About Me

I'm a currently enrolled Ph.D. student at the VITA group at the University of Texas at Austin under the supervision of Dr. Zhangyang (Atlas) Wang. I obtained my Bachelor's degree from Beijing University of Posts and Telecommunications (BUPT) in June 2018. From August 2018 to December 2020, I worked as a research assistant with professor Nuria González Prelcic in UT. My current research interests include symbolic reasoning, graph neural networks, transformers, reinforcement learning and second order optimization. Here is my [CV].


  • Symbolic Reasoning
  • Graph Neural Networks
  • Transformers
  • Second Order Optimization (Learning to Optimize)
  • Reinforcement Learning


  • The University of Texas at Austin
    M.S. in Engineering, Aug. 2018 - Dec.2020
    Ph.D., Dec. 2020 - present

  • Beijing University of Posts and Telecommunications
    B.Eng. in Communications Engineering, Sept. 2014 - Jun. 2018

Professional Experience

  • Research Intern, Google Cloud, May 2022 - present
    • Performance prediction, workload and platform matching for cloud computing.
    • Host(s): Dr. Eric Zhang, Dr. Chelsea Llull
  • Applied Science Research Intern, Amazon A9, May 2021 - March 2022
    • Cold-start graph embedding learning for recommendation systems: first pretrain a graph model to generate versatile node embeddings using self-supervised learning, then learn a student model that is able to generalize to strict-cold-start nodes.
    • Manager/Mentor(s): Dr. Karthik Subbian, Dr. Nikhil Rao
  • Research Assistant, Visual Informatics Group, the University of Texas at Austin
    • Advisor: Dr. Zhangyang (Atlas) Wang
    • Research topics include:
      • Learning to Optimize: deliver faster and better optimizer for deep neural networks through back-propogate through the optimization procedure and find optimal optimizer in a data driven way.
      • Transformers: leverage the sequence modeling power of transformers in graph modeling/reinforcement learning.
      • Graph Networks: develop efficient graph models that scales and generalize.
  • Research Assistant, WSIL Group, the University of Texas at Austin
    • Estimate user device position through 5G millimeter wave signal, using compressive sensing (Orthogonal Mathing Pursuit) and deep learning (ConvNets, swarm based learning to optimize) approaches.
    • Advisor: Dr. Nuria González Prelcic
  • Research Intern, GEIRI North America
    • Train a Soft Actor-Critic agent to manage large scale power grid: embed the huge discrete geometric actionsinto continuous space; using Graph Neural Networks as preprocessing; Monte-Carlo Tree search as efficientexploration
    • Mentor: Dr. Jiajun Duan
  • Research Assistant, UWC Lab, Beijing University of Posts and Telecommunications
    • Signal processing for wireless communications (Doppler spread estimation)
    • Advisor: Dr. Wenjun Xu


Wenqing Zheng, Edward W Huang, Nikhil Rao, Sumeet Katariya,
Zhangyang Wang, Karthik Subbian, in International Conference
on Learning Representations (ICLR) 2022
Wenqing Zheng, Tianlong Chen, Ting-Kuei Hu, Zhangyang Wang,
in International Conference on Learning Representations (ICLR) 2022
Peihao Wang, Wenqing Zheng, Tianlong Chen, Zhangyang Wang,
in International Conference on Learning Representations (ICLR) 2022
Tianlong Chen, Kaixiong Zhou, Keyu Duan, Wenqing Zheng,
Peihao Wang, Xia Hu, and Zhangyang Wang, in TPAMI, 2022
Wenqing Zheng, Qiangqiang Guo, Hao Yang, Peihao Wang,
Zhangyang Wang, In NeurIPS 2021.

Yaqian Xu, Wenqing Zheng, Jingchen Qi, Qi Li, 2019 IEEE International
Conference on Image Processing (ICIP). IEEE, 2019: 4519-4523.

W. Zheng, A. Ali, N. González-Prelcic, R. W. Heath Jr., A. Klautau, and
E. Moradi Pari, 2020 IEEE 91st Vehicular Technology Conference
(VTC2020). IEEE, 2020: 1-5.

Wenqing Zheng, Nuria González-Prelcic, 2019 53rd Asilomar Conference
on Signals, Systems, and Computers. IEEE, 2019: 1453-1458.


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