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• Chemical Process Optimization
• Chemical Process Analysis
• Chemical Process Design
• +3 more

Hua ZHOU serves as an Associate Professor in the Department of Chemical Engineering and Bioengineering at Xiamen University's College of Chemistry and Chemical Engineering, a position held since 2014 after progressing from Assistant Professor (2009-2014). His academic foundation includes a Bachelor's from the University of Petroleum (1992-1996), Master's from Xiamen University (2000-2003), and Ph.D. from South China University of Technology (2005-2008), with interim industry experience at Xiamen Haitong Automation Co., Ltd. (2003-2005). His educational journey is detailed as follows: Bachelor's Degree (1992-1996): Department of Refining and Applied Chemistry, University of Petroleum Master's Degree (2000-2003): Department of Chemical Engineering, Xiamen University Doctorate (2005-2008): School of Chemistry and Chemical Engineering, South China University of Technology Research expertise centers on chemical process optimization, analysis, design, and synthesis with specialized focus on industrial gas separation and purification . His work bridges theoretical modeling and industrial applications, emphasizing energy-efficient solutions for complex chemical systems through advanced simulation techniques and thermo-economic analysis. Publication trends (2008-2018) reveal concentrated contributions in gasification, hydrocracking, and electrocatalysis, with 13 articles in premier journals like Industrial & Engineering Chemistry Research and Energy . His research consistently integrates dynamic modeling, process optimization, and sustainability metrics, demonstrating expertise in translating theoretical frameworks to industrial-scale challenges. No scientific awards are documented in the provided materials. While specific advising records or grant details remain unreported, his Associate Professor role implies graduate student supervision and research funding activities within chemical engineering domains. No laboratory facilities or research teams under his direct leadership are specified in the available documentation.

• Robotics
• Mechanical Engineering
• Rehabilitation Engineering
• +3 more

Yixuan Guo is a Lecturer at the Department of Mechanical and Energy Engineering, Southern University of Science and Technology (SUSTech). With expertise in robotics and precision manufacturing, her research focuses include powered prosthetics , surgical robotics , and collaborative robotic arms . Prior to her current role, she held postdoctoral and lecturer positions at SUSTech and Wuhan University of Science and Technology. Ph.D. in Mechanical Engineering, Huazhong University of Science and Technology (2021) B.S. in Mechanical Engineering, Zhengzhou University (2016) Her research integrates advanced calibration techniques with robotics to enhance industrial applications, yielding over 10 SCI publications and 10 patents. Key projects include work on kinematic parameter calibration for industrial robots and error measurement systems in five-axis machine tools. Recent publications highlight her contributions to R-test based calibration , laser sensor integration , and multi-identification space methodologies in robotics. She has secured funding from the National Natural Science Foundation, Guangdong Basic Research Foundation, and Shenzhen Science and Technology Program. Outstanding Postdoctoral Fellow, SUSTech President (2023) Hubei Province Science and Technology Progress Third Prize (2024) Good Design Silver Award, Chinese Society of Mechanical Engineers (2024) Guo's work bridges robotics, mechanical engineering, and biomedical applications, with significant impacts on both academic research and industry practices.

• Complex intermittent process modeling
• Advanced process control
• Iterative learning control
• +4 more

Jia SHI is an Associate Professor in the Department of Chemical Engineering and Biological Engineering at Xiamen University's School of Chemistry and Chemical Engineering. With a background in Control Science and Engineering, they have contributed to advanced process control techniques for batch processes over their academic career. Education: Bachelor's (Control Science, Xiamen University, 1994), Master's (Operations Research and Cybernetics, Xiamen University, 1997), Doctorate (Control Science and Engineering, Zhejiang University, 2006) Academic Career: Lecturer at Xiamen University's School of Information Science and Technology (1997-2007), Associate Professor since 2008 Their research focuses on complex intermittent process modeling and advanced process control techniques , particularly iterative learning control (ILC) and model predictive control (MPC). These methods address challenges in batch process systems through robust, adaptive, and intelligent control strategies. Selected recent publications demonstrate expertise in 2D modeling approaches for control systems, fault-tolerant control, and integrated feedback mechanisms. Key trends include application of mathematical optimization techniques to industrial chemical processes and development of robust algorithms for process reliability. As an active researcher, they have collaborated with institutions like Hong Kong University of Science and Technology (Research Assistant, 2003-2006) and maintain a strong publication record in top-tier journals such as AIChE Journal and Industrial & Engineering Chemistry Research.

