Bingchang Wang | Control Theory | Outstanding Scientist Award

Posted on by sciencefather

Prof. Bingchang Wang | Control Theory | Outstanding Scientist Award

Professor at Shandong University, China.

Prof. Bingchang Wang is a distinguished researcher in control theory, mean field games, and multi-agent systems.  he is a Professor at Shandong University, China. His expertise spans reinforcement learning, Markov processes, and event-based control. He has held research positions in Canada, Australia, and Hong Kong, working with leading IEEE Fellows. Prof. Wang is a Senior Member of IEEE and serves as an Associate Editor for Mathematical Problems in Engineering. He has received prestigious awards, including the 2021 Best Theory Paper Award at the China Automation Congress. His research contributes significantly to intelligent control and optimization, with numerous publications in top-tier journals like IEEE Transactions on Automatic Control and Automatica.

professional profiles📖

Scopus Profile

Education 🎓

Prof. Wang pursued his undergraduate studies in Mathematics and Applied Mathematics at Ludong University, China, earning his B.Sc. degree in 2005. He then completed his M.Sc. in Probability and Statistics at Central South University, China (2005-2008), under the supervision of Prof. Zhen-Ting Hou. His master’s thesis focused on the local asymptotics of Markov modulated random walks with heavy-tailed increments and their applications in complex systems.

In 2008, he commenced his Ph.D. in System Modeling and Control at the Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China, under the guidance of Prof. Ji-Feng Zhang. His Ph.D. thesis, titled “Mean Field Games and Control of Multi-Agent Systems in a Markov Environment”, laid the foundation for his future research in distributed control and large-scale optimization. Throughout his academic journey, Prof. Wang developed a strong foundation in mathematical modeling, probability theory, and stochastic control, which continues to influence his innovative work in multi-agent systems and reinforcement learning.

work Experience💼

Prof. Wang has extensive international research experience, working with renowned scholars in control theory and automation. He began his postdoctoral research in 2011 at the University of Alberta, Canada, under the mentorship of Prof. Tongwen Chen (IEEE Fellow). In 2012, he moved to Australia as a Research Academic at the University of Newcastle, collaborating with Prof. Minyue Fu (IEEE Fellow) on advanced topics in stochastic control and optimization.

Returning to China in 2013, he joined Shandong University as an Associate Professor, where he played a crucial role in advancing research in multi-agent systems and reinforcement learning. During this period, he also held visiting research positions at Carleton University, Canada (2014-2015), working with Prof. Minyi Huang, and at The Hong Kong Polytechnic University (2016-2017), where he collaborated with Prof. Jianhui Huang on stochastic control problems in finance and engineering.

Since September 2021, Prof. Wang has been a Full Professor at Shandong University, China, leading innovative research projects in mean field games, event-based control, and AI-driven decision-making. He is an active IEEE Senior Member, a Program Committee Member for several top conferences, and an Associate Editor for Mathematical Problems in Engineering.

Research Focus

Prof. Wang’s research centers on mean field games and control, reinforcement learning, multi-agent systems, and Markov processes. His work addresses critical challenges in large-scale system optimization, intelligent automation, and distributed decision-making. By integrating game theory, stochastic control, and AI-driven strategies, he develops novel frameworks for robotic automation, smart production systems, and financial engineering.

His contributions to event-based control and reinforcement learning enhance adaptive decision-making in uncertain environments, optimizing processes in autonomous systems, industrial control, and AI-driven policy-making. Prof. Wang’s innovative models in Markov processes and stochastic control have significant applications in economics, energy systems, and networked control systems, advancing the field of intelligent automation.

Awards & Honors🏆 

Prof. Wang’s contributions to control theory and system optimization have been recognized through numerous prestigious awards. In 2021, he received the Best Theory Paper Award at the China Automation Congress, highlighting his pioneering work in mean field social systems and large-scale optimization. He was also honored with the Best Poster Paper Award at the Chinese Control Conference in 2020 and was a Finalist for the Guanzhaozhi Prize in 2019, a prestigious award recognizing outstanding young researchers in control systems engineering.

