Young-San Lin
Assistant Professor, Operations/Management Science
Young-San Lin is Assistant Professor, Operations/Management Science at Melbourne Business School’s Centre for Business Analytics.
He completed his PhD in the Department of Computer Science at Purdue University, where he was a teaching and research assistant.
His research interests are in the interdisciplinary field of theoretical computer science, economics, and operations research, with a focus on market design, revenue management, resource allocation, and online algorithms.
His work has been published in leading journals and conference proceedings, including Operations Research, Naval Research Logistics, Algorithmica, ACM Conference on Economics and Computation, Conference on Web and Internet Economics, Conference on Neural Information Processing Systems, International Conference on Approximation Algorithms for Combinatorial Optimization Problems (APPROX), and the European Symposium on Algorithms (ESA).
Most Recent Research
Allocation with Weak Priorities and General Constraints (2021), Young-San Lin, Hai Nguyen, Thành Nguyen, Kemal Altinkemer, Operations Research, ACM Conference on Economics and Computation
Market Equilibrium in Multi-tier Supply Chain Networks (2020), Tao Jiang, Young-San Lin, Thành Nguyen, Naval Research Logistics, Conference on Web and Internet Economics
Online Directed Spanners and Steiner Forests, Elena Grigorescu, Young-San Lin, Kent Quanrud (2021), special issue of Theory of Computation for the APPROX/International Conference on Randomization and Computation 2021
The Maximum Binary Tree Problem, K. Chandrasekaran, E. Grigorescu, G. Istrate, S. Kulkarni, Y.S. Lin, M. Zhu (2021), Algorithmica 83, pp 2427–2468, ESA 2020
