Imperial College London


Faculty of EngineeringDyson School of Design Engineering

Research Postgraduate



yanran.wang20 CV




Dyson BuildingSouth Kensington Campus





I am a Ph.D. student at Imperial College London, where I am a member of Systems and Algorithms Laboratory (SysAL).

My research interests mainly include Trustworthy Autonomous System Design through Formal Guarantees on Interpretable reinforcement learning and optimal control theories, and its application on real aerial robots. Particularly, I am interested in the theories and algorithms that empower machine to see and think more intelligent. In addition to scientific research, I loves classic music and sports!

If you are interested in my research, please move to see my personal website.

Visit Yanran's Google Scholar page.


2021.05 - NOW: Ph.D Student, in Dyson School of Design Engineering, Imperial College London.
2017.09 - 2020.03: M.S. in information and control, Shanghai Jiao Tong University.
2013.09 - 2017.06: B.S. in Automation, Southest University.



Xiao G, Wang Y, He F, 2019, Research on safety modeling and analysis in information fusion system, Aerospace Systems, Vol:2, ISSN:2523-3947, Pages:51-60

Wang Y, Xiao G, Dai Z, 2017, Integrated display and simulation for automatic dependent surveillance–broadcast and traffic collision avoidance system data fusion, Sensors, Vol:17, ISSN:1424-8220, Pages:1-23


Wang Y, O'Keeffe J, Qian Q, et al., 2022, Interpretable Stochastic Model Predictive Control using Distributional Reinforced Estimation for Quadrotor Tracking Systems, 2022 IEEE 61st Conference on Decision and Control (CDC), IEEE

Wang Y, O'Keeffe J, Qian Q, et al., 2022, KinoJGM: A framework for efficient and accurate quadrotor trajectory generation and tracking in dynamic environments, 2022 IEEE International Conference on Robotics and Automation (ICRA), IEEE

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