Machine Learning Approach for Resource Allocation in Mobile Edge Computing – Hang Hu

by Emma Delahanty

Originally from Macheng, China, Hang Hu came to City College to pursue his Ph.D. in Electrical Engineering.

“Motivated by a strong interest in the intersection of machine learning and intelligent network systems,” Hu said. “ I had the opportunity to engage in research at the forefront of these fields.”

Hu worked under the mentorship of  Professor Myung J. Lee, of the Department of Electrical Engineering at the Grove School of Engineering and doctoral faculty member of computer science at the Graduate Center. Guided by Lee, Hu was able to complete his dissertation, Machine Learning Approach for Resource Allocation in Mobile Edge Computing. His focus was on applying machine and AI learning to improve resource allocation in Mobile Edge Computing (MEC) systems, which is a network that brings cloud computing capabilities to an IT service environment. Hu found that, “Enhanced clustering stability and coverage in vehicular networks through GNN-based methods achieved 45.45% higher reliability and 43.54% greater energy efficiency than baseline methods in wireless scheduling.” During his time at CCNY, Hu also taught classes at the college.  

“I also gained valuable teaching experience in communication systems. The community at CCNY has shaped both my technical and professional growth.” 

Currently, Hu is a postdoctoral researcher at CCNY and Kyushu Institute of Technology in Japan. He is continuing his work on AI-enabled network systems and cross-continental testbed integration. For future plans, Hu hopes to pursue industry research and development, with a focus on edge/cloud computing, intelligent wireless networks, and applied AI technologies for next-generation communication systems.

You may also like

Skip to content