Conference on Robot Learning (CoRL), 2025
This work uses coverage-based active learning for discovering failures in robotic systems with a limited sample budget.
Recommended citation: A. Parashar, J. Zhang, Y. Li, C. Fan (2025). "Cost-aware Discovery of Contextual Failures using Bayesian Active Learning." 9th Conference on Robot Learning.
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International Conference on Robotics and Automation (ICRA), 2025
We use learning based techniques to improver the efficiency of MCMC sampling for testing of autonomous systems
Recommended citation: A. Parashar, J. Yin, C. Dawson, P. Tsiotras, C. Fan (2024). "Learning-based Bayesian Inference for Testing of Autonomous Systems." IEEE Robotics and Automation Letters.
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American Control Conference (ACC), 2023
We investigate the application of higher-order optimization techniques for a class of constrained optimization problems with linear constraints
Recommended citation: A. Parashar, P. Srivastava, A.M. Annaswamy (2023). "Accelerated Algorithms for a Class of Optimization Problems with Equality and Box Constraints." American Control Conference 2023.
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Conference of Decision and Control (CDC), 2022
We investigate the application of higher-order optimization techniques for convex optimization with constraints
Recommended citation: A. Parashar, P. Srivastava, A.M. Annaswamy (2022). "Accelerated Algorithms for a Class of Optimization Problems with Constraints." Conference of Decision and Control (CDC) 2022.
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Bayesian Decision making and Uncertainity workshop (BDU), NeurIPS 2024, Allerton, 2024
Novel failure discovery method that combines information from simulation and real-world systems using sampling based tchniques and Bayesian Experimental Design
Recommended citation: A. Parashar, K. Garg, C. Fan (2024). "Failure Prediction from Limited Hardware Demonstrations." IEEE proceedings, Allerton 2025.
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IEEE Transactions on Robotics (TRO), 2025
Gradient-accelerated sampling for failure discovery and repair using first order Langevin algorithm
Recommended citation: C. Dawson, A. Parashar, C. Fan (2025). "RADIUM: Predicting and Repairing End-to-End Robot Failures using Gradient-Accelerated Sampling." IEEE Transactions on Robotics 2025.
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Transactions on Machine Learning Research, 2025
Provable stability for second-order gradient based optimization for time-varying cost functions
Recommended citation: T.E. Gibson, S. Acharya, A. Parashar, J.E. Gaudio, A.M. Annaswamy (2025). "On the stability of gradient descent with second order dynamics for time-varying cost functions; Transactions on Machine Learning Research.
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Journal of Ocean Engineering, 2020
Design and analysis of a fault tolerant control for an AUtonomous Underwater Vehicle (AUV) with four rotatable thrusters
Recommended citation: J. Kadiyam, A. Parashar, D. Deskhukh, S. Mohan (2020). "Actuator fault-tolerant control study of an underwater robot with four rotatable thrusters." Journal of Ocean Engineering, Science Direct, 2020.
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