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Sheng Liu
I am an Assistant Professor of Operations Management and Statistics at the Rotman School of Management, University of Toronto. I joined Rotman after graduating from Berkeley in 2019. My research focuses on solving operations problems in supply chains, transportation, and logistics systems through optimization and data analytics. Most of my work leverages real-world data sets to derive insights and develop data-driven solution frameworks. I have extensive industry experience, consulting or working for organizations such as JD.com, Sport Chek, Ninja Van, Hungerhub, Amazon, and Lyft. I am fortunate to work on problems with real-world impacts, as recognized by finalists for the INFORMS Daniel H. Wagner Prize and M&SOM Practice-Based Research Competition. More recently, I have been investigating (a) data-driven and sustainable urban infrastructure planning, (b) inventory placement in online retailing, and (c) zoning/districting in emerging logistics systems. I am also interested in improving decision outcomes for vulnerable groups, motivated by collaboration with nonprofit organizations such as Shelter Movers. I am an associate editor of Transportation Science and an Editorial Review Board member of Service Science.
Email: sheng.liu[at]rotman.utoronto.ca
Research Interests:
optimization and data analytics, urban operations (particularly mobility and logistics), supply chain management, OM for social good (public-sector OM/OR)
Major Awards and Grants:
2024 INFORMS TSL Freight Transportation and Logistics SIG Outstanding Paper Award, Winner
2024 INFORMS Daniel H. Wagner Prize, Finalist
2024 INFORMS Service Science Best Cluster Paper Award, Finalist
2024 Connaught Community Partnership Research Award
2023 INFORMS PSOR (Public Sector Operations Research) Best Paper Award, Winner
2023 INFORMS Data Mining Best Paper Award, Finalist
2023 M&SOM Practice-Based Research Competition, Finalist
2023 Roger Martin Excellence in Research Award
2023 UofT-HUST Joint Seed Fund, 2023
2022 M&SOM Data-Driven Research Competition, Winner
2022 NSERC Discovery Grant
2022 INFORMS Data Mining Best Applied Paper, Finalist
2021 INFORMS SOLA (Section on Location Analysis) Best Student Paper Award, Winner
2018 The Data Open Competition (Citadel+Berkeley), Second Place
Publications & Working Papers:
Value of Dispatching Flexibility in On-Demand Delivery, submitted, 2025 (with Haoqing Wang, Mingliu Chen, Shuaian Wang)
Menu Optimization for (Office) Meal Delivery Platforms, under revision, 2024 (with Saman Lagzi, Ningyuan Chen, Pin Gao, Chenhao Wang)
Equitable Delivery Zoning for Last-Mile Logistics: A Framework Validated with Implementation, under revision, 2024 (with John Gunnar Carlsson, Stanley Lim, Han Yu)
Data Privacy in Pricing: Estimation Bias and Implications, under revision, 2024 (with Ningyuan Chen, Ming Hu, Jialin Li)
Inventory Allocation under the Greedy Fulfillment Policy: The (Potential) Perils of the Hindsight Approach, under revision, 2024 (with Stefanus Jasin and Jinglong Zhao)
Coordinate Package Delivery and On-Demand Rides: A Zoning Policy and Analysis, under revision, 2023 (with Junyu Cao)
Toward Stormwater-Resilient Cities: Robust Planning Against Extreme Rainfalls, under revision, 2023 (with Wei Qi, Aiqi Zhang)
Distributionally Robust Multilocation Newsvendor at Scale: A Scenario-Based Linear Programming Approach, under revision, 2023 (with Chenxi Li, Wei Qi, Lun Ran, Aiqi Zhang)
Planning Bike Lanes with Data: Ridership, Congestion, and Path Selection, Management Science, 2024 (with Auyon Siddiq and Jingwei Zhang)
Fairness in Accessibility of Public Service Facilities, Operations Research Letters, 2024 (with Nooshin Salari)
Pooling and Boosting for Demand Prediction in Retail: A Transfer Learning Approach, Manufacturing & Service Operations Management, 2024 (with Dazhou Lei, Yongzhi Qi, Hao Hu, Dongyang Geng, Jianshen Zhang, Zuo-Jun Max Shen)
Provably Good Region Partitioning for On-Time Last-Mile Delivery, Operations Research, 2023 (with John Gunnar Carlsson, Nooshin Salari, Han Yu)
On-Demand Delivery from Stores: Dynamic Dispatching and Routing with Random Demand, Manufacturing & Service Operations Management, 2023 (with Zhixing Luo)
On the Joint Inventory and Pricing Control for a One-Warehouse Multi-Store Problem with Lost Sales: Spiraling Phenomena and a Near-Optimal Heuristic, Operations Research, 2022 (with Yanzhe (Murray) Lei, Stefanus Jasin, Andrew Vakhutinsky)
Smart Urban Transport and Logistics: A Business Analytics Perspective, Production and Operations Management, 2022 (with Long He, Zuo-Jun Max Shen)
Real-Time Delivery Time Forecasting and Promising in Online Retailing: When Will Your Package Arrive?, Manufacturing & Service Operations Management, 2022 (with Nooshin Salari, Zuo-Jun Max Shen)
New Product Life Cycle Curve Modeling and Forecasting with Product Attributes and Promotion: A Bayesian Functional Approach, Production and Operations Management, 2022 (with Dazhou Lei, Hao Hu, Dongyang Geng, Jianshen Zhang, Yongzhi Qi, Zuo-Jun Max Shen)
Urban Bike Lane Planning with Bike Trajectories: Models, Algorithms, and a Real-World Case Study, Manufacturing & Service Operations Management, 2021 (with Xiang Ji, Zuo-Jun Max Shen)
On-Time Last Mile Delivery: Order Assignment with Travel Time Predictors, Management Science, 2021 (previously Data-Driven Order Assignment for Last Mile Delivery) (with Long He, Zuo-Jun Max Shen)
A Graph-Theoretic Approach for Spatial Filtering and Its Impact on Mixed-type Spatial Pattern Recognition in Wafer Bin Maps, IEEE Transactions on Semiconductor Manufacturing, 2021 (with Ahmed Aziz Ezzat, Dorit Hochbaum and Yu Ding)
Transient-State Natural Gas Transmission in Gunbarrel Pipeline Networks, INFORMS Journal on Computing, 2020 (with Shixuan Zhang, Tianhu Deng and Zuo-Jun Max Shen)
Adjacency-Clustering and Its Application for Yield Prediction in Integrated Circuit Manufacturing, Operations Research, 2018 (with Dorit Hochbaum)
Shared Mobility for Last-Mile Delivery: Design, Operational Prescriptions and Environmental Impact, Manufacturing & Service Operations Management, 2018, available on SSRN (with Wei Qi, Lefei Li and Zuo-Jun Max Shen)
Data Analytics and Smart City Operations, PhD Thesis, 2019
A Study of Three-Period Ramp-Up Polytope, Technical Report, 2015 (with Deepak Rajan)