Jing Su
Education
Ph.D. in Computer Science, °ÄÃÅÁùºÏ²ÊÔ¤²â,2024
M.S. in Computer Science, °ÄÃÅÁùºÏ²ÊÔ¤²â, 2019
Research Interests
Reinforcement Learning, Network Function Virtualization, Fault-Tolerant Computing
Publications
J. Su, S. Nair and L. Popokh, "EdgeGym: A Reinforcement Learning
Environment for Constraint-Aware NFV Resource Allocation," 2023
IEEE 2nd International Conference on AI in Cybersecurity (ICAIC)
J. Su, S. Nair and L. Popokh, "Optimal Resource Allocation in SDN/
NFV-Enabled Networks via Deep Reinforcement Learning," 2022
IEEE Ninth International Conference on Communications and
Networking (ComNet)
About
Jing is in the process of completing his Ph.D. dissertation. He is deeply passionate about reinforcement learning, fault-tolerant computing, and optimization research. Central to his research is the integration of reinforcement learning with constraint programming, aiming to address complex optimization challenges.