I am a PhD student at Cornell University in the Department of Computer Science, where I am co-advised by Prof. Vitaly Shmatikov and Chris De Sa, previously I received my bachelor degree in Mathematics from Shanghai Jiao Tong University in July 2019, where I am fourtunated to work with Prof. John E. Hopcroft and Huan Long.

My primary research interest lies in private and secure machine learning, such as defending against adversarial examples, developing privacy-preserving algorithms and mitigating the tradeoff between accurcy and robustness & privacy. Beyond this scope, I am also interested in adopting hyperbolic geometry in ML for stronger and accurate models, recently I am also pretty interested in federated learning.

We host the Machine Learning Security, Privacy & Fairness group weekly in Ithaca campus [Past Schedule].

[Curriculum Vitae] [Google Scholar] [Github] [LinkedIn]

Education & Experience

Research Intern June 2020 - Aug. 2020

It's my fortune to intern at Apple Turi AI/ML Privacy team with Ulfar Erlingsson, to look into and evaluate privacy guarantess in federated learning practically.

Research Intern July 2018 - Dec. 2018

Happy to get the research intern opportunity in Cornell CS from Prof. Kilian Q. Weinberger, to work on defenses against adversarial examples and simplifying GCN for NLP tasks. I also work closely with Prof. Chris De Sa on developing numerically robust and accurate models for hyperbolic embeddings of graphs.

B.S. in Mathematics Sep. 2015 - July 2019

It's my great honor to major in Mathematics and Applied Mathematics (ZhiYuan honours programme) at Shanghai Jiao Tong University, where I am so lucky to work with Prof. John E. Hopcroft and Huan Long, we analyzed both theoretically and experimentally of the intrinsic dimension of the manifolds embedded in neural networks.

Recent Projects


Tao Yu, Eugene Bagdasaryan, Vitaly Shmatikov. "Salvaging Federated Learning by Local Adaptation", [Code].

Tao Yu, Chris De Sa. "Numerically Accurate Hyperbolic Embeddings Using Tiling-Based Models", Spotlight, [Compression Code, Learning Code, Slides, Poster]. In 33rd Conference on Neural Information Processing Systems (NeurIPS 2019).

Tao Yu*, Shengyuan Hu*, Chuan Guo, Wei-Lun Chao, Kilian Q. Weinberger. "A New Defense Against Adversarial Images: Turning a Weakness into a Strength", [Code, Poster]. In 33rd Conference on Neural Information Processing Systems (NeurIPS 2019)

Felix Wu*, Tianyi Zhang*, Amauri Holanda de Souza Jr.*, Christopher Fifty, Tao Yu, Kilian Q. Weinberger. "Simplifying Graph Convolutional Networks", [Code]. In 36th International Conference on Machine Learning (ICML 2019).

Tao Yu, Huan long, John Hopcroft. "Curvature-based Comparison of Two Neural Networks". In 24th International Conference on Pattern Recognition (ICPR 2018).

Tao Yu, Yu Qiao, Huan Long. "Knowledge-based Fully Convolutional Network and Its Application in Segmentation of Lung CT Images". (Technical Report)

Professional Activities




NeurIPS 2019, "Numerically Accurate Hyperbolic Embeddings Using Tiling-Based Models".