Tong Wu


I am a PhD student at Princeton University .

Previously, I studied at Washington University in St. Louis , supervised by Prof. Yevgeniy Vorobeychik .

Research Interests: (Trustworthy) Machine Learning , Security, and Computer Vision

Please Check my [Curriculum Vitae]

Welcome to contact me via:


Defending against Physically Realizable Attacks on Image Classification

In Proceedings of the 8th International Conference on Learning Representations (ICLR’20)   Spotlight Presentation

Adversarial Robustness of Deep Sensor Fusion Models


Shaojie Wang, Tong Wu, Yevgeniy Vorobeychik        [Paper]    

Can Optical Trojans Assist Adversarial Perturbations?


Adith Boloor, Tong Wu, Patrick Naughton, Ayan Chakrabarti , Xuan Zhang, Yevgeniy Vorobeychik        [Paper]    

Systems and methods for defending against physical attacks on image classification

US Patent

Yevgeniy Vorobeychik , Tong Wu, Liang Tong        [Patent]    


Washington University in St. Louis

Bachelor/Master of Science
Major: Computer Science     Major: Mathematics -Probability/Statistics Track
GPA: 4.0/4.0   Major GPA: 4.0/4.0
  • Washington University in St. Louis Graduate Affiliation Scholarship
  • Undergraduate Research Award for Conference Travel
  • Member of TAU BETA PI (The Engineering Honor Society)
  • Research Excellence Award
Sep. 2018 - May 2021

DePauw University

Bachelor of Arts
Major: Pre-Engineering     Minor: Math
GPA: 3.94/4.0   Major GPA: 4.0/4.0
  • DePauw Merit Scholarship
  • DePauw Dean’s List
Sep. 2016 - May 2018


NEC Labs America

Research Intern

• Working on few shot learning, supervised by Jingchao Ni

Jan. 2021 - May 2021

University of California, Berkeley

Research Intern

• Worked on clean label poisoning attacks, supervised by Xinyun Chen and Prof. Dawn Song

Jan. 2021 - May 2021

Washington University in St. Louis

Research Assistant

• Studied the problem of defending deep neural network approaches for image classification from physically realizable attacks

Dec. 2018 - May 2021

University of Toronto

International Visiting Graduate Students

• Worked on adversarial robustness in audio space, supervised by Prof. Nicolas Papernot

May 2020 - Aug. 2020


Adversarial Machine Learning Resources