Minghao Ye @ NYU

Research

My research interests and expertise are concentrated in the following areas:

  • Traffic engineering (TE) and routing.
  • Network optimization methods.
  • Software-defined networking (SDN).
  • Machine learning (ML) for networking.
  • Networking for distributed ML.
  • Data center and cloud computing.

Research Summary

I have been focusing on designing intelligent traffic engineering (TE) solutions to optimize routing strategies for software-defined wide-area networks using artificial intelligence and machine learning techniques, aiming to:

  1. Improve network load balancing performance under dynamic traffic scenarios.
  2. Achieve good QoS provisioning with intelligent routing decisions.
  3. Reduce network disturbance and routing update overhead caused by TE operations.
  4. Accelerate TE operations in large-scale networks to achieve good scalability.
  5. Deploy robust routing strategies that are resilient to unexpected link failures.

Research Projects

During my Ph.D. studies at NYU, I have published 13 papers (7 first-authored papers) with 200+ citations in top-tier networking journals and conferences, including IEEE JSAC, IEEE/ACM ToN, IEEE INFOCOM, IEEE ICNP, and IEEE/ACM IWQoS. I am also the recipient of The Alexander Hessel Award for the Best Ph.D. Dissertation in Electrical Engineering in 2024 and The Dante Youla Award for Graduate Research Excellence in Electrical Engineering in 2023 at NYU.

My Curriculum Vitae   Google Scholar   DBLP   ORCiD   ResearchGate

My Laboratory

I am currently working with Prof. H. Jonathan Chao and a group of talented MS students at the NYU High-Speed Networking Lab (HSNL).

NYU High-Speed Networking Lab (HSNL)

Most of my research projects in machine learning + traffic engineering are completed in collaboration with Prof. Chao and two HSNL alumni: Dr. Junjie Zhang (Fortinet) and Prof. Zehua Guo (BIT).

Current MS students:

  • Huaqiu Liu (2024-)
  • Seeger Zou (2024-)
  • Yao Shen (2024-)
  • Runyu Wang (2024-)
  • Xiaocheng Zou (2024-)
  • Yuejia Tong (2024-)
  • Yilun Liang (2023-)
  • Xing Fang (2023-)
  • Po-Yen Chen (2023-)

HSNL alumni (MS students) from my research group:

  • Xingda Bao (2023) –> Software Engineer @ Stellar Services
  • Boyu Han (2022-2023) –> AI Development Engineer @ Lenovo
  • Zihan Lin (2022-2023) –> Quality Development Engineer @ InterSystems
  • Xiao Xie (2022-2023) –> Software Development Engineer @ Fortinet
  • Senlin Xiao (2022-2023) –> Embedded Software Engineer @ Fortinet
  • Tyler Lin (2022-2023) –> Back to work in China
  • Yang Hu (2021-2022) –> Software Development Engineer @ Fortinet, two papers published (IWQoS ’23: QoS-RL, JSAC 22: FlexEntry)
  • Ke Chen (2020-2021) –> Senior Software Development Engineer @ Fortinet, one paper published (MMSys ’22: RL-AFEC)
  • Han Wang (2020-2021) –> Back to work in China, one paper published (MMSys ’22: RL-AFEC)
  • Shuwen Fang (2020-2021) –> Back to work in China, one paper published (MMSys ’22: RL-AFEC)
  • Yang Li (2019) –> Software Engineer @ Google
  • Daihui Dou (2019) –> Back to work in China

Graduate Research Project Mentorship

I have been mentoring more than 20 graduate ECE students in 9 different advanced research projects at NYU since 2019.

Current Research Projects:

  1. Leveraging Multipath Transport for Improving Application Performance in Dynamic Networks
    • Research group: Yilun Liang, Yuejia Tong (co-advise with Chen-Yu Yen)
    • Past members: Boyu Han, Yao Shen, Ke Zhou
  2. Multi-constrained Distributed QoS Routing
    • Research group: Po Yen Chen, Zihan Lin
  3. Design and Implementation of SD-WAN Traffic Engineering
    • Research group: Xing Fang, Boyu Han, Xingda Bao, Xiao Xie, Senlin Xiao, Xiaocheng Zou, Yao Shen, Runyu Wang
    • Past members: Tyler Lin, Ke Zhou, Yilun Liang
  4. Networking for Distributed Machine Learning
    • Research group: Huaqiu Liu, Seeger Zou, Po Yen Chen

Past Research Projects:

  1. QoS-Aware Traffic Engineering with Reinforcement Learning
    • Research group: Yang Hu (2022)
    • One paper published (IWQoS ’23: QoS-RL)
  2. Destination-based Routing Update Overhead Mitigation with Reinforcement Learning
    • Research group: Yang Hu (2021 – 2022)
    • One paper published (JSAC 22: FlexEntry)
  3. Adaptive Forward Error Correction for Real-time Communications Based on Reinforcement Learning
    • Research group: Ke Chen, Han Wang, Shuwen Fang (2020 – 2021)
    • One paper published (MMSys ’22: RL-AFEC)
  4. Traffic Matrix Prediction with Deep Learning Models
    • Research group: Han Wang, Yang Li (2019 – 2020)
    • Developed an attention-based model with LSTM to predict traffic matrices
  5. Investigation of 5G and Multi-access Edge Computing Technologies
    • Research group: Daihui Dou (2019)
    • Conducted a thorough literature study on 5G and MEC