Ziping Zhao
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I still have quotas of master students for 2024 intake. Please feel free to contact me.
I am currently 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 (HK PhD Fellow) in Electronic and Computer Engineering 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.
My current research interests are primarily in mathematical (especially, 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.
I have openings for highly self-motivated and hard-working Postgraduate Students (both master students and doctoral students) and Visiting Students working on the general areas of optimization, data science, signal processing, and machine learning. If you are interested, please contact me with your recent CV and transcripts.
I am always welcoming enthusiastic Research Interns to join the group.
I have one opening for the Research Assistant position.
For more details, see [Recruit Notice].
Research Interests
Optimization, Statistics;
Signal Processing, Machine Learning.
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 Spring Term 2023-24
SI231B: Matrix Computations (Matrix Methods for Data Analysis, Machine Learning, and Signal Processing)
Time: Tue/Thu 8:15am-9:55am, Venue: Rm. 1D-104, SIST Building.
Office hours: Tue 10:00am-11:30am, or by email appointment.
Time: Tue/Thu 1:00pm-2:40pm, Venue: Rm. 1D-107, SIST Building.
Office hours: Tue 3:00pm-4:30pm, or by email appointment.
Recent News
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 Structure” (with Zepeng, Zengfeng, and Songtao)
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)
Dec. 2023 | Three papers have been accepted by ICASSP 2024.
“Accelerating Gradient Descent for Over-parameterized Asymmetric Low-rank Matrix Sensing via Preconditioning” (with Cheng)
“Joint Blind Deconvolution and Demixing of Sparse Signals via Factorization and Nonconvex Optimization” (with Mengting)
“Large Covariance Matrix Estimation Based on Factor Models via Nonconvex Optimization” (with Shanshan)
Dec. 2023 | Our work entitled “On Convergence Rates of Quadratic Transform and WMMSE Methods” has been made available; see the preprint here.
Nov. 2023 | Our work entitled “Discerning and Enhancing the Weighted Sum-Rate Maximization Algorithms in Communications” has been made available; see the preprint here.
Aug. 2023 | The paper “Large Covariance Matrix Estimation With Oracle Statistical Rate via Majorization-Minimization” (with Quan) has been accepted by IEEE Transactions on Signal Processing.
Jun. 2023 | Paper by Quan Wei entitled “Large Covariance Matrix Estimation With Oracle Statistical Rate” has been selected as the Best Student Paper Award in IEEE ICASSP 2023. Congratulations! See the ICASSP news page.
May 2023 | Prof. Wei Hu from Peking University, China visited my group and gave a talk in SIST Seminar on “Graph Signal Processing and Graph Machine Learning”.
May 2023 | Mr. Zepeng Zhang has successfully defended his master thesis “Optimization Induced Graph Neural Networks”. Congratulations! He will continue his Ph.D. study in École Polytechnique Fédérale de Lausanne (EPFL), Switzerland.
Apr. 2023 | Three papers have been accepted by SSP 2023.
“A Novel Algorithm for GARCH Model Estimation” (with Chenyu and Daniel)
“C-ISTA: Iterative Shrinkage-Thresholding Algorithm for Sparse Covariance Matrix Estimation” (with Wenfu and Ying)
“Efficient Sparse Reduced-Rank Regression With Covariance Estimation” (with Fengpei)
Feb. 2023 | Two papers have been accepted by ICASSP 2023.
“Large Covariance Matrix Estimation With Oracle Statistical Rate” (with Quan) (Top 3% Recognition)
“Enhancing the Efficiency of WMMSE and FP for Beamforming by Minorization-Maximization” (with Zepeng and Kaiming)
The editor wrote that “It's kind of amazing that there still are some new possibilities to successfully twist this old but significant problem.”
Dec. 2022 | Our work entitled “Large Covariance Matrix Estimation With Oracle Statistical Rate via Majorization-Minimization” has been made available.
Oct. 2022 | Our work entitled “ASGNN: Graph Neural Networks With Adaptive Structure” has been made available; see the preprint here. In this work, we proposed a robust graph neural network model based on an optimization problem which aims at simultaneously denoising the graph signal and the graph structure.
