Kelin Luo

Kelin Luo is an Assistant Professor of Teaching in the Department of Computer Science and Engineering at the University at Buffalo, part of the School of Engineering and Applied Sciences. His research focuses on theoretical computer science and operational research, particularly discrete optimization problems and online algorithms. He holds a PhD in Management Science and Engineering from Xi'an Jiaotong University (2019) and a BS in Financial Engineering from Northwest University (2014). His work addresses challenges in collaborative delivery systems, vehicle routing, scheduling, and real-time decision-making under uncertainty.

Dr. Luo's research interests include developing efficient algorithms for logistics and transportation systems, such as drone delivery optimization, food delivery routing, and dynamic vehicle scheduling. His contributions span theoretical advancements and practical applications in areas like car-sharing systems, online bipartite matching, and hierarchical grouping algorithms for multi-vehicle dial-a-ride problems. Recent papers highlight innovations in minimizing flow time, handling stochastic requests, and leveraging historical data for improved decision-making.

His articles frequently explore optimization under constraints, such as restricted movement areas for drones or variable booking times in car-sharing. Notable themes include approximation algorithms for combinatorial problems, online algorithms for dynamic environments, and the integration of historical data into scheduling systems. Despite his prolific output, no scientific awards are explicitly listed in his profile.

While no specific grants or advising details are provided, his academic role emphasizes teaching alongside research. His work contributes to foundational and applied aspects of computer science and operations research, with implications for modern logistics and transportation networks.