Akhil Nadigatla

About Me

Hello and welcome! I am currently a senior in the School of Computer Science at Carnegie Mellon University pursuing a major in Computer Science with a concentration in Machine Learning and a minor in Philosophy.

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 game theory.

Here is my resumé .

Projects & Work Experiences

Work Experiences

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)

Research

Towards Efficient Neural Zeroth-Order Optimization Algorithms
CMU Machine Learning Department (August 2021 - present)

- Under SCS Honors Thesis Program, exploring 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.

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