Track 3. Learning and Artificial Intelligence for Robotics and Control
Chair:
Prof. Jing Na, Kunming University of Science and Technology, China 那靖教授（昆明理工大学）
Co-Chair:
Assoc. Prof. Faxiang Zhang, Kunming University of Science and Technology, China 张发祥副教授（昆明理工大学）
As intelligent systems continue to evolve toward higher levels of autonomy and adaptability, the integration of robot learning and artificial intelligence has become a driving force in modern robotics and control engineering. This track explores the synergy between data-driven methodologies and physical systems, emphasizing how learning-based approaches can enhance perception, decision-making, and control in complex and uncertain environments. By bridging advances in machine learning with real-world robotic applications, it aims to foster innovative solutions that enable robots to learn from data, interact with dynamic surroundings, and continuously improve performance. Particular attention is given to scalable, robust, and interpretable AI techniques that support reliable deployment in safety-critical and real-time systems.
Potential topics of interest include but are not limited to:
● Robot Learning and Learning-based Control
● Reinforcement Learning and Adaptive Decision-Making
● Machine Learning for Robotics and Autonomous Systems
● Imitation Learning and Human-guided Learning
● Data-driven Modeling and Intelligent Systems
● AI for Planning, Control, and Optimization
● Multi-agent Learning and Cooperative Intelligence
● Trustworthy, Safe, and Interpretable AI for Robotics
Submit:
http://www.easychair.org/conferences/?conf=irce2026
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Prof. Jing Na, Kunming University of Science and Technology, China 那靖教授（昆明理工大学）
Biography: Jing Na is the Executive Vice
Dean, Professor, and Ph.D. supervisor at the School of
Mechanical and Electrical Engineering, Kunming University of
Science and Technology. He is a "National High-level Talent"
Distinguished Professor, recipient of the National Excellent
Young Scientist Fund, and a Marie Curie Fellow of the
European Union. He obtained his Bachelor's and Ph.D. degrees
in Engineering from Beijing Institute of Technology in 2004
and 2010, respectively. He conducted postdoctoral research
at ITER Organization in France and the University of Bristol
in the UK. Since joining Kunming University of Science and
Technology in 2010, he was promoted to professor in 2013.
His research interests include mechatronic system modeling,
intelligent control, adaptive parameter estimation, and
nonlinear control. He has led several national, EU, and
provincial research projects, published 2 books and over 100
papers. He has received numerous awards, including the Hu
Yingdong Young Scientist Award and Yunnan Province Youth
Science and Technology Award, and has held key roles in
several international conferences, such as ICMIC 2017
Program Committee Chair and DDCLS 2019 Co-chair.
个人简介:
那靖，现为昆明理工大学机电工程学院常务副院长，教授、博士生导师，国家高层次人才”特聘教授项目入选者、国家基金委优秀青年基金获得者，欧盟“玛丽∙居里学者”，云南省中青年学术技术带头人。2004年和2010年于北京理工大学分别获得工学学士和工学博士学位。2011年至2012年于法国ITER
Organization从事博士后研究，2015年至2016年于英国布里斯托大学工作。2010年起加入昆明理工大学机电工程学院，2013年破格晋升教授。主要研究方向为机电系统建模及智能控制、自适应参数估计、非线性控制及应用。主持国家自然科学基金6项，欧盟资助项目及省部级资助项目10余项。在Elsevier出版英文专著2部，发表论文100余篇。获霍英东青年科学奖、云南省青年科技奖，自动化学报首届钱学森论文奖、云南省自然科学一等奖等奖励，并获中国青年五四奖章、全国优秀教师、云南省先进工作者等荣誉称号。现为IEEE
TIE,
Neurocomputing等三个国际期刊编委，入选科睿唯安全球高被引学者、爱思唯尔中国高被引学者榜单。担任ICMIC
2017程序委员会主席、DDCLS 2019会议共同主席、CCDC 2021组委会副主席等。
Assoc. Prof. Faxiang Zhang, Kunming University of Science and Technology, China 张发祥副教授（昆明理工大学）
Biography: Zhang Faxiang is an Associate
Professor and Master’s Supervisor, and a young talent under
Yunnan Province’s “Xing Dian Talent Support Program.” He
received his Ph.D. in Engineering from Southeast University
in 2022. He is currently working at the School of Mechanical
and Electrical Engineering, Kunming University of Science
and Technology. From 2025 to 2026, he is a postdoctoral
researcher at the University of Macau.
His research interests include fuzzy/neural network control,
nonlinear adaptive control, and their applications. He has
led one National Natural Science Foundation of China (NSFC)
Youth Program and three provincial/ministerial-level
projects, and participated in several national key research
projects. He has published over 20 SCI-indexed journal
papers and received the Best Conference Paper Award at ICBSR
2025. He serves as a committee member of DDCS and as a
session chair/co-chair for multiple international
conferences.
个人简介:
张发祥，副教授，硕士生导师，云南省“兴滇英才支持计划“青年人才。2022年于东南大学获得工学博士学位。2022年起于昆明理工大学机电工程学院工作，其间2025年至2026年于澳门大学从事博士后研究。主要研究方向为模糊/神经网络控制、非线性自适应控制及应用。主持国家自然科学基金青年项目1项、省部级项目3项，参与国家自然科学基金重点项目等4项。发表SCI期刊论文20余篇（其中IEEE
TFS、TNNLS、TC、TCNS等权威期刊论文10余篇），获2025
ICBSR“最佳会议论文奖”。担任DDCS专委会委员、DDCLS 2025专题主席、CCDC 2025 专题共同主席。