Hello! I am a final year PhD student at Boston University, advised by Prof. Yannis Paschalidis and Prof. Ashok Cutkosky.

I am broadly interested in the theoretical aspects of machine learning, optimization and control theory. Specifically, I work on adaptive online learning, i.e., designing online decision making algorithms that optimally exploit problem structures.

Recently I am thinking about how to systematically simplify the design and verification of online learning algorithms, from a continuous-time perspective. I am looking for a postdoc position starting in Fall 2023.

Prior to BU, I studied mechanical engineering at Tsinghua University.

Email address: zhiyuz [at] bu (dot) edu

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Research

• Unconstrained Dynamic Regret via Sparse Coding
  ZZ, Ashok Cutkosky, Ioannis Paschalidis.
  Preprint.

• Optimal Comparator Adaptive Online Learning with Switching Cost
  ZZ, Ashok Cutkosky, Ioannis Paschalidis.
  NeurIPS 2022. Also presented at ICML 2022 workshop.

• PDE-Based Optimal Strategy for Unconstrained Online Learning
  ZZ, Ashok Cutkosky, Ioannis Paschalidis.
  ICML 2022.

• Adversarial Tracking Control via Strongly Adaptive Online Learning with Memory
  ZZ, Ashok Cutkosky, Ioannis Paschalidis.
  AISTATS 2022.

• Provable Hierarchical Imitation Learning via EM
  ZZ, Ioannis Paschalidis.
  AISTATS 2021. Also presented at ICML 2020 Workshop.

Service

Reviewer for ICML, NeurIPS, AISTATS.

Top reviewer (10%) at AISTATS’22, ICML’22, NeurIPS’22.