Ziliang Xiong
PhD student
Passionate about AI in general and Uncertainty Quantification in particular: enabling artificial neural networks to be aware of the uncertainty in their own predictions, a vital step towards safe and trust-worthy AI.
I am an academic PhD student at Computer Vision Laboratory.
Quick Facts: Ziliang Xiong
CV
- 2022-: PhD in Electrical Engineering with specialization in Computer Vision, Linköping University, Linköping, Sweden.
- 2020-2022: Master of Sience in Machine Learing, Lund University, Lund, Sweden.
- 2015-2019: Bachelor's in Automation Sience and Technology, Beihang University, Beijing, China
Social Media
- ORCID: https://orcid.org/0009-0008-8277-7476
- LinkedIn: https://www.linkedin.com/in/xzleo
- GitHub: https://github.com/XZLeo
Publications
Ziliang Xiong, Shipeng Liu, Nathaniel Helgesen, Joakim Johnander, Per-Erik Forssen, CATPlan: Loss-based Collision Prediction in End-to-End Autonomous Driving (2025) 
https://arxiv.org/abs/2503.07425
Shipeng Liu, Ziliang Xiong, Bastian Wandt, Per-Erik Forssén, Continuous Normalizing Flows for Uncertainty-Aware Human Pose Estimation (2025) https://arxiv.org/abs/2505.02287
Ziliang Xiong, Arvi Jonnarth, Abdelrahman Eldesokey, Joakim Johnander, Bastian Wandt, Per-Erik Forssén, 
Hinge-Wasserstein: Estimating Multimodal Aleatoric Uncertainty in Regression Tasks, IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp. 3471-3480, IEEE (2024) 
https://doi.org/10.1109/cvprw63382.2024.00351
Simon Kristoffersson Lind, Ziliang Xiong, Per-Erik Forssén, Volker Kruger, Uncertainty quantification metrics for deep regression, Pattern Recognition Letters 186:91-97 (2024) https://doi.org/10.1016/j.patrec.2024.09.011 https://arxiv.org/abs/2405.04278
Zihan Wang, Ziliang Xiong, Hongying Tang, Xiaobing Yuan, Detail-Enhancing Framework for Reference-Based Image Super-Resolution (2024) https://arxiv.org/abs/2405.00431
Research
Research Activities
My PhD project is part of Situation Aware Perception for Safe Autonomous Robotics Systems is funded by Swedish national strategic research environment ELLIIT (grant C08).
I am affiliated with the Wallenberg AI, Autonomous Systems and Software Program.
Teaching
I am a teaching assistant and a project supervisor in several courses such as ”TSBB19 Machine Learning for Computer Vision”, ”TSBB18 Embeded Perception System”, and ”TSDT18 Signal and System”.I am also a supervisor for both internal and external master theses.
