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, 6： 7515-7525，2018.
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 Systems，In 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. 7： 64533-64544, 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.