Lingxuan (Leo) Kong is a PhD student supervised by Prof. Alexandra Brintrup in the Supply Chain AI Lab in Institute of Manufacturing at University of Cambridge. His current research area is on machine learning methods for supply chain financing risk predictions. Lingxuan has explored different machine learning methods including federated learning, Hierarchical Bayesian model to identify, model and mitigate the potential disruption risks on order- level associated in supply chain financing area. He also aims to discover the causility of the supply chain financing order-level risks by causal machine learning apporach and generate the corresponding policy trees for optimising the decision making process in supply chain network.

Lingxuan received his Bachelor of Engineering (Honours) degree from Australian National University. He majored in mechatronics system. His previous research projects during bachelor study mainly focus on the distributed clustering algorithm and graph partitioning techniques. These algorithms can be applied to multi-robot system and data processing problems. He also took an internship at Bernecker & Rainer Industrial Automation. He designed a learning-based controller which combines the BP neural network learning and pole-placement control methods for the inverted pendulum.

Publications:

Kong, Lingxuan, Ge Zheng, and Alexandra Brintrup. "A federated machine learning approach for order-level risk prediction in Supply Chain Financing." International Journal of Production Economics 268 (2024): 109095.

Zheng, Ge, Lingxuan Kong, and Alexandra Brintrup. "Federated machine learning for privacy preserving, collective supply chain risk prediction." International Journal of Production Research 61.23 (2023): 8115-8132.

Yuni Zhou, Lingxuan Kong, Stefan Sosnowski, Qingchen Liu, Sandra Hirche" Distributed Event/Self-Triggered Coverage Control with Speed Constrained Unicycle Robots", in 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Prague, 2021

L Kong, Q. Liu and C. Yu, "Range-limited distributed algorithms on higher-order Voronoi partitions in multi-robot systems", in 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Macau, 2019