I am a final year Ph.D. candidate in Computer Science & Engineering at University of Minnesota, Twin Cities. I am very fortunate to be advised by Prof. Zhi-Li Zhang. Before starting my Ph.D. study, I obtained my Master’s and Bachelor’s degrees in Communication Engineering at University of Electronic Science & Technology of China.

I am interested in machine learning, deep learning, and their applications to computer communication and networks. I aim to design domain-knowledge-guided machine learning to intelligently model and enhance networked systems, such as smart grids, content delivery networks, 5G networks, and video streaming.

I am actively looking for a full-time position. Feel free to let me know if you have any openings.

Publications

Dissecting Carrier Aggregation in 5G Networks:Measurement, QoE Implications and Prediction
Wei Ye, Xinyue Hu, Steven Sleder, Anlan Zhang, Udhaya Kumar Dayalan, Ahmad Hassan, Rostand AK Fezeu, Akshay Jajoo, Myungjin Lee, Eman Ramadan, Feng Qian, Zhi-Li Zhang
Proceedings of the ACM SIGCOMM 2024 Conference

COREL: Constrained Reinforcement Learning for Video Streaming ABR Algorithm Design Over mmWave 5G
Xinyue Hu, Arnob Ghosh, Xin Liu, Zhi-Li Zhang, Ness Shroff
2023 IEEE International Workshop Technical Committee on Communications Quality and Reliability (CQR)

Raven: belady-guided, predictive (deep) learning for in-memory and content caching
Xinyue Hu, Eman Ramadan, Wei Ye, Feng Tian, Zhi-Li Zhang
Proceedings of the 18th International Conference on emerging Networking EXperiments and Technologies(CoNEXT), 2022

5GNN: extrapolating 5G measurements through GNNs
Wei Ye, Xinyue Hu, Tian Liu, Ruoyu Sun, Yanhua Li, Zhi-Li Zhang
Proceedings of the 1st International Workshop on Graph Neural Networking, 2022

Lumos5G: Mapping and predicting commercial mmWave 5G throughput
Arvind Narayanan, Eman Ramadan, Rishabh Mehta, Xinyue Hu, Qingxu Liu, Rostand AK Fezeu, Udhaya Kumar Dayalan, Saurabh Verma, Peiqi Ji, Tao Li, Feng Qian, Zhi-Li Zhang
Proceedings of the ACM internet measurement conference(IMC), 2020

Physics-guided deep neural networks for power flow analysis
Xinyue Hu, Haoji Hu, Saurabh Verma, Zhi-Li Zhang
IEEE Transactions on Power Systems, 2020

Towards a graph signal processing framework for modeling power system dynamics
Xinyue Hu, Zhi-Li Zhang
2019 IEEE Global Conference on Signal and Information Processing (GlobalSIP)

Interactive and stochastic complex geological-surface reconstruction based on sketch
Xinyue Hu, Lu Cai, Qi Wang
SEG Technical Program Expanded Abstracts 2016

Teaching Assistant

• CSCI 1933 Intro to Algorithms & Data Structures, Fall, 2020

Work Experience

• Research Intern in AT&T Research Lab, Summer 2021
• Data Scientist PhD Intern in Cisco Systems Inc., Summer 2019
• System Engineer Intern in Symantec Corp., Spring 2015

Honors and Awards

• Doctoral Dissertation Fellowship from UMN, 2024
• Travel Grant from Grace Hopper Celebration, 2019
• Travel Grant from CRA-W, 2019
• ADC Fellowship from UMN, 2017