Research
PhD Research
PhD Research
Nonlinear Optimization
Nonlinear Optimization
Design and analysis of Nonlinear Optimization algorithms.
Extensive testing of the empirical performance of the methods.
My research interests include Adaptive Sampling, Stochastic Optimization, Constrained Optimization,
Derivative-Free Optimization, Distributed Optimization etc.
Collaborations with Argonne National Laboratory and Lawrence Livermore National Laboratory.
Internship at Lawrence Berkeley National Laboratory.
Conference presentations: IOS 2022, ICCOPT 2022, SIAM OP23, INFORMS Annual Meeting 23.
Adaptive Sampling Augmented Lagrangian
Adaptive Sampling Augmented Lagrangian
Published in "Computers & Mathematics with Applications" (2023).
https://doi.org/10.1016/j.camwa.2023.09.014.
Check out the presentation.
Previous Research
Previous Research
Navigation of Autonomous Robots (Summer '20)
Navigation of Autonomous Robots (Summer '20)
Check out our conference paper.
