Shunhua Jiang

About me

I am a 5th year PhD student in the theoretical computer science group at Columbia University. I am fortunate to be advised by Prof. Omri Weinstein and Prof. Alexandr Andoni. My main research interests are optimization and data structures, while I am also broadly interested in other problems in theory and machine learning.

Experiences

Previously I obtained my bachelor's degree from Yao class at Tsinghua University, where I worked with Prof. Ran Duan and Prof. Jian Li.

In Spring 2018, I exchanged to Aarhus University where I worked with Prof. Kasper Green Larsen.

In Fall 2023, I will be visiting the Simons Institute at UC Berkeley to participate in the "Data Structures and Optimization for Fast Algorithms" program.

Publications

• The Complexity of Dynamic Least-Squares Regression. [arxiv]
  Shunhua Jiang, Binghui Peng, Omri Weinstein.
  FOCS 2023
• Solving SDP Faster: A Robust IPM Framework and Efficient Implementation. [arxiv]
  Baihe Huang, Shunhua Jiang, Zhao Song, Runzhou Tao, Ruizhe Zhang.
  FOCS 2022
• A Faster Interior-Point Method for Sum-of-Squares Optimization. [arxiv]
  Shunhua Jiang, Bento Natura, Omri Weinstein.
  ICALP 2022
• The Energy Complexity of Las Vegas Leader Election. [arxiv]
  Yi-Jun Chang, Shunhua Jiang.
  SPAA 2022
• Fast Graph Neural Tangent Kernel via Kronecker Sketching. [arxiv]
  Shunhua Jiang, Yunze Man, Zhao Song, Zheng Yu, Danyang Zhuo.
  AAAI 2022
• Faster Dynamic Matrix Inverse for Faster LPs. [arxiv]
  Shunhua Jiang, Zhao Song, Omri Weinstein, Hengjie Zhang.
  STOC 2021
• Near-Optimal Time-Energy Trade-Offs for Deterministic Leader Election. [arxiv]
  Yi-Jun Chang, Ran Duan, Shunhua Jiang.
  SPAA 2021
• Tight Revenue Gaps among Multi-Unit Mechanisms. [arxiv]
  Yaonan Jin, Shunhua Jiang, Pinyan Lu, Hengjie Zhang.
  EC 2021
• A Faster External Memory Priority Queue with DecreaseKeys. [arxiv]
  Shunhua Jiang, Kasper Green Larsen.
  SODA 2019
• Learning Gradient Descent: Better Generalization and Longer Horizons. [arxiv]
  Kaifeng Lv, Shunhua Jiang, Jian Li.
  ICML 2017

Manuscripts

• SupergeoDesign: Generalized Matching for Geographic Experiments. [arxiv]
  Aiyou Chen, Nick Doudchenko, Shunhua Jiang, Cliff Stein, Bicheng Ying.

Industry Research

• Research intern at Google (June 2022 - August 2022). Worked on supergeo experimental design for geo experiments. Hosted by Bicheng Ying and Nick Doudchenko.

Teaching

• Spring 2020: TA for COMS 4995-2: Advanced Algorithms, taught by Prof. Alexandr Andoni. Columbia University.

• Fall 2021: TA for COMS 6998: Algebraic Techniques in TCS, taught by Prof. Josh Alman. Columbia University.

Awards

• Simons-Berkeley Research Fellowship, Fall 2023.

• Google PhD Fellowship, 2022.

• Columbia Presidential Fellowship, 2019.

Miscellaneous

I am a big fan of the traditional Chinese kunqu opera.