Sheng Liu

Sheng Liu

University of Toronto

H-index: 9

North America-Canada

About Sheng Liu

Sheng Liu, With an exceptional h-index of 9 and a recent h-index of 9 (since 2020), a distinguished researcher at University of Toronto, specializes in the field of Data Analytics, Supply Chain Management, Logistics, Optimization.

His recent articles reflect a diverse array of research interests and contributions to the field:

Joint inventory and pricing for a one-warehouse multistore problem: Spiraling phenomena, near optimal policies, and the value of dynamic pricing

Pooling and Boosting for Demand Prediction in Retail: A Transfer Learning Approach

Provably good region partitioning for on-time last-mile delivery

Coordinate Package Delivery and On-Demand Rides: A Zoning Policy and Analysis

Data Privacy in Pricing: Estimation Bias and Implications

On-Demand Delivery from Stores: Dynamic Dispatching and Routing with Random Demand

New product life cycle curve modeling and forecasting with product attributes and promotion: A Bayesian functional approach

Toward Stormwater-Resilient Cities: Robust Planning Against Extreme Rainfalls

Sheng Liu Information

University

Position

Rotman School of Management

Citations(all)

465

Citations(since 2020)

451

Cited By

115

hIndex(all)

9

hIndex(since 2020)

9

i10Index(all)

9

i10Index(since 2020)

9

Email

University Profile Page

Google Scholar

Sheng Liu Skills & Research Interests

Data Analytics

Supply Chain Management

Logistics

Optimization

Top articles of Sheng Liu

Joint inventory and pricing for a one-warehouse multistore problem: Spiraling phenomena, near optimal policies, and the value of dynamic pricing

Operations Research

2022/10/17

Pooling and Boosting for Demand Prediction in Retail: A Transfer Learning Approach

Available at SSRN 4490516

2022/9/10

Provably good region partitioning for on-time last-mile delivery

Operations Research

2024/1

Coordinate Package Delivery and On-Demand Rides: A Zoning Policy and Analysis

Available at SSRN

2023/9/7

Data Privacy in Pricing: Estimation Bias and Implications

Available at SSRN

2023/6/22

On-Demand Delivery from Stores: Dynamic Dispatching and Routing with Random Demand

Manufacturing & Service Operations Management

2023/3

New product life cycle curve modeling and forecasting with product attributes and promotion: A Bayesian functional approach

Production and Operations Management

2023/2

Toward Stormwater-Resilient Cities: Robust Planning Against Extreme Rainfalls

Rotman School of Management Working Paper

2022/10/1

Smart urban transport and logistics: A business analytics perspective

Production and Operations Management

2022/10

Urban bike lane planning with bike trajectories: Models, algorithms, and a real-world case study

Manufacturing & Service Operations Management

2022/9

Distributionally Robust Multilocation Newsvendor at Scale: A Scenario-Based Linear Programming Approach

Available at SSRN 4207042

2022/8/31

Fairness in accessibility of public service facilities

Available at SSRN 4200501

2022/8/8

Real-time delivery time forecasting and promising in online retailing: when will your package arrive?

Manufacturing & Service Operations Management

2022/5

Planning bike lanes with data: Ridership, congestion, and path selection

Congestion, and Path Selection (March 12, 2022)

2022/3/12

On-time last-mile delivery: Order assignment with travel-time predictors

Management Science

2021

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

2021/3/2

Transient-state natural gas transmission in gunbarrel pipeline networks

INFORMS Journal on Computing

2020/7

See List of Professors in Sheng Liu University(University of Toronto)