Ziping Zhao

Ziping Zhao Assistant Professor School of Information Science and Technology ShanghaiTech University Shanghai, China

I am an Assistant Professor with the School of Information Science and Technology at ShanghaiTech University, Shanghai, China, where I joined in December 2019. I received the Ph.D. degree in Electronic and Computer Engineering (HK PhD Fellow) from the Hong Kong University of Science and Technology, Hong Kong in 2019, where I was fortunate to be advised by Prof. Daniel P. Palomar. Before that, I received a B.Eng. degree in Electronic and Information Engineering (ranked 1st for 4 years in a row) from the Qiming Honors College and the Department of Electronic and Information Engineering, Huazhong University of Science and Technology, Wuhan, China in 2014. I have held several visiting research positions in University of Minnesota, Twins City, MN, USA and the Hong Kong University of Science and Technology, Hong Kong.

I have been awarded the Best Student Paper Award at IEEE ICASSP 2023, and was a finalist for the Best Student Paper Award at IEEE SAM 2020, IEEE SPAWC 2021, and IEEE SAM 2024.

My current research interests are primarily in computational and statistical foundations of data science, signal processing, and machine learning. I am also interested in developing novel models and approaches for various applications related to data analytics.

Research Keywords

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The work in our laboratory follows the Reproducible Research Philosophy, thus all papers, source code, and data are made available in open access.

Teaching in Fall Term 2024-25

• CS182: Introduction to Machine Learning

• Time: Tue/Thu 8:15am-9:55am, Venue: Rm. 103, Teaching Center.

• Office hours: Tue 10:00am-11:30am, or by email appointment.

Recent News

• Sept 2024 | Two papers have been accepted by APSIPA ASC 2024.

  • “A Joint Graph Signal and Laplacian Denoising Network Inspired by Majorization-Minimization” (with Zepeng)

  • “Sparse Blind Deconvolution and Demixing via Block Majorization-Minimization” (with Mengting)

• Sep. 2024 | The paper “Graph Neural Networks with Adaptive Structures” (with Zepeng, Songtao, and Zengfeng) has been accepted by IEEE Journal of Selected Topics in Signal Processing: Special Series on AI in Signal & Data Science.

• July 2024 | Two papers have been accepted by ITW 2024.

  • “Geometric Analysis of Non-convex Optimization Landscapes for Robust M-Estimation of Location” (with Hongyuan and Ying)

  • “Improved Stability Bounds for Graph Convolutional Neural Networks under Graph Perturbations” (with Jun)

• July 2024 | Paper by Quan Wei entitled “High-Dimensional Constrained Huber Regression” has been selected as the Best Student Paper Award Finalist in IEEE SAM 2024. Congratulations!

• May 2024 | Mr. Quan Wei has successfully defended his master thesis “High-dimensional Covariance Matrix Estimation”. Congratulations! He will continue his Ph.D. study in University of Minnesota, USA.

• May 2024 | The paper “Accelerating Quadratic Transform and WMMSE” (with Kaiming, Yannan, Zepeng, and Victor) has been accepted by IEEE Journal on Selected Areas in Communications: Special Issue on Advanced Optimization Theory and Algorithms for Next Generation Wireless Communication Networks.
  

• Apr. 2024 | Three papers have been accepted by ISIT 2024.
  

  • “Guaranteed Robust Large Precision Matrix Estimation Under t-distribution” (with Fengpei)

  • “Efficient Nonconvex Optimization for Two-way Sparse Reduced-Rank Regression” (with Cheng)

  • “Accelerating Quadratic Transform and WMMSE” (with Kaiming, Yannan, Zepeng, and Victor)

• Apr. 2024 | Two papers have been accepted by GSP 2024.
  

  • “On Stability of GCNN Under Graph Perturbations” (with Jun)

  • “Graph Neural Networks With Adaptive Structures” (with Zepeng, Songtao, and Zengfeng)

• Apr. 2024 | Three papers have been accepted by SAM 2024.
  

  • “Two-way Sparse Reduced-Rank Regression via Scaled Gradient Descent with Hard Thresholding” (with Cheng)

  • “Distributed Sparse Covariance Matrix Estimation” (with Wenfu and Ying)

  • “High-Dimensional Constrained Huber Regression” (with Quan)

Find out more.

Contact

Office: Rm. 1A-404D, SIST Building [transportation guide]
Mailing Add.: SIST-37#, SIST Building, 393 Middle Huaxia Road, Pudong, Shanghai 201210, China
Web: www.zipingzhao.com
Email: first+last at shanghaitech dot edu dot cn OR last+first at shanghaitech dot edu dot cn