[1] Huawei, Prediction Team at Autonomous Driving Solution (ADS)Domain: Behavior intention modeling and trajectory prediction of autonomous vehicle system.Experience: Designing, implementing, optimizing, and deploying a large-scale distributed Scene-centric Transformer model for trajectory and long-term intention prediction of vehicles and vulnerable road users.[2] Huawei, Scenario Research at Smart Transportation SolutionDomain: AI-Driven optimization of electric and connected vehicle system.Project #1: Charging Scheduling of Electric Buses Based on Machine Learning Methods for Combinatorial Optimization. Developing a real-time combinatorial optimization algorithm for charging and scheduling of electric buses, and optimizing the comprehensive goal of the total electricity fee and the quality of bus services through precisely predicting the proper charging moment and duration.Project #2: Business, Architecture and Development for A Connected MaaS System. Designing a local MaaS system considering different mobility modes of connected vehicles and exploring their cost-effectiveness.Project #3: A Vehicle-road Collaboration System for Specialized Vehicles at Airports. Participating in the optimization of routing, scheduling and simulation of electric specialized vehicles (e.g., catering truck) at airport airside.

Project: Modelling Transportation Resilience under Extreme Weather Events Based on Graph Neural Networks.Methodology: Diffusion graph convolutional recurrent neural network and a dynamic-capturing algorithm of transportation resilience jointly build the deep learning framework. Codes: Artificial intelligence in transportation resilience, https://github.com/Charles117/resilience_shenzhen