Broadly, I am passionate about adapting machine learning techniques to fields like agriculture, with a focus on developing
countries. I am specifically interested in machine learning robustness and optimization, as well as its intersection with
Software Engineer Intern Splunk (June 2021 - August 2021)
Web Development and Support Lead CS Academy (May 2019 - December 2019)
Research Intern World Agroforestry Center (July 2016 - August 2016)
Neural Zeroth-Order Optimization: Empirical Study and Insights CMU Machine Learning Department (August 2021 - May 2022)
- Under SCS Honors Thesis Program, explored zeroth-order (derivative-free) optimization techniques that (1) make no assumptions about underlying objective function (2)
require few queries to the (potentially noisy) zeroth-order oracle, (2) scale well to higher-dimensions with minimal computation between queries.
- Advised by Prof. Pradeep Ravikumar
and Arun Suggala.
Adversarial Robustness via Model Ensembles CMU Machine Learning Department (October 2020 - May 2021)
- Contemporary training algorithms against adversarial risk rely on heuristics, often leading to lower-than-expected test accuracy.
- Under the mentorship of Prof. Pradeep Ravikumar
and Arun Suggala, investigated the effects of using weighted ensembles of
classifiers on the advesarial robustness of deep neural networks, specifically in image classification tasks.