to produce high-quality, feasible solutions to NP-hard problems. I am always open to discussion and collaboration; feel free to reach out by email.
Publications
Selected publications and preprints.
Curriculum Vitae
Last updated: June 2026
Education
Integrated M.S./Ph.D. in Artificial Intelligence
Department of Artificial Intelligence.
B.S. in Information Security and Cryptography
Department of Information Security and Cryptography.
Research Experience
Optimizing Container Ship Stowage Plans via Reinforcement Learning
Development of a method for optimizing container ship stowage plans using reinforcement learning techniques.
AI-based Input Signal Quality Improvement for Fatigue Monitoring
Development of an AI-based input signal quality improvement methodology to improve the accuracy of evaluation of a nuclear power plant fatigue monitoring system.