Prof. Wai Kin Victor Chan | Artificial Intelligence | Best Researcher Award
Prof. Wai Kin Victor Chan | Artificial Intelligence | Professor at Tsinghua University | China
Prof. Wai Kin Victor Chan is a distinguished academic and researcher at Tsinghua University’s Tsinghua-Berkeley Shenzhen Institute, widely recognized for his expertise in agent-based simulation, discrete-event systems, intelligent transportation networks, and sustainable energy applications. Over his career, he has made significant strides in computational modeling, deep learning frameworks, blockchain systems, and manufacturing optimization, earning more than 2,600 citations across his research portfolio. His work addresses pressing technological challenges by bridging simulation science, artificial intelligence, and smart city innovation, establishing him as a thought leader and collaborator in advancing next-generation technologies for global benefit.
Academic Profile
Education
Prof. Chan earned his Ph.D. in Systems Engineering, focusing on discrete-event simulation modeling and optimization techniques for complex industrial systems. His doctoral research, supported by international collaborations, laid the foundation for his future breakthroughs in multi-cluster scheduling, simulation-based energy analysis, and AI-driven forecasting frameworks. Building upon his early academic achievements, his continuous learning through postdoctoral engagements and research residencies allowed him to refine expertise in transportation systems modeling, sustainable manufacturing, and decentralized technologies.
Experience
Prof. Chan has built an extensive research career through faculty roles, international research collaborations, and industry-linked projects that merge academic rigor with real-world impact. At Tsinghua University, he leads interdisciplinary initiatives connecting simulation, artificial intelligence, and smart infrastructure, partnering with global institutions to develop computational frameworks for blockchain energy modeling, emergency transportation planning, and AI-powered traffic systems. His experience spans conference leadership, workshop facilitation, and mentoring graduate researchers, while his advisory roles for industrial partners have enabled the application of his models to enhance supply chains, urban planning, and energy-efficient manufacturing systems.
Research Interest
Prof. Chan’s research interests are anchored in agent-based and discrete-event simulations, Monte Carlo computational techniques, AI-enabled traffic prediction, blockchain-driven sustainability, and system optimization for smart cities and industrial processes. He is particularly focused on developing hybrid modeling approaches that combine simulation and artificial intelligence to manage complex, dynamic systems. His contributions to the study of emergent behavior modeling, electricity market simulations, and multi-cluster scheduling have influenced the design of scalable frameworks for both academic research and applied engineering solutions worldwide.
Award
Prof. Chan’s exceptional academic trajectory, marked by his citation index of 2,634, h-index 24, and i10-index 49, positions him as a strong nominee for the Best Researcher Award. His contributions have advanced transportation system resilience, sustainable blockchain adoption, and AI-driven optimization techniques, earning recognition within academic and professional networks such as IEEE and ACM. His role as a collaborative leader in international research projects exemplifies the kind of global impact celebrated by this award category.
Publications
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“Cost modeling and optimization of a manufacturing system for mycelium-based biocomposite parts”
Published year: 2016 | Citations: 77 -
“Agent-Based Simulation Tutorial: Simulation of Emergent Behavior”
Published year: 2010 | Citations: 240 -
“Optimal Scheduling of Multicluster Tools Part I”
Published year: 2010 | Citations: 154 -
“Spatial-Temporal Attention Wavenet for Traffic Prediction”
Published year: 2021 | Citations: 117 -
“Evaluation of Energy Consumption in Blockchains”
Published year: 2020 | Citations: 109 -
“Monte Carlo Simulations Applied to Uncertainty in Measurement”
Published year: 2013 | Citations: 125 -
“Offline RL with No OOD Actions: In-Sample Learning via Implicit Value Regularization”
Published year: 2023 | Citations: 107
Conclusion
Prof. Wai Kin Victor Chan’s research career embodies the qualities celebrated by the Best Researcher Award, blending theoretical innovation, high-impact publications, and interdisciplinary leadership. His pioneering studies in agent-based systems, AI-driven simulations, and sustainable technologies not only advance the state of knowledge but also provide solutions for urban resilience, energy efficiency, and digital innovation. With a strong publication record, global collaborations, and a vision for expanding AI-integrated sustainability and smart infrastructure frameworks, he continues to shape the future of computational science, making him a deserving recipient of this recognition.