Assistant professor in electrical and computer engineering appointed journal associate editor, publishes textbook
Published: Apr 11, 2024 10:15 AM
By Kat Bader
Bosen Lian, assistant professor in electrical and computer engineering, has been appointed associate editor for two leading Institute of Electrical and Electronics Engineers scholarly journals and already published his first textbook as lead author since joining the Auburn faculty last fall.
As associate editor for Transactions on Neural Networks and Learning Systems (TNNLS) and Transactions of the Institute of Measurement and Control (TIMC), Lian will support the editorial process and share responsibility for handling manuscripts, quality control and communication.
“Faculty members taking lead roles in academic and professional societies, including serving as editors of journals, can have several important benefits, including advancing research and scholarship, building networks and collaborations, professional development, recognition and visibility, contributing to the community,” he said.
The journals focus on different areas in engineering and technology.
TNNLS primarily focuses on research related to neural networks, machine learning and computational intelligence. The journal covers a wide range of topics, including neural network models and architectures, learning algorithms, computational neuroscience, pattern recognition, optimization techniques and applications of neural networks in various domains such as computer vision, natural language processing, robotics, and informatics.
TIMC, however, dives into research related to measurement, instrumentation, and control systems.
“TIMC caters to researchers, engineers and practitioners working in fields such as instrumentation and measurement, control engineering, automation, robotics and industrial process control.”
Lian’s textbook, “Integral and Inverse Reinforcement Learning for Optimal Control Systems and Games,” offers cutting-edge insights into integral reinforcement learning and inverse reinforcement learning for optimal control systems and games, presenting the disciplines in two parts.
One focus on integral reinforcement learning addresses the challenges posed by the continuous-time Hamiltonian equations in optimal control systems and games. The focus on inverse reinforcement learning introduces model-free capabilities to unravel the underlying performance functions that drive observed optimal behaviors in the realm of system and control theory, distinguishing it from existing model-based inverse optimal control approaches.
“The book is very suitable for students and researchers working on the use of artificial intelligence (AI) in control systems since it provides a mathematical basis in an area where ideas are often presented in an intuitive style,” Lian said. “Engineers wishing to use AI and machine learning methods in areas such as robotics, automotive applications, aircraft systems, power systems and chemical processes can be comforted that the approach described is relatively simple given the challenge and complexity of the problem.”
Lian’s second textbook is forthcoming.
Media Contact: , jem0040@auburn.edu, 334.844.3447
Bosen Lian joined the Auburn University faculty in the Fall 2023 semester.
