Dr. Dazi Li

Time:2023-06-05Views:14

Dr. Dazi Li

Professor, PhD Supervisor,

Associate Dean of College of Information Science and Technology

Email: lidz@mail.buct.edu.cn


Background                                                                  

Professor Dazi Li received her B.Sc. and M.Sc. degrees from the Department of Automation, Beijing University of Chemical Technology (BUCT) in 1988 and 1995. She worked as a lecturer at BUCT in 1995. She studied abroad in Japan in 2000 and received Ph.D. degree in Electrical and Electronic Systems from the Department of Informatics, Kyushu University in 2004.


Areas of Research of Expertise

  • Machine Learning and Artificial Intelligence

  • Advanced Control

  • Complex System Modeling and Optimization

Memberships

  • Member of Technical Committee on Adaptive Dynamic Programming and Reinforcement Learning, Chinese Association of Automation

  • Member of Technical Committee on Data-Driven Control, Learning and Optimization, Chinese Association of Automation

  • Member of Technical Committee on Energy Internet, Chinese Association of Automation

Teaching                                          

Undergraduate Teaching

  • Process Control Engineering

  • Artificial Intelligence & Automation

  • Introduction to Automation Science

Postgraduate Teaching

  • Theory of Pattern Recognition and its Application

Research                                          

Funded Research Projects

The National Natural Science Foundation of China:

  • Research on Optimization of Complex Process Safety Policy Based on Bidirectional Reinforcement Learning

  • Research on data-driven reinforcement learning control for complex dynamic systems

The Beijing Natural Science Foundation:

  • Research on Decision Control of High-Dimensional Partially Observable Processes Based on Deep Reinforcement Learning

Others:

  • High-efficiency sedimentation tank precise dosing system

Main Achievements & Awards

  • The Beijing Teaching Master Award

  • Beijing Science and Technology Award, 3rd grade, the key technology and application of process monitoring and controller optimization of refining and chemical equipment

  • China Petroleum and Chemical Automation Industry Science and Technology Invention Award, 1st grade, Key Technology and Application of Full-process Automatic Control of Refining and Chemical Equipment

Publications                                       

  • Tianheng Song, Dazi Li*, Liulin Cao, Kotaro Hirasawa, Kernel-based Least Squares Temporal Difference with Gradient Correction, IEEE Transactions on Neural Networks and Learning Systems, 2016, 27(4)771- 782.

  • Luntong Li, Dazi Li*, Tianheng Song, Xin Xu, Actor-Critic Learning Control based on L2-Regularized Temporal-difference Prediction with Gradient Correction, IEEE Transactions on Neural Networks and Learning Systems, 29(12): 5899-5909, December 2018  

  • Dazi Li*, Yuting Wang, Tianheng Song, Qibing Jin, An Adaptive Policy Evaluation Network Based on Recursive Least Squares Temporal Difference with Gradient Correction, IEEE Access, 67515-75252018.  

  • Dazi Li*, Ze Wang, Wenlong Yu, Quanshan Li, Qibing Jin, Application of LADRC with stability region for a hydrotreating back-flushing process, Control Engineering Practice, 79(2018), 185-194, 2018.

  • Dazi Li*, Xiangyi Tian, Qibing Jin and Kotaro Hirasawa, Adaptive fractional-order total variation image restoration with split Bregman iteration, ISA Transactions, 82(2018): 210-222.  

  • Tianheng Song, Dazi Li*, Weiming Yang, Kotaro Hirasawa, Recursive Least-Squares Temporal Difference with Gradient Corretion, IEEE Transactions on Cybernetics, 2019, Early Access Article.  2019 Mar 19. Doi:10.1109/TCYB.2019.2902342.

  • Luntong Li, Dazi Li*, Tianheng Song, Xin Xu, Actor-Critic Learning Control with Regularization and Feature Selection in Policy Gradient Estimation, IEEE Transactions on Neural Networks and Learning SystemsIn press.

  • Tianheng Song, Dazi, Li*, Qibing Jin, Kotaro Hirasawa, Sparse Proximal Reinforcement Learning via Nested Optimization, IEEE Transactions on Systems, Man and Cybernetics: Systems, doi:10.1109/TSMC.2018.2865505.

  • Dazi Li*, Liming Wei, Tianheng Song, and Qibing Jin, Study on Asymptotic Stability of Fractional Singular System with Time Delay, International Journal of Control, Automation and Systems, 18(4), 2020, 1002-1011.

  • Tianheng Song, Dazi Li*, Zhiyin Liu, and Weiming Yang, Online ADMM-Based Extreme Learning Machine for Sparse Supervised Learning, IEEE Access. 764533-64544, 2019

  • Dazi Li*, Fuqiang Zhu, Xiao Wang, Qibing Jin, Multi-objective reinforcement learning for fed-batch fermentation process control, Journal of Process Control, 2022, 115: 89-99.

  • Dazi Li*, Jianxun Liu, Jun Liu. NNI‐SMOTE‐XGBoost: A Novel Small Sample Analysis Method for Properties Prediction of Polymer Materials, Macromolecular Theory and Simulations, 2021, 30(5): 2100010.

  • Li Song, Dazi Li*, Xin Xu. Sparse online maximum entropy inverse reinforcement learning via proximal optimization and truncated gradient, Knowledge-Based Systems, 2022, 252: 109443.

  • Tianheng Song, Dazi Li*, Xin Xu. Online Sparse Temporal Difference Learning Based on Nested Optimization and Regularized Dual Averaging, IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2021, 52(4): 2042-2052.

  • Li Song, Dazi Li*, Xiao Wang, et al. AdaBoost maximum entropy deep inverse reinforcement learning with truncated gradient, Information Sciences, 2022, 602: 328-350.

  • Dazi Li*, Wenjie Yu, Kunfeng Wang, Daozhong Jiang, Qibing Jin, Speckle noise removal based on structural convolutional neural networks with feature fusion for medical image, Signal Processing: Image Communication, 2021, 99: 116500.