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Anjali Parashar

3 accepted papers

2026

SEED-SET: Scalable Evolving Experimental Design for System-level Ethical Testing

ICLR 2026poster

As autonomous systems such as drones, become increasingly deployed in high-stakes, human-centric domains, it is critical to evaluate the ethical alignment since failure to do so imposes imminent danger to human lives, and long term bias in decision-making. Automated ethical benchmarking of these sys…

Cited by 0SourceScholar
2025

Cost-aware Discovery of Contextual Failures using Bayesian Active Learning

CoRL 2025poster

Ensuring the robustness of robotic systems is crucial for their deployment in safety-critical domains. Failure discovery, or falsification, is a widely used approach for evaluating robustness, with recent advancements focusing on improving sample efficiency and generalization through probabilistic s…

Cited by 0SourceScholar
2024

Learning-Based Bayesian Inference for Testing of Autonomous Systems

RA-L 2024

For the safe operation of robotic systems, it is important to accurately understand its failure modes using prior testing. Hardware testing of robotic infrastructure is known to be slow and costly. Instead, failure prediction in simulation can help to analyze the system before deployment. Convention

Cited by 2SourceScholar