People also call him Robin.

Email: zw287 at cornell dot edu / wuziyang at idea dot edu dot cn
Google Scholar


I am a researcher advised by Prof. Harry Shum at International Digital Economy Academy (IDEA) in Shenzhen, China. I obtained my MS degree at Cornell University advised by Prof. Bharath Hariharan and Prof. Madeleine Udell. I graduated summa cum laude and received my BS degrees from Cornell University in Computer Science and in Operations Research. I also work closely with Prof. Yi Ma from UC Berkeley. My primary research interests lie in machine learning and computer vision.


(* indicates equal contribution)


Incremental Learning of Structured Memory via Closed-Loop Transcription
Shengbang Tong, Xili Dai, Ziyang Wu , Mingyang Li, Brent Yi, Yi Ma

Efficient Maximal Coding Rate Reduction by Variational Forms
Ziyang Wu*, Christina Baek*, Kwan Ho Ryan Chan, Tianjiao Ding, Heung-Yeung Shum, Yi Ma, Benjamin Haeffele

Closed-Loop Data Transcription to an LDR via Minimaxing Rate Reduction
Xili Dai*, Shengbang Tong*, Mingyang Li*, Ziyang Wu* , Kwan Ho Ryan Chan, Pengyuan Zhai, Yaodong Yu, Michael Psenka, Xiaojun Yuan, Heung-Yeung Shum, Yi Ma

Conferences & Workshops

How Low Can We Go: Trading Memory for Error in Low-Precision Training
Chengrun Yang*, Ziyang Wu* , Jerry Chee, Christopher De Sa, Madeleine Udell
International Conference on Learning Representations (ICLR), 2022
[link] [arxiv] [code]

Incremental Learning via Rate Reduction
Ziyang Wu* , Christina Baek*, Chong You, Yi Ma
Conference of Computer Vision and Pattern Recognition (CVPR), 2021
ICML Workshop on Theory and Foundation of Continual Learning, 2021 (Oral Presentation)

Can We Characterize Tasks Without Labels or Features
Bram Wallace*, Ziyang Wu* , Bharath Hariharan
Conference of Computer Vision and Pattern Recognition (CVPR), 2021
[link] [code]

TenIPS: Inverse Propensity Sampling for Tensor Completion
Chengrun Yang, Lijun Ding, Ziyang Wu , Madeleine Udell
NeurIPS 2020 Workshop on Optimization for Machine Learning (OPT), 2020 (Oral Presentation)
International Conference on Artificial Intelligence and Statistics (AISTATS), 2021

AutoML Pipeline Selection: Efficiently Navigating the Combinatorial Space
Chengrun Yang, Jicong Fan, Ziyang Wu , Madeleine Udell
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2020
[link] [code]


Automated Machine Learning and Task Space Navigation
Ziyang Wu
Master’s Thesis, Cornell University, 2021


Maximizing Rate Reduction: Principle and Applications
International Digital Economy Academy (IDEA), Oct. 2021

Incremental Learning via Rate Reduction
ICML Workshop on Theory and Foundation of Continual Learning, Jul. 2021


CS 4700 (Fall 2018, Fall 2019, Fall 2020): Foundations of Artificial Intelligence (Teaching Assistant)

CS 2800 (Fall 2016, Spring 2021): Discrete Structures (Teaching Assistant)

CS 4670/5670 (Spring 2020): Introduction to Computer Vision (Teaching Assistant)

CS 4820 (Fall 2017, Summer 2020): Introduction to Algorithms (Teaching Assistant)

CS 3110 (Spring 2017): Data Structures and Functional Programming (Teaching Assistant)


Thanks Haozhi Qi for sharing this html template.