Zhuangdi Zhu

Zhuangdi Zhu

Senior Data & Applied Scientist



I am Zhu, Zhuangdi (朱 ). I am currently a senior Data & Applied Scientist at Microsoft. I received my PhD degree from the Department of Computer Science and Engineering, Michigan State University, advised by Professor Jiayu Zhou. I am an alumni member of the ILLIDAN Lab@MSU.

My research interest resides in both applied and fundamental machine learning. I am dedicated to developing principled algorithms that facilitate knowledge transfer across domains. My current research focuses on Federated Learning and Reinforcement Learning. My previous research involves systems, scheduling, and wireless networking. Some of my selected research topics:

📢📢 I will join the Department of Cyber Security Engineering at George Mason University as a tenure-track assistant professor in Jan 2024. I am looking for prospective Ph.D. students starting at Spring 2024 or Fall 2024. Please email me your CV, transcript, and a Statement of Purpose if you are interested!

  • Knowledge Transfer; Domain Adaptation;
  • Federated Learning
  • Reinforcement Learning
  • Robustness, Fairness, Privacy, and Security for AI
  • Wireless Networking; IoT; Edge Computing
  • Knoweldge Distillation from LLM
  • PhD in Computer Science, 2017 - 2022

    Michigan State University

  • Exchange Program in Computer Science, 2014

    Australian National University

  • BSc in Computer Science, 2011 - 2015

    Nanjing University of Science and Technology

Professional Activities


  • August, 2023 🎉 We hosted a KDD workshop on federated learning for distributed data mining (FL4Data-Mining). Check more details at fl4data-mining.github.io.
  • June, 2023 🎉 Our survey paper, Transfer Learning in Deep Reinforcement Learning has been accepted for publication in the IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) journal.
  • Feb, 2023: Check out our preprint survey paper about Topology-aware Federated Learning in Edge Computing.
  • Sep, 2022: I joined Microsoft as a Senior Data & Applied Scientist.
  • Aug, 2022: Our paper about Robust Unsupervised Domain Adaptation has been accepted by ICDM 2022 [paper].
  • May, 2022: Our paper about Resilient and Communication Efficient Federated Learning has been accepted by ICML 2022 [paper].
  • Dec, 2021: Our paper about Self-Adaptive Imitation Learning has been accepted by AAAI 2022 [paper].
  • June, 2021: I joined the Ads Core Machine Learning team of Meta as a PhD SDE intern.
  • May, 2021: Our paper about Knowledge Transfer in Federated Learning has been accepted by ICML 2021 [paper] [code].
  • May, 2021: Our paper about Debiasing in Federated Learning has been accepted by KDD 2021 [paper] [project].
  • Sep, 2020 Our paper about Imitation Learning has been accepted by NeurIPS 2020 [paper] [code].

Invited Talks

  • Aug, 2023, Invited talk on AI2Healthcare. [video]
  • Jan, 2023, Invited talk at GMU: Knowledge Distillation for Efficient Learning in Heterogeneous Federated Systems.
  • Dec, 2022, Invited talk at UT Austin: Efficient Knowledge Transfer for Heterogeneous Machine Learning Domains.
  • ICML 2022 Spotlight Presentation: Resilient and Communication Efficient Learning for Heterogeneous Federated Systems. [video]
  • AAAI 2022 Short Presentation: Self Adaptive Imitation Learning: Learning Sparse Rewarded Tasks from Sub-Optimal Demonstrations.
  • ICML 2021 Poster Presentation: Data-free knowledge Distillation for Heterogeneous Federated Learning.
  • NeurIPS 2020 Poster Presentation: Off-Policy Imitation Learning from Observations. [slides].


  • Program Chair:

  • Session Chair:

    • 29th ACM SIGKDD Conference On Knowledge Discovery and Data Mining (KDD), 2023
  • Program Committee Member:

    • AAAI Conference on Artificial Intelligence (AAAI), 2021-2023
    • 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2022
  • Conference Reviewer:

    • Conference on Neural Information Processing Systems (NeurIPS), 2021 - 2023
    • International Conference on Machine Learning (ICML), 2021 -2023
    • AAAI Conference on Artificial Intelligence (AAAI), 2020 - 2023
    • International Conference on Learning Representations (ICLR), 2022 - 2023
    • ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2021 - 2023
    • IEEE International Conference on Robotics and Automation (ICRA), 2022 - 2023
    • IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2022 - 2023
  • Journal Reviewer:

    • IEEE TPAMI, 2022
    • IEEE Network Magazine, 2021 - 2022
    • IEEE Journal of Automatica Sinica, 2022
    • IEEE Robotics and Automation Letters, 2021 - 2022
    • NeuroComputing, 2020 -2023
    • Information Sciences, 2021 - 2022


I served as a teaching assistant for the following courses at MSU. I enjoy helping students master skills on analytical thinking, mathematics, and programming.

  • CSE 847: Machine Learning (Spring 2020, Spring 2021)
    • Volunteer teaching assistant for graduate-level machine learning class.
    • Instructor for pre-exam Q & A lab sessions.
    • Proposed lecture materials for CSE 847 advanced topics including Reinforcement Learning and Federated Learning.
  • CSE 231: Introduction to Programming (Spring 2017, Spring 2018, Fall 2018)
    • Instructor for weekly lab sessions to teach Python programming techniques.
    • Tutor for weekly in-person Q & A sessions for hundreds of students.
    • Designed homework projects about Python data structures, including Class and String.
  • CSE 260: Discrete Structures in Computer Science (Fall 2017)
    • Teaching assistant for undergraduate-level classes; Served for grading, office-hours, and Q & A sessions.


Senior Data & Applied Scientist
Sep 2022 – Oct 2023 WA, USA
Revolutionizing AI-powered Search Engine with Large Language Models.
Meta (Facebook)
PhD Intern - Machine Learning Track
Meta (Facebook)
May 2021 – Aug 2021 WA, USA
Improved facebook users’ long-term engagement via Reinforcement Learning.
Reasearch Associate
Jan 2019 – May 2019 Beijing, China
Improved digital market making with AI empowered risk prediction.
PhD Intern
May 2018 – Aug 2018 CA, USA
Research Intern
Jan 2015 – May 2015 Beijing, China

Selected Publications

Please check Google Scholar for my complete publications

Quickly discover relevant content by filtering publications.
My Cat "RiceCake"

My Cat "RiceCake"

Silly Handsome

More About Me

  • I have a cat named RiceCake.
  • I love tennis, snowboarding, and swimming.
  • I play Just Dance like a pro.
  • Travel, Hiking, Jazz, Musical Romance
  • Movies, Reading
  • Singing, Dancing
  • Gym & Coffee