• Robotics
• Robot Audition
• Optimal Filtering and Estimation
• +4 more

He Kong is an Associate Professor at Southern University of Science and Technology (SUSTech), affiliated with the School of Automation and Intelligent Manufacturing, where he also serves as Deputy Director of the SUSTech Institute of Robotics. Previously, he was an Assistant Professor in the Department of Mechanical and Energy Engineering at SUSTech from January to May 2022. Prior to joining SUSTech, he was a Research Fellow at the Australian Centre for Field Robotics, University of Sydney (2016-2021), and at Cranfield University's Advanced Vehicle Engineering Centre (2015-2016). He received his Ph.D. in Electrical Engineering from the University of Newcastle, Australia (2014), M.E. in Control Science and Engineering from Harbin Institute of Technology (2010), and B.E. in Electrical Engineering and Automation from China University of Mining and Technology (2004). His research focuses on robotic intelligent perception and decision making, robot audition, optimal filtering and estimation, and advanced control methods. Specifically, he works on active multi-mode perception, parameter calibration of robot audition systems, optimal filtering under unknown inputs, and fully actuated system approaches. His work has significant applications in precision agriculture, environmental monitoring, and robotic inspection of hazardous industries such as chemical and mining operations. His recent publications reveal a strong emphasis on multi-modal perception systems, particularly combining visual and auditory sensing for robotic applications. His research shows a progression from theoretical control methods toward practical implementations in field robotics, with increasing focus on real-world applications in agriculture and hazardous environments. Finalist for Youth Author Prize, IFAC Workshop on Robot Control (2019) Fifth China Robotics Academic Annual Conference Best Poster Award (2024) 14th International Conference on Indoor Positioning and Indoor Navigation Best Paper Award (2024) The Equity Scholarship, Council of International Students Australia (2011) Outstanding Postgraduate Students Award, Harbin Institute of Technology (2010) Professor Kong actively supervises numerous PhD and Master's students and has established a productive research group focused on active intelligent systems. His laboratory is equipped with advanced facilities including over 30 motion capture systems, Unitree humanoid robots, robot dogs, wheeled mobile robots, and custom-developed platforms like Cubli and acoustic perception systems. He serves on editorial boards for several prestigious journals including IEEE Robotics and Automation Letters and IEEE Sensors Letters, and has been an Associate Editor for major robotics conferences such as IEEE ICRA and IEEE/RSJ IROS.

Derong LiuView profile

Professor

• Adaptive Dynamic Programming
• Reinforcement Learning
• Intelligent Control
• +5 more

Derong Liu is a Chair Professor at Southern University of Science and Technology (SUSTech) in Shenzhen, China, holding dual appointments as Full Professor of Electrical and Computer Engineering and Computer Science at the University of Illinois at Chicago. He is a distinguished scholar with multiple prestigious recognitions including Member of Academia Europaea, Fellow of IEEE, Fellow of International Neural Network Society, and Fellow of International Association for Pattern Recognition. His academic journey spans multiple institutions across China and the United States, with significant contributions to control theory and artificial intelligence. Ph.D. in Electrical Engineering from University of Notre Dame (1994) M.Sc. in Automatic Control Theory from Chinese Academy of Sciences (1987) B.Sc. in Mechanical Engineering from East China Institute of Technology (1982) Liu's research focuses on Adaptive Dynamic Programming and Reinforcement Learning, Intelligent Control and Information Processing, Modeling and Control of Complex Industrial Processes, Neural Networks and Computational Intelligence, and Smart Grid technologies. His work bridges theoretical foundations with practical applications in industrial control systems, particularly in automotive engine control and energy management. He has pioneered significant methodologies in neural network design and adaptive control systems that have become foundational in the field. His publication record demonstrates a consistent trajectory of high-impact research, with recent articles focusing on event-triggered control systems, neural architecture search, fault tolerant control, and multi-agent game theory applications. The research spans both theoretical advances in control algorithms and practical implementations in complex industrial systems, showing a clear evolution from foundational neural network research to sophisticated adaptive control frameworks. Member, Academia Europaea (2021) IEEE Computational Intelligence Society Neural Network Pioneer Award (2022) Dennis Gabor Award from International Neural Network Society (2018) Highly Cited Researcher by Clarivate (2017-present) Editor-in-Chief of Artificial Intelligence Review (2014-present) Liu has mentored numerous students and researchers throughout his career, serving as Editor-in-Chief for major journals and leading significant research initiatives. His work has been supported by multiple grants from the National Science Foundation of the United States and the National Natural Science Foundation of China. His research group continues to push boundaries in adaptive control systems and neural network applications. Currently, Liu leads a research group at SUSTech focusing on intelligent control systems, with active projects in adaptive dynamic programming, reinforcement learning applications, and smart grid technologies. His laboratory serves as a hub for interdisciplinary research connecting theoretical control frameworks with practical industrial implementations.