In 2018, Prof. Wang was awarded the IEEE CSS Beijing Chapter Youth Author Prize, acknowledging his exceptional contributions to stochastic control and reinforcement learning. His early career achievements were further recognized in 2017 when he was nominated for the Youth Author Prize at the Asian Control Conference. These accolades underscore his global influence in intelligent control and mathematical optimization.

Conclusion✅

Dr. Bing-Chang Wang is an outstanding candidate for the Research for Outstanding Scientist Award. His deep expertise in control systems, mean field games, and reinforcement learning, coupled with his strong publication record, prestigious awards, and international experience, make him highly deserving of this recognition. Addressing interdisciplinary research opportunities, industry collaboration, and public outreach could further elevate his scientific impact.

Publications to Noted 📚

Mean field LQG social optimization: A reinforcement learning approach

Authors: Zhenhui Xu, Bingchang Wang, Tielong Shen

Year: 2025

Citations: 0

Journal: Automatica

An Online Q-Learning Method for Linear-Quadratic Nonzero-Sum Stochastic Differential Games with Completely Unknown Dynamics

Authors: Baoqiang Zhang, Bingchang Wang, Ying Cao

Year: 2024

Citations: 0

Journal: Journal of Systems Science and Complexity

Mean Field Social Control for Production Output Adjustment with Noisy Sticky Prices

Authors: Bingchang Wang, Minyi Huang

Year: 2024

Citations: 3

Journal: Dynamic Games and Applications

An online value iteration method for linear-quadratic mean field social control with unknown dynamics

Authors: Bingchang Wang, Shumei Li, Ying Cao

Year: [No source information available]

Citations: 4

Discrete-time indefinite linear-quadratic mean field games and control: The finite-population case

Authors: Yong Liang, Bingchang Wang, Huanshui Zhang

Year: 2024

Citations: 2

Journal: Automatica

Differentially Private Consensus for Second-Order Multiagent Systems With Quantized Communication

Authors: Wenjun Zhang, Bingchang Wang, Yong Liang

Year: 2024

Citations: 3

Journal: IEEE Transactions on Neural Networks and Learning Systems

Discrete-time indefinite mean field linear quadratic games with multiplicative noise

Authors: Xiao Ma, Bingchang Wang, Huanshui Zhang

Year: 2024

Citations: 1

Journal: Asian Journal of Control

Kil soo Lee | Intelligent Control | Best Researcher Award

Posted on by sciencefather

Dr. Kil soo Lee | Intelligent Control | Best Researcher Award

Principal Researcher at Korea Construction Equipment Technology Institute/Automation System Design Research Group , South Korea

Dr. Kilsoo Lee is a distinguished researcher in mechanical engineering, currently serving as the Group Leader and Principal Researcher at the Korea Construction Equipment Technology Institute (KOCETI). His expertise spans intelligent construction machinery, robotics, and autonomous vehicle technology. Dr. Lee has played a pivotal role in numerous research projects, leading innovations in electric and construction machinery. He has also been a vital contributor to international conferences and professional journals. A dedicated professional, he is a member of the Korean Society of Mechanical Engineers, the Institute of Control, Robotics and Systems, and the Korean Institute of Navigation and Port Research. He has received multiple accolades for his contributions, including awards at autonomous vehicle competitions. His research aims to enhance intelligent construction equipment, furthering advancements in automation and safety technologies.

professional profiles📖

Scopus Profile

Education 🎓

Dr. Kilsoo Lee obtained his PhD in Engineering from Pusan National University, where he specialized in mechanical engineering and automation systems. His academic journey began with undergraduate and master’s degrees in mechanical engineering, during which he developed a strong foundation in robotics and control systems. He later worked as a junior researcher at the Research Institute of Mechanical Technology (RIMT) and the Mechanical, Architectural, and Traffic Engineering Research Information Center (MATERIC). His academic training has equipped him with expertise in intelligent machinery and vehicle automation. Through his doctoral studies, Dr. Lee focused on the integration of advanced control mechanisms, laying the groundwork for his future contributions in autonomous and intelligent construction equipment. His educational background has been instrumental in shaping his career as a leader in automation research and system design.

