Dr. Xie is the Co-Founder of WIOMAX. He is a researcher and inventor focusing on creating smart and scalable optimization solutions for real-world applications towards achieving intelligent transportation, sustainable urban mobility, smart cities, with integration of cutting-edge technology in artificial intelligence (AI), optimization, data analytics, and the Internet of things (IoT).
He is a leading expert on creating smart and scalable modeling and optimization solutions for computationally hard and real-world problems, with his broad and deep academic and industrial experience, and his multidisciplinary background in very diverse fields including Electrical Engineering, Computer Science, and Transportation Science, etc.
He is the lead inventor of the smart and scalable urban traffic control system, which integrates artificial intelligence (AI) with transportation theory to reduce traffic congestion, with 25% travel time saved in the real-world traffic networks. The adaptable traffic signal system was listed as 25 Great Things about computer science at Carnegie Mellon. He has also worked as co-PI and key member for multiple traffic and transportation projects, in collaboration with federal and state DOT agencies and city officers and engineers, university researchers, and industrial partners.
He has created the Cooperative Group Optimization (CGO) system to provide a core framework for effectively building advanced optimization algorithms. He developed optimization algorithms to improve the records for the bounded gaps between primes, in collaboration with a team of top mathematicians in the Polymath8 project (featured on the cover of Notices of the AMS). Some of his algorithms, including DEPSO and Social Cognitive Optimization (SCO), were implemented in NLPSolver (Solver for Nonlinear Programming), an extension of Calc in Apache OpenOffice. His algorithms have also achieved state-of-the-art performance for various hard combinatorial problems, e.g., Traveling Salesman Problem (TSP), Graph Coloring (GCP), Quadratic Knapsack Problem (QKP), Flowshop Scheduling (FSP), and Quadratic Assignment Problem (QAP), etc. His software was the 2nd runner-up on solving a combinatorial problem using modern heuristic methods in an International Optimization Competition.
He also worked on other real-world applications. He was the key developer for the commercial expert system of Model Quality Assurance (MQA) tool, which has been widely adopted by leading companies. He was a main developer for the modeling and synthesis system on electronic design automation (EDA) with Motorola DigitalDNA Lab. He also designed and developed the software for agent-mediated supply chain integration.
He serves as an Editorial Board member of Web Intelligence and International Journal of Applied Metaheuristic Computing (IJAMC), and served as a Program Committee member for several major conferences, as well as a reviewer for many peer-reviewed journals and conferences. In recent years, he has published over 50 scientific papers, and his work has been cited over 2500 times. His other research interests include: Multi-Agent Systems, Swarm Intelligence, Discrete Choice Models, Automated Planning and Scheduling, (Data-Driven, Decentralized) Optimization, Self-Organized Systems, Metaheuristic Search, Coordination Mechanisms, Learning & Collective Behavior, Big Data and Urban Informatics.
He was a Scientist at the Robotics Institute, Carnegie Mellon University (CMU), and worked there for five years. Before that, he was a researcher worked with Dr. J. Liu (IEEE Fellow) at HKBU, and an early team member at a startup company Accelicon (acquired by Keysight Technologies). He received his B.S., M.S., and Ph.D. degrees in Solid-State Electronics from University of Electronics Science and Technology and Tsinghua University, respectively. In addition, he shortly worked with Intelligent Automation, and studied in Machine Learning at CMU.