Brief Biography

Hi, my name is Qiao Zhang, I’m an assistant professor as well as a postdoctoral fellow at College of Computer Science, Chongqing University, China. My current research is about the privacy-preserving machine learning.

Education

  • Ph.D. (2017-2021, GPA: 3.96/4.0) in ECE (advised by Prof. Hongyi Wu), Old Dominion University, Norfolk, VA, USA.
  • M.S. (2014-2017, ranking in major: 1/441) in ECE, Chongqing University of Posts and Telecommunications, Chongqing, China.
  • B.S. (2010-2014, ranking in major: 1/333) in ECE, Chongqing University of Posts and Telecommunications, Chongqing, China.

Publication

  • Xu, X., Zhang, Q., Ning, R., Xin, C., & Wu, H. (2024). SPOT: Structure Patching and Overlap Tweaking for Effective Pipelining in Privacy-Preserving MLaaS with Tiny Clients. In ICDCS.

  • Zhang, Q., Xiang, T., Xin, C., & Wu, H. (2024). United We Stand: Accelerating Privacy-Preserving Neural Inference by Conjunctive Optimization with Interleaved Nexus. In AAAI.

  • Zhang, Q., Xiang, T., Xin, C., & Wu, H. (2024). From Individual Computation to Allied Optimization: Remodeling Privacy-Preserving Neural Inference with Function Input Tuning. In S&P.

  • Cai, Y., Zhang, Q., Ning, R., Xin, C., & Wu, H. (2024). MOSAIC: A Prune-and-Assemble Approach for Efficient Model Pruning in Privacy-Preserving Deep Learning. In AsiaCCS.

  • Zhang, Q., Xiang, T., Cai, Y., Zhao, Z., Wang, N., & Wu, H. (2022). Privacy-Preserving Machine Learning as a Service: Challenges and Opportunities. In IEEE Network.

  • Cai, Y., Zhang, Q., Ning, R., Xin, C., & Wu, H. (2022). Hunter: HE-friendly structured pruning for efficient privacy-preserving deep learning. In AsiaCCS.

  • Zhang, Q., Xin, C., & Wu, H. (2021). Privacy Preserving Deep Learning based on Multi-Party Secure Computation: A Survey. In IEEE Internet of Things Journal.

  • Zhang, Q., Xin, C., & Wu, H. (2021). GALA: Greedy ComputAtion for Linear Algebra in Privacy-Preserved Neural Networks. In NDSS.

  • Zhang, Q., Xin, C., & Wu, H. (2020). SecureTrain: An Approximation-Free and Computationally Efficient Framework for Privacy-Preserved Neural Network Training. In IEEE Transactions on Network Science and Engineering.

  • Zhang, Q., Wang, C., Wu, H., Xin, C., & Phuong, T. V. (2018). GELU-Net: A Globally Encrypted, Locally Unencrypted Deep Neural Network for Privacy-Preserved Learning. In IJCAI.

Service

  • TPC Member:IEEE ICDCS’24.
  • Conference Reviewer:IEEE INFOCOM, AAAI, ACL, IEEE ICDCS, IWQoS.
  • Journal Reviewer:IEEE TMC, IEEE TC, IEEE TDSC, IEEE TIFS, ACM CSUR, IEEE TSP, IEEE TVT, IEEE Internet of Things Journal.