Wei Zhang 张蔚

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I am an assistant professor of Harbin Institute of Technology Shenzhen. Before that, I was a postdoctoral research fellow in School of Electrical and Electronic Engineering at Nanyang Technological University, working with Prof. Tay Wee Peng. Before this, I received my Ph.D. degree in the Department of Electrical Engineering at the City University of Hong Kong (CityU), supervised by with Prof. Shu-Hung Leung and Prof. Taejoon Kim. I received the B.S. and M.S. degrees from the Harbin Institute of Technology, Harbin, China, in 2013 and 2015, respectively.

Assistant Professor
School of Electronics and Information Engineering
Harbin Institute of Technology Shenzhen

Email: zhangwei.sz[AT]hit[DOT]edu[DOT]cn

Recent News

  • [August 2024] Our paper “Channel Estimation for Movable-Antenna MIMO Systems Via Tensor Decomposition” is accepted by IEEE Wireless Communication Letters.

  • [June 2024] Congratulations to Li Fujin and Luo Xinyi on receiving the Department's Excellent Undergraduate Graduation Design Award!

  • [April 2024] Our paper “A Novel Domain Transformation Based on Iterative Rotation for Linear Time-Variant Fading Channels” is accepted by IEEE Transactions on Vehicular Technology.

  • [January 2024] Our paper “Restricted Isometry Property of Rank-One Measurements with Random Unit-Modulus Vectors” is accepted by AISTATS 2024.

  • [September 2023] Welcome Gengshuo Chang and Lehan Zhang to join our group!

  • [September 2023] Our paper “Successful Recovery Performance Guarantees of SOMP Under the L2-Norm of Noise” is accepted by IEEE Transactions on Vehicular Technology.

  • [April 2023] Our paper “Approximate Maximum-Likelihood RIS-Aided Positioning” is accepted by IEEE Transactions on Wireless Communications.

Research Interests

My researchs focus on low-rank matrix recovery and its application in millimeter wave channel estimation. The current research topics include:

  • Millimeter wave channel estimation: AoAs and AoDs estimation, hybrid precoding, and subspace estimation

  • Low-rank matrix recovery: restricted isolated property analysis and convex optimization

  • Statistical analysis: probability analysis and robust parameter estimation