Awards

• 10/2023, The 2023 Top 2% of Scientists on Stanford List
• 12/2022, The George N. Saridis Best Transactions Paper Award of The IEEE Transactions on Intelligent Vehicles
• 04/2022, Top 50 Rising Star Young Scholar on “AI+X” by Baidu Xueshu.
• 08/2020, IVADO Postdoc Research Fellowship Awards for Two Years, Canada.
• 07/2019, 3rd Summer School on Cognitive Robotics, LA, USA.
• 07/2018, The Best Ph.D. Dissertation Awards in China Society of Automotive Engineers (SAE-China).
• 09/2017, Excellent Ph.D. Programs Fellowship of Beijing Institute of Technology (BIT), China.
• 04/2015, Two-Year Graduate Student Fellowship of China Scholarship Councils (CSC), China.

Talks

(To be updated)

• 09/2021, ‘Spatiotemporal learning of multivehicle interaction patterns with nonparametric Bayesian statistics’, @ 24th IEEE International Conference on Intelligent Transportation, Indianapolis, IN, United States.
• 09/2021, ‘Variational Inference for Multivaritate Gaussian Mixtures’, @ McGill University
• 07/2021, ‘Interpretable Learning of multi-vehicle interactions for autonomous driving decision-making’, @ McGill University
• 05/2021, ‘How does human make sequential decisions during interactions?’, @ Beijing Institute of Technology (BIT), and @ Tongji University, China
• 04/2021, ‘Human-level learning of multi-vehicle interactions toward autonomous driving decision-making’, @ Jilin University, China
• 01/2021, ‘Driving primitives – Human-level learning for autonomous vehicles’, @ Beijing Jiaotong University, China
• 11/2020, ‘Adaptive path tracking for agricultural vehicles with sliding consideration’, @ Beijing AIForce Technoloy Co. Ltd., China
• 08/2019, ‘Human-level learning of driving primitives through Bayesian nonparametric statistics’, @ Vision and Automation System Lab at Robotics Institute, Carnegie Mellon University (CMU)
• 2019/07, ‘Traffic primitives: Concept, theory, and applications’, @ Mechanical Systems Control (MSC) Lab, UC Berkeley
• 05/2019, ‘Traffic primitives: concept, learning, and applications’, @ Smart Transportation Lab, McGill University
• 09/2018, ‘Traffic primitives: learning-based extraction and its applications’, @ Series Talks of Safe AI Lab, Carnegie Mellon University (CMU).
• 07/2018, ‘Extracting traffic primitives through Bayesian nonparametric learning and its applications’, @ Workshop on Safe AI in Autonomous Vehicles, Carnegie Mellon University (CMU).
• 06/2017, ‘A learning-based method for modeling driver behavior: theory and applications’, @ 2017 IEEE Intelligent Vehicles Symposium, CA, USA.