Minghao Ye

  • Ph.D. in Electrical Engineering

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Minghao Ye NYU ECE

Minghao Ye received his Ph.D. degree in Electrical Engineering from the NYU Tandon School of Engineering in May 2024. His research focuses on designing intelligent traffic engineering solutions for adaptive routing in wide-area networks using machine learning. Since 2018, he has been working with Professor H. Jonathan Chao at the NYU ECE High-Speed Networking Lab. Prior to his Ph.D., Minghao earned an M.S. degree in Electrical Engineering from NYU in 2019 and dual B.Eng. degrees from Sun Yat-sen University and The Hong Kong Polytechnic University in 2017.

Research Interests
Traffic Engineering, Routing, Network Optimization, Software-Defined Networks, Machine Learning for Networking

New York University (NYU)

Doctor of Philosophy, Electrical Engineering, 2024

Master of Science, Electrical Engineering, 2019

The Hong Kong Polytechnic University (PolyU)

Bachelor of Engineering (Honours), Electronic Engineering, 2017

Sun Yat-sen University (SYSU)

Bachelor of Engineering, Microelectronic Science and Engineering, 2017


Journal Papers

1. Yuntian Zhang, Ning Han, Tengteng Zhu, Junjie Zhang, Minghao Ye, Songshi Dou, and Zehua Guo, “Prophet: Traffic Engineering-centric Traffic Matrix Prediction,” IEEE/ACM Transactions on Networking (ToN), 2024.

2. Minghao Ye, Junjie Zhang, Zehua Guo, and H. Jonathan Chao, “FlexDATE: Flexible and Disturbance-Aware Traffic Engineering with Reinforcement Learning in Software-Defined Networks,” IEEE/ACM Transactions on Networking (ToN), 2023.

3. Minghao Ye, Yang Hu, Junjie Zhang, Zehua Guo, and H. Jonathan Chao, “Mitigating Routing Update Overhead for Traffic Engineering by Combining Destination-based Routing with Reinforcement Learning,” IEEE Journal on Selected Areas in Communications (JSAC), 2022.

4. Junjie Zhang, Minghao Ye, Zehua Guo, Chen-Yu Yen, and H. Jonathan Chao, “CFR-RL: Traffic Engineering with Reinforcement Learning in SDN,” IEEE Journal on Selected Areas in Communications (JSAC), 2020.

5. Huazhong Liu, Laurence T. Yang, Jinjun Chen, Minghao Ye, Jihong Ding, and Liwei Kuang, “Multivariate Multi-order Markov Multi-modal Prediction with Its Application in Network Traffic Management,” IEEE Transactions on Network and Service Management (TNSM), 2019.


Conference and Workshop Papers

1. Haowen Zhu, Minghao Ye, and Zehua Guo, “Toward Determined Service for Distributed Machine Learning,” The 32nd IEEE/ACM International Symposium on Quality of Service (IWQoS), 2024.

2. Minghao Ye, Junjie Zhang, Zehua Guo, and H. Jonathan Chao, “Roracle: Enabling Lookahead Routing for Scalable Traffic Engineering with Supervised Learning,“ The 31st IEEE International Conference on Network Protocols (ICNP), 2023.

3. Minghao Ye, Junjie Zhang, Zehua Guo, and H. Jonathan Chao, “LARRI: Learning-based Adaptive Range Routing for Highly Dynamic Traffic in WANs,” IEEE International Conference on Computer Communications (INFOCOM), 2023.

4. Minghao Ye, Yang Hu (co-first author), Junjie Zhang, Zehua Guo, and H. Jonathan Chao, “Reinforcement Learning-based Traffic Engineering for QoS Provisioning and Load Balancing,” The 31st IEEE/ACM International Symposium on Quality of Service (IWQoS), 2023.

5. Ke Chen, Han Wang, Shuwen Fang, Xiaotian Li, Minghao Ye, and H. Jonathan Chao, “RL-AFEC: Adaptive Forward Error Correction for Real-time Video Communication Based on Reinforcement Learning,” The 13th ACM Multimedia Systems Conference (MMSys), 2022.

6. Minghao Ye, Junjie Zhang, Zehua Guo, and H. Jonathan Chao, “Federated Traffic Engineering with Supervised Learning in Multi-region Networks,” The 29th IEEE International Conference on Network Protocols (ICNP), 2021.

7. Minghao Ye, Junjie Zhang, Zehua Guo, and H. Jonathan Chao, “DATE: Disturbance-Aware Traffic Engineering with Reinforcement Learning in Software-Defined Networks,” The 29th IEEE/ACM International Symposium on Quality of Service (IWQoS), 2021.

8. Junjie Zhang, Zehua Guo, Minghao Ye, and H. Jonathan Chao, “SmartEntry: Mitigating Routing Update Overhead with Reinforcement Learning for Traffic Engineering,” ACM SIGCOMM Workshop on Network Meets AI & ML (NetAI), 2020.


Course Instructor

ECE-GY 6363 Data Center and Cloud Computing (Spring 2023)

Teaching Assistant / Course Assistant

ECE-UY 3613 Communication Networks (Spring 2020)

ECE-GY 6363 Data Center and Cloud Computing (Fall 2021 - Fall 2022)

ECE-GY 6383 High-Speed Networks (Spring 2019 - Spring 2021, Fall 2023)


  • The Alexander Hessel Award for the Best Ph.D. Dissertation in Electrical Engineering, 2024
  • The Dante Youla Award for Graduate Research Excellence in Electrical Engineering, 2023
  • IEEE ICNP 2021 Student Registration Award, 2021
  • NYU ECE MS Student Academic Achievement Award, 2018

Research Centers, Labs, and Groups