Zecheng He

Ph.D Candidate

Department of Electrical Engineering, Princeton University

Email: zechengh@princeton.edu

I am a fifth-year PhD student in PALMS group, Department of Electrical Engineering at Princeton University, advised by Prof. Ruby B. Lee. I received M.A. in Electrical Engineering from Princeton University in 2017 and B.E. in Electronic Information Engineering from University of Science and Technology of China (USTC) in 2015, respectively.


Selected Publications

    Conference Paper

  • Model Inversion Attacks against Collaborative Inference
    Zecheng He, Tianwei Zhang and Ruby B. Lee
    Annual Computer Security Applications Conference (ACSAC'19), to appear (accept rate 22%)
    Oral Presentation

  • Sensitive-Sample Fingerprinting of Deep Neural Networks
    Zecheng He, Tianwei Zhang and Ruby B. Lee
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR'19), 2019

  • Power-Grid Controller Anomaly Detection with Enhanced Temporal Deep Learning
    Zecheng He, Aswin Raghavan, Guangyuan Hu, Sek Chai and Ruby B. Lee
    IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom'19), 2019
    Oral Presentation

  • How Secure Is Your Cache Against Side-channel Attacks?
    Zecheng He, and Ruby B. Lee
    IEEE/ACM International Symposium on Microarchitecture (Micro'17), 2017 (accept rate 18%)
    Oral Presentation

  • Cross-Scale Color Image Restoration Under High Density Salt-and-Pepper Noise
    Zecheng He, Ketan Tang and Lu Fang
    IEEE International Conference on Image Processing (ICIP'17), 2017

  • Machine Learning Based DDoS Attack Detection from Source Side in Cloud
    Zecheng He, Tianwei Zhang, and Ruby B. Lee
    IEEE International Conference on Cyber Security and Cloud Computing, 2017
    Oral Presentation


  • VerIDeep: Verifying Integrity of Deep Neural Networks through Sensitive-Sample Fingerprinting
    Zecheng He, Tianwei Zhang, Ruby B. Lee
    In submission [arXiv]

  • Detecting Zero-day Controller Hijacking Attacks on the Power-Grid with Enhanced Deep Learning
    Zecheng He, Aswin Raghavan, Sek Chai, Ruby B. Lee
    In submission [arXiv]

  • Privacy-preserving Machine Learning through Data Obfuscation
    Tianwei Zhang, Zecheng He, Ruby B. Lee
    Under Revision [arXiv]

Working Experience


  • Software Engineer Intern (Ph.D), Facebook
    Machine learning track, Core ML team in Business Integrity. May 2019 - Aug 2019, Menlo Park, CA
    Detect policy-violating ads through machine learning.
    Evaluate the proposed models on BI top-level metrics. Work has been adopted across teams.

  • Deep Learning Research Intern, SRI International
    Jun 2017 - Sep 2017, Princeton, NJ
    Enhancing deep temporal model with statistical test for processor anomaly detection in power-grid systems.
    Real-time and high-reliable controller abnormal behavior detection system design.

  • Deep Learning Research Intern, Huawei Technologies R&D
    Jun 2016 - Sep 2016, Bridgewater, NJ
    Adaptive-depth convolutional neural network (CNN) for image style transfer.

Selected Awards

  • 1st place, Siemens Futuremaker Hackthon, 2018   [Press1] [Press2]
  • Gordon Y.S. Wu Fellowship in Engineering, 2015-2019
  • Guo Moruo Scholarship, USTC, 2015   (top 1%, highest award for undergraduate excellence)
  • Honor Degree, Elites Class in Information Science, USTC, 2015
  • National Scholarship, China, 2014 (top 2%)
  • Honorable Fellowship, Institute of Electronics China Academy of Science, 2013


  • "Security Meets Deep Learning"
    Princeton AI Seminar, Princeton, Apr 2019

  • "How Secure Is Your Cache Against Side-Channel Attacks?"
    SRC Techcon, Austin TX, Sep 2018

  • "Security in Deep Learning"
    Z2AI, Princeton NJ, Aug 2018

  • "Deep Learning Meets Security"
    SRI International, Princeton NJ, Jun 2018

  • "Modeling and Evaluatiing Cache Resilience Against Side-channel Attacks"
    Princeton Research Day, Princeton NJ, May 2018

  • "Security Verification of Resilience to Cache Side-Channel Attacks"
    SRC T3S Annual Meeting, Portland OR, Sep 2016

Professional Service

    Session Chair

  • Session 4, IEEE International Conference on Cyber Security and Cloud Computing, New York, NY, 2017


  • 2016: Micro
  • 2017: Micro, HASP, IEEE ToC
  • 2018: CCS, S&P, Micro, HPCA
  • 2019: S&P, IEEE SPL


  • Teaching Assistant, ELE 470 Smartphone Security and Architecture, Princeton University, 2017 Fall
  • Teaching Assistant, Signals and Systems, University of Science and Technology of China (USTC), 2015 Spring
  • Teaching Assistant, The C Language Programing, University of Science and Technology of China (USTC), 2014 Fall


  • Princeton University
    Ph.D, Electrical Engineering, Sep 2015 -
    M.A., Electrical Engineering, Sep 2015 - May 2017
    Advisor:Prof. Ruby B. Lee

  • University of Science and Technology of China (USTC)
    B.E., Electronic Information Engineering, Sep 2011 - May 2015
    GPA 4.00/4.30, rank 1/252