Sep. 2022 | Prof. Siheng Chen from Shanghai Jiaotong University, China visited my group and gave a talk in SIST Seminar on “Multi-Agent Graph Learning”.
Jun. 2022 | Prof. Quanming Yao from Tsinghua University, China gave a talk in SIST Seminar on “Hyper-parameter Learning in Knowledge Graphs”.
Jun. 2022 | One paper has been accepted by SIGKDD-DLG 2022.
“Designing Graph Neural Networks via Algorithm Unrolling” (with Zepeng)
Jun. 2022 | Dr. Yatao Bian from Tecent AI Lab, China gave a talk in SIST Seminar on “Energy-Based Learning for Cooperative Games”.
May 2022 | Thesis by Mr. Xiuyuan Huang was selected as the Best SIST Undergraduate Thesis Award (First Runner-Up).
Jan. 2022 | Our work entitled “Towards Understanding Graph Neural Networks: An Algorithm Unrolling Perspective” has been made available; see the preprint here. In this work, we bridged the Graph Neural Network (GNN) models and the Graph Signal Denoising (GSD) problems based on an optimization perspective and the algorithm unrolling/unfolding technique.
Dec. 2021 | Dr. Junxiao Song from inspir.ai, China gave a talk in SIST Seminar on “Deep Reinforcement Learning for Game AI”.
Dec. 2021 | Our work entitled “Rate Maximizations for Reconfigurable Intelligent Surface-Aided Wireless Networks: A Unified Framework via Block Minorization-Maximization” has been made available; see the preprint here. In this work, we proposed a unified and convergent algorithmic framework to solve a class of rate maximization problems for general RIS/IRS-aided wireless networks achieving the SOTA performance.
Sep. 2021 | Paper by Zepeng Zhang entitled “Weighted Sum-Rate Maximization for Multi-Hop RIS-Aided Multi-User Communications: A Minorization-Maximization Approach” has been selected as the Best Student Paper Award Finalist in IEEE SPAWC 2021. Congratulations!
Jul. 2021 | Three papers have been accepted by Asilomar 2021.
“Sparse Reduced-Rank Regression With Adaptive Selection of Groups of Predictors” (with Quan and Yujia)
“Multi-Period Portfolio Optimization for Index Tracking in Finance” (with Xiuyuan and Zepeng)
“Waveform Design for Mutual Information Maximization via Minorization-Maximization”” (with Huanyu)
Jul. 2021 | One paper has been accepted by SPAWC 2021.
“Weighted Sum-Rate Maximization for Multi-Hop RIS-Aided Multi-User Communications: A Minorization-Maximization Approach” (with Zepeng)
Jun. 2021 | Mr. Weicong Liu from Jiwei Fund, China visited my group and gave a talk in SIST Seminar on “Financial Machine Learning”.
May 2021 | Two papers have been accepted by SSP 2021.
“Globally Convergent Algorithms For Learning Multivariate Generalized Gaussian Distributions” (with Bin, Huanyu, and Ying)
“Scalable Financial Index Tracking With Graph Neural Networks” (with Zepeng)
May 2021 | Two papers have been accepted by EUSIPCO 2021.
“Vast Portfolio Selection With Submodular Norm Regularization” (with Zepeng)
Mar. 2021 | Prof. Gang Wang from Beijing Institute of Technology, China visited my group and gave a talk in SIST Seminar on “Theory of Deep Learning and Temporal Difference (TD) Learning”.
Nov. 2020 | Dr. Lei Cheng from Shenzhen Research Institute of Big Data, China gave a talk in SIST Seminar on “Structured Tensor Decompositions in Big Data Analytics”.
Aug. 2020 | One paper has been accepted by Asilomar 2020.
“A Deep Learning-Aided Approach to Portfolio Design for Financial Index Tracking” (with Zepeng)
Jul. 2020 | Yao Zhao from ShanghaiTech University, China has joined the group as a Research Assistant. Welcome!
May 2020 | Paper by Fin Yang entitled “Online Robust Reduced-Rank Regression” has been selected as the Best Student Paper Award Finalist in IEEE SAM 2020. Congratulations!
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