Category: News
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Ivan visits South Carolina with confidence and robustness
Ivan visited Pooyan Jamshidi at the University of South Carolina. The agenda included conversations with like-minded researchers and tours of impressive mechanical, industrial, and electrical facilities. Thanks to UF and the SEC for supporting this academic exchange! In exchange, Ivan gave two talks about the recent research on confidence and robustness:
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New preprint: differentiable discrete abstractions
Our team figured out how to optimize discrete abstractions of continuous-state systems with gradient descent. The solution lies in a smooth proxy for a simulation metric. An example state grid, resulting from our technique, is shown above. Details below:
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New tutorial: conservative discrete abstractions
Our tutorial on building conservative, sound discretizations of continuous-state systems is finally online! To be presented by Jordan at the Embedded Systems Week in Barcelona. Citation:
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Zhenjiang defends his PhD thesis proposal
The proposed thesis, “Chance Prediction under Distribution Shift: Diagnosis, Calibration, and Guarantees for Visual Autonomy and Language Agents”, outlines a vision for detecting, adapting, and calibrating confidence under 4 types of shifts: observation, dynamics, initial state, and controller. The proposal builds on a significant list of papers where Zhenjiang contributed:
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Zhenjiang and Ani present temporal confidence at ACL’26
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Ani (who also volunteered) and Zhenjiang traveled to the Association for Computational Linguistics (ACL) conference in San Diego to present our work on using temporal signatures in language model logics to calibrate their correctness confidence. It was an exciting contribution and an exciting trip!
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Ivan receives IEEE TCCPS Early Career Award
This award recognizes a junior researcher from either academia or industry who has demonstrated outstanding contributions to the field of cyber-physical systems (CPS) in the early stage of his/her career development. Ivan was awarded ‘‘for contributions to rigorous assurance of learning-enabled cyber-physical systems, including their safety verification, trustworthy monitoring, and controller repair.’’ Big thanks to the IEEE Technical Committee on…
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New preprint: anomaly-informed safety confidence
We developed a new safety prediction pipeline that leverages a vector of anomaly scores to predict the system’s safety confidence. Somehow, it manages to generalize to unseen anomalies in sensing and dynamics. Citation:
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Zhenjiang presents confidences & world models at CPS Week
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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…
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New preprint: elimination for hypothesis testing
As a starting point towards using bandit-style algorithms for autonomy, we have developed finite-sample bounds for efficient hypothesis testing while eliminating unlikely hypotheses. Citation:
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New preprint: TEACar Autonomous Racing Platform
We have released our shiny new TEACar platform for autonomous racing, inspired by DonkeyCar but with upgraded mechanical, hardware, and software components! Citation: