Gang WANG

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Hello, welcome to my personal webspace! I'm a currently PhD candidate in the Department of Electrical and Computer Engineering, and Digital Technology Center at the University of Minnesota. I am a member of the SPiNCOM research group directed by Professor Georgios B. Giannakis. I earned my Bachelor degree in Electrical Engineering and Automatic Control from Beijing Institute of Technology, Beijing, China in 2011.

Contact

Digital Technology Center
University of Minnesota, Minneapolis
117 Pleasant Street SE, Minneapolis, MN, 55455
Office: 460 Walter Library
E-mail: gangwangATumn.edu.

Recent news

  1. We won a Best Student Paper Award in the EUSIPCO’2017 Conference for the joint work with Profs. G. B. Giannakis and J. Chen on efficient algorithms for large-scale phase retrieval, which was selected from a few hundred submissions based on rigorous evaluations of the selection committee.

  2. Paper coauthored with Profs. G. B. Giannakis, Y. Saad (CS, UMN), and J. Chen (BIT) accepted to NIPS’2017 (Acceptance rate: 21%), which presents a new algorithm for solving systems of random quadratic equations benchmarking the numerical performance. Matlab codes available for download here.

  3. Paper on randomized block Franke-Wolfe algorithms, joint work with L. Zhang, D. Romero (Univ. of Agder, Norway), accepted to the IEEE Transactions on Signal Processing, in which we develop a rich family of feasible step sizes for running Frank-Wolfe in parallel. Congratulations Liang!

  4. Paper “Solving Random Systems of Quadratic Equations via Truncated Amplitude Flow,” joint work with Prof. Y. Eldar (Technion), accepted to the IEEE Transactions on Information Theory. Matlab codes available here.

  5. Paper on scalable composite optimization algorithms for robust LAV (least-absolute-value) power system state estimation submitted. Check it out in Publications.

  6. Invited book chapter on “Advances in Power System State Estimation,” coauthored with Profs. V. Kakatos (VT), H. Zhu (UT Austin), and G. B. Giannakis submitted. The book chapter offers a contemporary view of state estimation for modern autonomous energy grids.

  7. Paper “Solving Large-scale Random Systems of Quadratic Equations via Stochastic Truncated Amplitude Flow” accepted to the IEEE Transactions on Signal Processing. Matlab codes available here.

  8. Paper “Solving Random Systems of Quadratic Equations via Truncated Generalized Gradient Flow” accepted to NIPS’2016, which is to be held in Barcelona, Spain. The proposed algorithm benchmarks the performance of solving generalized phase retrieval under Gaussian random measurements or coded diffraction patterns. A full version along with Matlab implementations is available at here.