Zhuangdi Zhu

Zhuangdi Zhu

Assistant Professor (Tenure-Track)

George Mason University

Biography

I am Zhu, Zhuangdi (朱 ). I am a tenure-track assistant professor at the Department of Cyber Security Engineering of George Mason University. Prior to that I worked as a senior Data & Applied Scientist for Microsoft. I received my Ph.D. degree from the Department of Computer Science and Engineering, Michigan State University, advised by Dr. Jiayu Zhou.

My current research centers around Accountable, Scalable, and Trustworthy AI, e.g., decentralized machine learning, knowledge transfer for supervised and reinforcement learning, and de-biased representation learning. My previous research involves systems, scheduling, and wireless networking. Some of my selected research topics:

📢📢 Prospective Ph.D. students and research interns: Please email me your CV, transcript, and a Statement of Purpose if you are interested!

Interests
  • Knowledge Transfer; Domain Adaptation;
  • Federated Learning
  • Reinforcement Learning
  • Robustness, Fairness, Privacy, and Security for AI
  • Wireless Networking; IoT; Edge Computing
  • Multi-Modal Learning
  • Privacy Preserving Large Language Models
Education
  • PhD in Computer Science, 2017 - 2022

    Michigan State University

  • BSc in Computer Science, 2011 - 2015

    Nanjing University of Science and Technology

Professional Activities

News

  • April, 2024: 📢 Call for Participation: Please join our first International Joint Workshop on Federated Learning for Data Mining and Graph Analytics, co-located with KDD2024, August 25-26th, at Barcelona.
  • April, 2024: Our survey paper on Topology-aware Federated Learning in Edge Computing is accepted by ACM Computing Surveys and selected in the ACM Showcase.
  • Jan, 2024: I joined GMU as an assistant professor.
  • 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 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].

Services

  • 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

Teaching

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

  • GMU CYSE 650: Introduction to Federated Learning (Spring 2024)
  • MSU 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.
  • MSU 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.
  • MSU CSE 260: Discrete Structures in Computer Science (Fall 2017)
    • Teaching assistant for undergraduate-level classes; Served for grading, office-hours, and Q & A sessions.

Experience

 
 
 
 
 
Microsoft
Senior Data & Applied Scientist
Microsoft
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.
 
 
 
 
 
CyberX
Reasearch Associate
Jan 2019 – May 2019 Beijing, China
Improved digital market making with AI empowered risk prediction.
 
 
 
 
 
Google
PhD Intern
Google
May 2018 – Aug 2018 CA, USA
 
 
 
 
 
IBM
Research Intern
IBM
Jan 2015 – May 2015 Beijing, China

Selected Publications

Please check Google Scholar for my complete publications

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My Cat "RiceCake"

My Cat "RiceCake"

Silly Handsome

More About Me

  • I have a cat named RiceCake.
  • I play Just Dance like a pro.
Interests
  • Travel; Reading; Movies
  • Jazz; Musical Romance
  • Tennis; Snowboarding