Yutao Tang


Yutao Tang ( 唐于涛 )
Associate Professor, Ph.D.
School of Artificial Intelligence
Beijing University of Posts and Telecommunications

Room 307, Innovation Building
No.10, Xitucheng Road, Beijing, China
Email: yttang@bupt.edu.cn
Mobile: +(86) 152-1098-2909
Official page: http://teacher.bupt.edu.cn/yttang

Research Interests

Nonlinear Control;  Distributed Optimization;  Mobile Robotics;  Machine Learning

Recent News

  • Journal paper co-authored with P. Yi, Y. Zhang, and D. Liu on Nash equilibrium seeking accepted by Autonomous Intelligent Systems, April 05, 2022: Nash equilibrium seeking over directed graphs.

  • Invited session on “Cooperative Control and Optimization with Uncertainties” and a conference paper accepted at the 41st Chinese Control Conference (CCC), Hefei, July, 2022: Solving linear equations with disturbance rejection.

  • Conference paper on distributed Nash equilibrium seeking accepted at the 13th Asian Control Conference (ASCC), Jeju Island, May, 2022: Distributed Nash equilibrium seeking algorithms for uncertain linear multi-agent systems.

  • Journal paper co-authored with K. Zhu accepted by Journal of Systems Science and Complexity, January 26, 2022: Primal-dual varepsilon-subgradient method for distributed optimization.

  • Journal paper co-authored with K. Zhu accepted by International Journal of Robust and Nonlinear Control, Novemeber 18, 2021: Optimal consensus for uncertain high-order multi-agent systems by output feedback.

  • Invited session on “Nonlinear Control and Optimization” and two conference papers accepted at the 40th Chinese Control Conference (CCC), Shanghai, July, 2021: Optimal consensus with inexact first-order information and Distributed optimization for high-order multi-agent systems via event-triggered control.

  • Conference paper on deep learning approach for ECG classification accepted at the 33rd Chinese Control and Decision Conference (CCDC), Kunming, May, 2021: Modified LSTM-CNN model for arrhythmia classification with mixed handcrafted features.