work Experience💼

Dr. Lee has accumulated extensive experience in engineering research and leadership. Since 2014, he has been leading research at KOCETI’s Automation System Design Research Group, focusing on construction and agricultural machinery innovations. Prior to this, he served as a postdoctoral researcher at Pusan National University (2013–2014), where he advanced research on autonomous vehicle technologies. From 2010 to 2013, he was the CEO and CTO of e-Metro Technology, Inc., where he spearheaded projects in intelligent transportation systems. His involvement in major research projects includes developing machine control kits for excavators and autonomous control mechanisms for construction machinery. Dr. Lee’s expertise has also been recognized in the defense sector, where he has contributed to unmanned vehicle technology. His career reflects a commitment to advancing intelligent and automated engineering solutions.

Awards and Honors 

Dr. Kilsoo Lee has received multiple awards recognizing his excellence in engineering research and technological innovation. Notably, he led Pusan National University’s team at the 1st and 2nd Autonomous Vehicle Competitions, securing the Challenge Award for successfully completing all courses. His work in developing intelligent construction machinery has earned him recognition in industry and academia. He has also been honored for his contributions to automation and robotics research through awards from professional organizations, including the Korean Society of Mechanical Engineers. His patents and research contributions have been acknowledged as significant advancements in safety and control mechanisms for machinery. Additionally, his work in autonomous vehicle technology has been cited in international conferences, further solidifying his reputation as a leader in the field. His achievements continue to drive advancements in automation and intelligent machinery.

Research Focus

Dr. Lee’s research focuses on the development of intelligent control systems for construction machinery, electric vehicles, and autonomous systems. His projects aim to enhance efficiency, safety, and automation in industrial machinery. A key area of his research is the application of artificial intelligence in machine control, particularly for excavators and autonomous vehicles. He has contributed to the design of robust lateral controllers and functional safety systems for unmanned vehicles. His work also extends to the integration of LiDAR-based navigation for transport robots, improving object detection and autonomous movement capabilities. Through his research, Dr. Lee aims to advance automation technologies that optimize machinery performance while ensuring operational safety. His efforts in developing novel control methodologies contribute significantly to the evolving landscape of intelligent engineering solutions.

 

Conclusion✅

Dr. Kilsoo Lee is a highly qualified and impactful researcher with significant contributions to automation, intelligent construction systems, and control engineering. His leadership, strong publication record, patents, and national project success make him a strong contender for the Best Researcher Award. By expanding international collaborations, industry partnerships, and citation visibility, he can further solidify his global reputation in the field.

 

📚Publications to Noted

 

Study on the Near-Distance Object-Following Performance of a 4WD Crop Transport Robot: Application of 2D LiDAR and Particle Filter

Authors: Eun-Seong Pak, Byeong-Hun Kim, Kil-Soo Lee, Yong-Chul Cha, Hwa-Young Kim

Year: 2025

“On the Synthesis of an Underwater Ship Hull Cleaning Robot System”

Authors: Man Hyung Lee, Kil Soo Lee, Won Chul Park, Seok Hee Lee, Sinpyo Hong, Hyung Gyu Park, Jae Won Choi, Ho Hwan Chun

Year: 2012

“Lateral Controller Design for an Unmanned Vehicle via Kalman Filtering”

Authors: Man Hyung Lee, Kil Soo Lee, Hyung Gyu Park, Young Chul Cha, Dong Jin Kim, Byung Il Kim, Sinpyo Hong, Ho Hwan Chun

Year: 2012

“Implementation of Electric Power Assisted Steering System via Hardware-In-Loop-Simulation System”

Authors: Kil Soo Lee, Hyung Gyu Park, Myoung Kook Kim, Jung Hyen Park, Man Hyung Lee

Year: 2011

“4WS Unmanned Vehicle Lateral Control Using PUS and Gyro Coupled by Kalman Filtering”

Authors: Kil Soo Lee, Hyung Gyu Park, Man Hyung Lee

Year: 2011

“Robust Lateral Controller for an Unmanned Vehicle via a System Identification Method”

Authors: Man Hyung Lee, Kil Soo Lee, Hyung Gyu Park, Ho Hwan Chun, Jae Heon Ryu

Year: 2010