Yuke Zhang 张钰珂

About Me

Yuke

I am a postdoc researcher in the ECE Department at the University of Toronto, where I work with Prof. Natalie Enright Jerger. I received my Ph.D. from the ECE Department of the University of Southern California, and I am very fortunate to be advised by Prof. Peter A. Beerel.

My research interests include My research vision aims to provide a comprehensive and vertically integrated suite of solutions for data privacy—from the algorithmic core to the silicon substrate—ensuring that privacy is not just an add-on feature but a foundational principle of modern ML systems.

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Publications (Full list)

(*= Equal contribution)

  1. Y. Zhang*, D. Chen*, S. Kundu*, C. Cheng, P. A. Beerel, "SAL-ViT: Towards Latency Efficient Private Inference on ViT using Selective Attention Search with a Learnable Softmax Approximation," ICCV 2023.
    Paper | Code | Video
  2. D. Chen*, Y. Zhang*, S. Kundu*, C. Cheng, P. A. Beerel, "RNA-ViT: Reduced-Dimension Approximate Normalized Attention Vision Transformers for Latency Efficient Private Inference," ICCAD 2023.
    Paper | Video
  3. Y. Zhang, D. Chen, S. Kundu, H. Liu, R. Peng, P. A. Beerel, "C2PI: An Efficient Crypto-Clear Two-Party Neural Network Private Inference," DAC 2023.
    Paper | Code (in preparation) | Video
  4. S. Kundu, Y. Zhang, D. Chen, P. A. Beerel, "Making Models Shallow Again: Jointly Learning to Reduce Non-Linearity and Depth for Latency-Efficient Private Inference," CVPR workshop (ECV) 2023.
    Paper
  5. Y. Hu, Y. Zhang, K. Yang, D. Chen, P. A. Beerel, P. Nuzzo, "On the Security of Sequential Logic Locking Against Oracle-Guided Attacks," TCAD-I 2023.
    Paper
  6. S. Kundu, S. Lu, Y. Zhang, J. Liu, P. A. Beerel, "Learning to linearize deep neural networks for secure and efficient private inference," ICLR 2023.
    Paper
  7. Y. Zhang*, Y. Hu*, P. Nuzzo, P. A. Beerel, "TriLock: IC Protection with Tunable Corruptibility and Resilience to SAT and Removal Attacks," DATE 2022
    Paper | Code | Video
  8. Y. Hu*, Y. Zhang*, K. Yang, D. Chen, P. A. Beerel, P. Nuzzo, "Fun-SAT: Functional Corruptibility-Guided SAT-Based Attack on Sequential Logic Encryption," HOST, 2021.
    Paper | Code
  9. D. El-Damak, P. Garcha, M. R. Abdelhamid, and Y. Zhang, "Circuit Implementation Using Emerging Technologies," IEEE SSCS Magazine, Fall Issue, 2021
    Paper
  10. C. Y. Ko, C. Chen, Z. He, Y. Zhang, K. Batselier, and N. Wong, "Model Compression and Inference Speedup of Sum–Product Networks on Tensor Trains," IEEE TNNLS, Sep. 2019.
    Paper
  11. Y. Zhang, D. El-Damak, "A Reconfigurable Passive Switched-Capacitor Multiply-and-Accumulate Unit for Approximate Computing," MWSCAS, 2020.
    Paper
  12. Y. Zhang, C. Y. Ko, C. Chen, K. Bastelier, N. Wong, "Sparse Tensor Network System Identification for Nonlinear Circuit Macromodeling," 2018 IEEE 14th International Conference on Solid-State and Integrated Circuit Technology. (Invited)
    Paper
  13. Y. Zhang, K. El-Sankary, J. Zhou, "A Blind Digital Background Calibration for VCO-based ADC," Analog Integrated Circuits and Signal Processing, vol 97, no.2, pp.387-394, Nov. 2018.
    Paper
  14. Y. Zhang, K. El-Sankary, "Offset-Injection Digital Background Calibration for VCO-based ADC," Analog Integrated Circuits and Signal Processing, vol. 92, no.3, pp.501-506, Jul. 2017.
    Paper
  15. Y. Zhang, K. El-Sankary, "Orthogonal Polynomials Nonlinearity Compensation for a digital VCO-based ADC," Electronics Letters, vol 52, no.11, pp 915-917, May 2016.
    Paper

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