cv

General Information

Name Hanhan Zhou
CV Resume(PDF)

Education

  • 2024 (expected)
    Ph.D. Student in Electrical and Computer Engineering
    the George Washington University
    • Reinforcement Learning
    • Federated Learning
    • Generative Models
    • Cyber Security

Academic Interests

  • Multi-Agent Reinforcement Learning
    • Proposed several frameworks aiding global value function factorization in multi-agent reinforcement learning, including deep variational information bottleneck method, utlizing counterfactual assitive information and optimal prioritized experience replay.
    • Evaluated the proposed method on the several challenging benchmarks including StarCraft II challenge and demonstrated a substantial performance improvement.
    • Several papers are published in NeurIPS, AAAI, AAMAS and IEEE trans.
  • Optimizations in Distributed Learning
    • Proposed an optimization algorithm and conducted convergence analysis with in-depth theoretical exploration of generalized Heterogeneous Federated Learning.
    • Validated the proposed theory on several datasets and provided remarks on designing algorithms of heterogeneous federated learning with actionable insights for designing and developing models of local clients.
    • Preliminary works are published at NeurIPS 2023 and International Workshop on Federated Learning 2022 (FL-NeurIPS'22) for oral presentation (~5%).
  • Cyber and Software Security
    • Conducted software security testing using {AFL}-based fuzzing tools on communication protocols like SSL and proposed a machine-learning-based privacy-preserving app for Android using the Xposed framework.
    • Studied the occurrence of concurrent bugs in JavaScript inside the WebKit engine, and proposed a framework that generates critical conditions to promote the reproduction of concurrency-related bugs within limited execution overhead, the work is accepted at CCS FEAST 2020.

Awards and Honors

  • 2022
    • NeurIPS Scholar Award
  • 2021
    • Lin Weng Graduate Scholarship
    • Runner Up Prize at GW New Venture Competition
  • 2019
    • Facebook Research Scholarship
    • GW SEAS Graduate Ambassador

Services

  • Reviewer
    • Advances in Neural Information Processing Systems (NeurIPS)
    • IEEE International Conference on Computer Communications (INFOCOM)
    • IEEE/ACM Transactions on Networking
    • IEEE Transactions on Artificial Intelligence
    • IEEE Transactions on Communications
    • New Frontiers in Graph Learning (GLFrontiers)
    • Foundation Models for Decision Making (FMDM), NeurIPS Workshop
    • Temporal Graph Learning Workshop, NeurIPS Workshop