Accelerated Algorithms for a Class of Optimization Problems with Constraints. - Anjali Parashar; Priyank Srivastava; Anuradha M. Annaswamy; Biswadip Dey; Amit Chakraborty (CDC, 2022)

Accelerated Algorithms for a Class of Optimization Problems with Constraints. - Anjali Parashar; Priyank Srivastava; Anuradha M. Annaswamy (CoRR, 2022)

Accelerated Algorithms for a Class of Optimization Problems with Equality and Box Constraints. - Anjali Parashar; Priyank Srivastava; Anuradha M. Annaswamy (ACC, 2023)

On the stability of second order gradient descent for time varying convex functions. - Travis E. Gibson; Sawal Acharya; Anjali Parashar; Joseph E. Gaudio; Anuradha M. Annaswamy (CoRR, 2024)

Failure Prediction from Limited Hardware Demonstrations. - Anjali Parashar; Kunal Garg; Joseph Zhang; Chuchu Fan (CoRR, 2024)

Fast and Modular Autonomy Software for Autonomous Racing Vehicles. - Andrew Saba; Aderotimi Adetunji; Adam Johnson; Aadi Kothari; Matthew Sivaprakasam; Joshua Spisak; Prem Bharatia; Arjun Chauhan; Brendan Duff Jr.; Noah Gasparro; Charles King; Ryan Larkin; et al. (Field Robotics, 2024)

Learning-Based Bayesian Inference for Testing of Autonomous Systems. - Anjali Parashar; Ji Yin; Charles Dawson 001; Panagiotis Tsiotras; Chuchu Fan (IEEE Robotics Autom. Lett., 2024)

On the stability of gradient descent with second order dynamics for time-varying cost functions. - Travis E. Gibson; Sawal Acharya; Anjali Parashar; Joseph E. Gaudio; Anuradha Annaswamy (Trans. Mach. Learn. Res., 2025)

RADIUM: Predicting and Repairing End-to-End Robot Failures Using Gradient-Accelerated Sampling. - Charles Dawson 001; Anjali Parashar; Chuchu Fan (IEEE Trans. Robotics, 2025)