Prof. Guoliang Wang | Control Science and Engineering | Best Researcher Award

 Guoliang Wang is a Professor at the Department of Automation, School of Information and Control Engineering, Liaoning Petrochemical University. With extensive expertise in control theory and automation, he has made significant contributions to Markov jump systems, stochastic system theory, and big data-driven fault detection. He has published 86 journal articles indexed in SCI and Scopus, authored books, and holds 9 patents. As a postdoctoral researcher at Nanjing University of Science and Technology (2011-2016), he furthered his research in control engineering. His professional memberships include the Chinese Association of Automation and the Chinese Mathematical Society. He has received the Liaoning Province Natural Science Academic Achievement Second Prize for his contributions. His innovative work in optimization, reinforcement learning, and system modeling continues to impact academia and industry.

Profile

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Education

Guoliang Wang earned his Ph.D. in Control Theory and Control Engineering from Northeastern University (2007-2010). Prior to that, he completed his Master’s degree in Operations Research and Control Theory at the School of Science, Northeastern University (2004-2007). His academic foundation is built on advanced mathematical modeling, stochastic systems, and automation, equipping him with expertise in complex system analysis. His research has consistently focused on optimizing control mechanisms and enhancing stability in dynamic environments. As a Postdoctoral Researcher at Nanjing University of Science and Technology (2011-2016), he deepened his understanding of control theory, reinforcement learning, and system dynamics. His education has been pivotal in developing innovative methodologies for automation, fault detection, and big data-driven decision-making.

Experience

Since March 2010, Guoliang Wang has been a Professor at Liaoning Petrochemical University, specializing in automation and control engineering. He served as Associate Dean of the Department of Automation (2013-2014), leading academic and research initiatives. His postdoctoral research at Nanjing University of Science and Technology (2011-2016) explored stochastic system applications and control theory advancements. Over the years, he has led multiple research projects, consulted on industrial automation solutions, and contributed to major technological advancements. His work has resulted in 86 peer-reviewed journal publications, 9 patents, and significant contributions to adaptive dynamic programming. As a member of various professional associations, he actively collaborates with international researchers and institutions. His expertise spans Markov jump systems, stochastic modeling, fault detection, and AI-driven automation strategies

Research Interests

Guoliang Wang’s research spans modeling and control of Markov jump systems, stochastic system applications, and AI-driven automation. His work in fault detection, diagnosis, and big data-driven prediction has led to practical advancements in system optimization. He has proposed novel stabilizing controllers, developed reinforcement learning-based optimization models, and improved system performance through convex optimization techniques. His expertise in stochastic control extends to image processing, predictive analytics, and adaptive dynamic programming. His research contributions have significantly enhanced system stability and reduced computational complexity in industrial automation. Through collaborations with global researchers, he continues to push the boundaries of automation, AI, and smart control systems. His work integrates theoretical insights with real-world applications, ensuring a lasting impact on engineering and technology.

Awards & Recognitions

Guoliang Wang has been recognized for his outstanding contributions to automation and control engineering. He received the prestigious Liaoning Province Natural Science Academic Achievement Second Prize for his groundbreaking research. His achievements include being a member of elite research committees such as the Youth Committee of the Chinese Association of Automation and the Adaptive Dynamic Programming and Reinforcement Learning Technical Committee. He has been an invited speaker at international conferences and has received commendations for his work in optimizing stochastic system control. His research impact is further reflected in his editorial board membership at the Journal of Liaoning Petrochemical University. With numerous patents, consultancy projects, and high-impact research, he continues to receive nominations and accolades in automation, AI, and control system optimization

Publications