Zhenjiang Mao travelled all the way to Brittany in France to present his recent contributions at the CPS-IoT Week 2026.
First, Zhenjiang showcased his proposed PhD work on “Action Confidence Trajectories for Safety Assurance in Autonomous Systems” at the CPS-IoT Week PhD Forum. He gave a short pitch and then presented a poster, which was popular thanks to its unorthodox view of safety assurance.
Second, Zhenjiang presented “Physically Interpretable World Models via Weakly Supervised Representation Learning” in the HSCC/ICCPS main track. This paper targeted an exciting problem setting of learning interpretable state spaces with partial information and weak supervision. However, it also left many curiosities to explore and loose ends to chase in the future.
Citation:
- Zhenjiang Mao, Mrinall Eashaan Umasudhan, Ivan Ruchkin.
Physically Interpretable World Models via Weakly Supervised Representation Learning [Arxiv] [Slides] [Poster] [Demo] [Github].
In Proceedings of the 17th ACM/IEEE International Conference on Cyber-Physical Systems (ICCPS), Saint Malo, France, 2026.
