Summary
Ziliang Xiong is a Ph.D. researcher in machine learning for computer vision at Linköping University and affiliated with the WASP program, specializing in uncertainty estimation for neural networks to improve trustworthy, explainable AI in robot perception and autonomous driving. With eight years of industry and research experience—from thesis work on radar-based road-user detection at Zenseact to deep learning internships at Axis—he blends applied system development with rigorous academic inquiry. He has supervised master's theses and taught embedded perception systems, demonstrating an ability to translate research into practical pipelines and open-source code. A top-performing student in his MSc at Lund, Ziliang is also interested in generative AI and large models, positioning him to bridge probabilistic perception and modern foundation-model approaches. Notably, his thesis work on YOLO and grid-mapping for RadarScenes was open-sourced, reflecting a commitment to reproducible research.
8 years of coding experience
1 year of employment as a software developer
Bachelor of Engineering, Automation, 3.53, Bachelor of Engineering, Automation, 3.53 at Beihang University
Master of Science, Machine Learning, System and Control, 4.4/5 (TOP 1), Master of Science, Machine Learning, System and Control, 4.4/5 (TOP 1) at Lund University
Doctor of Philosophy - PhD, Electrical Engineering with specialization in Computer Vsion, Doctor of Philosophy - PhD, Electrical Engineering with specialization in Computer Vsion at Linköping University
Chinese, 瑞典语, Chinese