Professional Experience:
Dr. Xiaoming Li currently serves as a Research Associate at Concordia University, MontrƩal, where he supervises interdisciplinary research in artificial intelligence and operations research for shared mobility-on-demand applications. His role involves designing deep learning models for time-series demand forecasts, developing data-driven stochastic optimization models for renewable energy mobility management, and creating an integrated optimization framework for sustainable crowd-shipping services. Previously, Dr. Li held a Research Assistant position at Concordia, working on data analysis and machine learning model development for various projects, including forecasting commodity rates and predicting hotel booking cancellations.
Dr. Li’s industrial experience includes internships at Ericsson’s Global Artificial Intelligence Accelerator, where he developed an energy-saving framework for 5G base stations, and Medialpha, where he optimized nurse routing and medical resource allocation using meta-heuristic algorithms. Additionally, he has substantial experience as a Software Engineer at Shenyang Aerospace University, leading projects and managing teams.
In academia, Dr. Li has served as an Adjunct Faculty at Vanier College, teaching database theory and application development, and as a Full-Time Lecturer at Shenyang Aerospace University, instructing on a variety of computer science courses and supervising numerous student projects.
Research Interest:
- Machine Learning
- Operations Research
- Data Science
- Data-Driven Optimization
- Agent-Based Simulation Modeling
- Shared Mobility
- Smart Logistics
- Sustainable Intelligent Transportation Systems