Di Wang

Di Wang is a Ph.D. student in the Department of Mechanical and Industrial Engineering at the University of Illinois at Chicago, IL, USA. He received his B.S. and M.S. degrees in electrical engineering from Fuzhou University, China, in 2014 and Tianjin University, China, in 2017. His current research interests include smart manufacturing, multi-agent systems, large language model, and energy management.

Publications

Robust Adversarial Deep Reinforcement Learning
Robust Adversarial Deep Reinforcement Learning
Di Wang. © 2024. 20 pages.
Deep reinforcement learning has shown remarkable results across various tasks. However, recent studies highlight the susceptibility of DRL to targeted adversarial disruptions....
Sustainable Manufacturing Through Digital Twin and Reinforcement Learning
Sustainable Manufacturing Through Digital Twin and Reinforcement Learning
Di Wang. © 2024. 19 pages.
Smart manufacturing is on the cusp of a significant transformation as it integrates virtual systems with their real-world counterparts, primarily through the use of digital...
Reinforcement Learning for Combinatorial Optimization
Reinforcement Learning for Combinatorial Optimization
Di Wang. © 2023. 15 pages.
Combinatorial optimization (CO) problems have many important application domains, including social networks, manufacturing, and transportation. However, as an NP-hard problem...
Explainable Deep Reinforcement Learning for Knowledge Graph Reasoning
Explainable Deep Reinforcement Learning for Knowledge Graph Reasoning
Di Wang. © 2023. 16 pages.
Artificial intelligence faces a considerable challenge in automated reasoning, particularly in inferring missing data from existing observations. Knowledge graph (KG) reasoning...