معرفی
Daniel Yuh Chao is a Professor in the Department of Management Information Systems at National Chengchi University's College of Commerce, specializing in Petri nets, discrete event systems, and flexible manufacturing systems control. His academic career at NCCU spans from Associate Professor (1994-1997) to full Professor (1997-present), with recognition as a Distinguished Professor in 2008.
- National Chengchi University, Department of Management Information Systems (1994-present)
- Ph.D. in EECS from University of California, Berkeley (1983-1987)
- M.S. in Electrical Engineering from University of California, Los Angeles (1980-1981)
- B.S. in Mechanical Engineering from National Taiwan University (1972-1976)
Professor Chao's research focuses on Petri net theory and applications, particularly in deadlock prevention and control of flexible manufacturing systems. His work has established significant theoretical foundations for siphon-based control, elementary siphon analysis, and maximally permissive controllers. He has developed innovative approaches for state enumeration, controller synthesis, and simplification of control structures without requiring full reachability analysis.
His publication record shows consistent high-impact research from 1986 through 2014, with over 80 journal and conference papers. The most recent works (2013-2014) demonstrate continued advancement in recursive state computation methods, closed-form controller solutions, and structural analysis of weakly dependent siphons, with applications to increasingly complex manufacturing systems.
- Distinguished Professor at National Chengchi University (2008)
Professor Chao has supervised numerous research projects on deadlock analysis and Petri net applications in manufacturing systems. His theoretical contributions have practical implications for industrial automation, particularly in developing efficient control strategies for complex resource-sharing systems. His research group has produced significant advancements in computational methods for Petri net analysis, reducing the complexity of controller synthesis while maintaining system liveness and performance.
His laboratory work focuses on applying Petri net theory to real-world manufacturing challenges, with particular emphasis on developing computationally efficient control algorithms that can scale to large industrial systems. Current research directions include extending control methodologies to more general Petri net structures and developing closed-form solutions for controller synthesis in infinitely large systems.
