معرفی
Pengyu Qian serves as an Assistant Professor in the Department of Operations and Technology Management at Boston University's Questrom School of Business, where he conducts research at the intersection of operations research, economics, and algorithmic systems design.
Education
- PhD, Graduate School of Business, Columbia University, 2021
- B.Sc., Peking University, 2015
Research Interests
Dr. Qian specializes in theoretical and applied problems within matching markets, dynamic resource allocation, and queueing network optimization. His work develops algorithmic solutions for market inefficiencies using tools from game theory, stochastic modeling, and mechanism design. Current investigations focus on partner competition dynamics in two-sided markets, incentive structures for resource pooling, and blind control policies in closed networks where system states remain partially observable.
Publication Trends
His 2018-2024 publications demonstrate consistent output in top-tier venues including Management Science and ACM Economics & Computation conferences, with increasing emphasis on real-world market applications. The research trajectory shows progression from foundational queueing network control to sophisticated matching market analyses, maintaining strong theoretical rigor while addressing practical constraints like information asymmetry and dynamic partner competition.
Scientific Awards
No scientific awards, fellowships, or major honors are documented in the available profile information.
Advising and Grants
While specific student advisees and grant funding details are not disclosed in the current materials, Dr. Qian's publication record suggests active collaboration with leading researchers including Yash Kanoria and Itai Ashlagi, indicating participation in significant research initiatives within operations management and market design.
Labs and Teams
Though no dedicated laboratory is specified, his research profile aligns with Boston University's operations management research groups at Questrom, particularly those focused on algorithmic market design and stochastic optimization within business contexts.
