Jiacen(Jason) Xu

嘉涔 徐

I am a first-year Ph.D. student in DSP Lab, Department of Electrical Engineering and Computer Science at University of California, Irvine. My advisor is Prof. Zhou Li.

I received my B.S. and Master degree from Shanghai Jiao Tong University and got Outstanding Undergraduate in 2017 and Outstanding Graduate in 2020.

Email  /  Github  /  Google Scholar  /  Twitter  /  Blogs

profile photo
  • [04/02/2021] One paper is accepted by CVPR 2021.
  • [12/01/2020] I pass the Ph.D. Preliminary Examination on November 2020.
  • [09/01/2020] I become a Ph.D. student at University of California, Irvine on September 2020.

My research interests include Adversarial Machine Learning and Data-driven Security. Much of my research is about inferring the physical world and real world applications. Representative papers are highlighted.

Scalability vs. Utility: Do We Have to Sacrifice One for the Other in Data Importance Quantification?
Ruoxi Jia, Fan Wu*, Xuehui Sun*, Jiacen Xu*,  David Dao,  Bhavya Kailkhura, Ce Zhang, Bo Li, Dawn Song (*= Equal Contribution)
CVPR, 2021
project page / arXiv

Towards a unified min-max framework for adversarial exploration and robustness
Jingkang Wang, Tianyun Zhang, Sijia Liu, Pin-Yu Chen, Jiacen Xu, Makan Fardad, Bo Li
arXiv, 2019

Great thanks to Jon Barron and Yingwei Li.