My name is Zexuan Zhong. I am a M.S. student at Department of Computer Science, University of Illinois at Urbana-Champaign. I am working with Prof. Tao Xie on Intelligent Software Engineering, with recent topics on program synthesis, and security for AI system. I also work closely with Prof. Jian Peng. Before coming to UIUC, I received a B.S. in Computer Science from Peking University. During summer 2018, I was doing research at MIT Media Lab under supervision of Prof. Fadel Adib. I was also a full-time research intern at Microsoft Research Asia in my undergrad senior year.


  1. Learning Food Quality and Safety using Wireless Stickers
    Unsoo Ha, Yunfei Ma, Zexuan Zhong, Tzu-Ming Hsu, Fadel Adib
    Download: [PDF]
  2. SemRegex: A Semantics-Based Approach for Generating Regular Expressions from Natural Language Specifications
    Zexuan Zhong, Jiaqi Guo, Wei Yang, Jian Peng, Tao Xie, Jian-Guang Lou, Ting Liu, Dongmei Zhang
    Download: [PDF]
  3. CoLink: An Unsupervised Framework for User Identity Linkage
    Zexuan Zhong, Yong Cao, Mu Guo, Zaiqing Nie
    Download: [PDF]
  4. Generating Regular Expressions from Natural Language Specifications: Are We There Yet?
    Zexuan Zhong, Jiaqi Guo, Wei Yang, Tao Xie, Jian-Guang Lou, Ting Liu, Dongmei Zhang
    Download: [PDF]
  5. MULDEF: Multi-model-based Defense Against Adversarial Examples for Neural Networks
    Siwakorn Srisakaokul, Zexuan Zhong, Yuhao Zhang, Wei Yang, Tao Xie
    arXiv: 1809.00065
    Download: [PDF]

Selected Projects

Breaking transferability (ongoing)
One property of adversarial examples is transferability: adversarial examples for one model can also mislead other models. We explore how to break the transferability for adversarial examples, i.e, to train a complementary model given a reference model (adversarial examples cannot transfer across them). The problem is formalized as a non-convex min-max game problem. We propose a convex approximation to effectively solve the problem.
Regexs generation from NL sentences
We focus on automatically generating regular expressions from natural language specifications. Existing approaches reduce the target problem to a general machine translation task. We find a huge drop of performance when applying existing approaches on real-world data vs synthetic data. We propose to utilize string examples of regexs to define the semantic correctness, and use reinforcement learning to maximize the semantic correctness of regexs predicted by the model.
User Identity Linkage
User Identity Linkage refers to match identical users across two social networks. In this project, we propose an unsupervised framework based on co-training to address this problem. We develop an attribute-based model and a relationship-based model. The models will be enhanced in iterative way via co-training. We also propose to employ sequence-to-sequence learning to measure the similarity of attributes, which is an effective implementation of attribute-based model.
DualFocus is a tool for image refocusing. DualFocus takes two images with different focal lengths as input, and outputs an all-in-focus image. For each image, we solve a deconvolution problem with constrains based on prior characteristics of natural in-focus images. We then use Alternating Direction Method of Multipliers (ADMM) to minimize the differences between the deconvolution results for two input images. DualFocus does not require modification of cameras (i.e., coded aperture), and outperformances single-image-based refocusing approaches.
ObjRender is a tool to render 3D synthetic objects in images. We use a mirror ball as a light probe to obtain environment mapping. We take several low dynamic range (LDR) images of the mirror ball to recover a high dynamic range (HDR) image. We build the environment lighting box by mapping the HDR image in sphere domain to the equirectangular domain. We annotate necessary geometry models such as tables in the scene, and render the synthetic objects on those models.


  • 2017.8 - present, University of Illinois at Urbana-Champaign
    M.S. in Computer Science
  • 2013.9 - 2017.7, Peking University
    B.S. in Computer Science and Technology


  • 2017.8 - present, Research Assistant, University of Illinois at Urbana-Champaign
    Advisor: Prof. Tao Xie
  • 2018.5 - 2018.8, Visiting Research Assistant, MIT Media Lab
    Advisor: Prof. Fadel Adib
  • 2016.7 - 2017.5, Research Intern, Microsoft Research Asia
    Mentors: Dr. Zaiqing Nie and Dr. Yong Cao
  • 2015.11 - 2016.5, Research Assistant, Peking University
    Advisor: Prof. Yingfei Xiong


  • Siebel Scholar Class of 2019 [News Post]
  • Tang Li-Xin Scholar (4 in 400), 2014 - present
  • Beijing City Excellent Graduate, 2017
  • Peking University Excellent Graduate, 2017
  • Bachelor of Science Summa Cum Laude, 2017
  • Peking University Merit Student, 2014 - 2017

Program Contests

  • Finalist, ACM-ICPC World Final, 2019
  • Gold Medal, ACM-ICPC Mid-Central USA Regionals Chicago site, 2018
  • Gold Medal, ACM-ICPC Mid-Central USA Regionals Chicago site, 2017
  • Gold Medal, ACM-ICPC Asia Regionals Changchun site, 2013
  • First Prize, China National Olympiad in Informatics, 2012


3107 Siebel Center
201 N. Goodwin Ave.
Urbana, IL 61801, USA
Email: zexuan2@illinois.edu