Research

PhD Research

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

Published in "Computers & Mathematics with Applications" (2023).

https://doi.org/10.1016/j.camwa.2023.09.014.

Check out the presentation.

Stochastic Derivative-Free Optimization

Check out our preprint.

Previous Research

Flight Route Optimization (Spring '21)

Check out our work on Sabre's webpage.

Navigation of Autonomous Robots (Summer '20)

Check out our conference paper.

Google Sites

Report abuse