Yiding Hua

I am a second-year PhD student in theoretical computer science at ETH Zurich, advised by Prof. David Steurer. My research focuses on algorithmic aspects of high-dimensional statistics.

E-Mail: yiding (dot) hua (at) inf (dot) ethz (dot) ch

Education

• 2023-present: PhD in Computer Science, ETH Zurich, advised by Prof. David Steurer.
• 2020-2023: MSc in Computer Science, ETH Zurich.
• 2016-2020: BEng in Software Engineering (Honours Class I and University Medal), University of Sydney.

Publications

• Improved Robust Estimation for Erdős-Rényi Graphs: The Sparse Regime and Optimal Breakdown Point,
  with Hongjie Chen, Jingqiu Ding, Stefan Tiegel.
  In Submission, arxiv.
  


• Low Degree Conjecture Implies Sharp Computational Thresholds in Stochastic Block Model,
  with Jingqiu Ding, Lucas Slot, David Steurer.
  In Submission, arxiv.
  


• Private Edge Density Estimation for Random Graphs: Optimal, Efficient and Robust,
  with Hongjie Chen, Jingqiu Ding, David Steurer.
  NeurIPS 2024 (spotlight), arxiv.
  


• Private Graphon Estimation via Sum-of-Squares,
  with Hongjie Chen, Jingqiu Ding, Tommaso d'Orsi, Chih-Hung Liu, David Steurer.
  STOC 2024, arxiv.
  


• Reaching Kesten-Stigum Threshold in the Stochastic Block Model under Node Corruptions,
  with Jingqiu Ding, Tommaso d'Orsi, David Steurer.
  COLT 2023, arxiv.
  


• SQ Lower Bounds for Random Sparse Planted Vector Problem,
  with Jingqiu Ding.
  ALT 2023, arxiv.
  


• Maintaining Expander Decompositions via Sparse Cuts,
  with Rasmus Kyng, Maximilian Probst Gutenberg, Zihang Wu.
  SODA 2023, arxiv.
  


• Smart Redbelly Blockchain: Reducing Congestion for Web3,
  with Deepal Tennakoon, Vincent Gramoli.
  IPDPS 2023, proceeding.
  


• CollaChain: A BFT Collaborative Middleware for Decentralized Applications,
  with Deepal Tennakoon, Vincent Gramoli.
  Manuscript, arxiv.