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Personal profile

Research profile

Yongqi got his B.Sc. in Telecommunication from Beijing Jiaotong University (2014), and M.Sc. in Control Science and Engineering from Tsinghua University (2017), where he also minored in Data Science. During the very past few years, he had trained himself as a researcher in various universities, research institutions and companies, adopting Machine Learning and Data Science methods to transportation research and smart mobility. In January 2020, he started his Ph.D. research career within the  SAMEN  project, under the supervision of Dr. ir. Haneen Farah and Prof. dr. Bart van Arem. His research focuses on developing data-driven models to expand Automated Vehicles Operational Design Domain in mix traffic.

Academic Homepage: https://yongqidong.github.io/ 

Research profile

My current research centers around the areas of Automated Vehicle, Smart & Shared Mobility, and Artificial Intelligence. I aim at developing innovative Deep Learning models for Automated Vehicles’ sensing and Deep Reinforcement Learning models for Automated Vehicles’ controlling, and thus realize  Safe, Efficient, and Socially Compliant Autonomous Driving. I have also delved into shared mobility employing big data analytics and machine learning techniques to reveal unique spatial-temporal patterns. My previous works have been published in high-quality top journals and conferences, including Transportation Research Part CIEEE Transactions on Intelligent Transportation Systems, and Computer-Aided Civil and Infrastructure Engineering, as well as IEEE International Conference on Intelligent Transportation Systems  (ITSC) and Transportation Research Board annual meeting  (TRB).

Research interests

My ultimate goal is to employ artificial intelligence and interdisciplinary research as tools to shape a better world. For that, I have delved in the transportation domain as the use case. The essence of transportation is to reconcile the spatio-temporal imbalance in the distribution of matter, information and energy, which is all about time and space. Thus, I had attach utmost importance to the spatial-temporal correlations in my research.

My current research centers around three main pillars, i.e., 1) Deep Learning for sensing and anomaly detecting, 2) Deep Reinforcement Learning for controlling and decision-making, 3) Big Data Analytics for spatial-temporal pattern mining.

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  • SDG 9 - Industry, Innovation, and Infrastructure
  • SDG 11 - Sustainable Cities and Communities

Education/Academic qualification

Tsinghua University

1 Sep 20141 Jul 2017

Award Date: 1 Jul 2017


  • TE Highway engineering. Roads and pavements
  • automated driving
  • Deep learning
  • TA Engineering (General). Civil engineering (General)
  • Traffic
  • Transportation safety


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