Work

I'm a Master's in ML student at Carnegie Mellon University in Pittsburgh, USA, graduating in December 2026.

Previously, I was a software engineer at Google in the Bengaluru, India office. I worked on the Google Maps team, contributing to the fight against abuse using Graph Neural Networks. Previously, I also worked with Google Ads.

I graduated from BITS Pilani, Goa, in 2023 with a major in Computer Science and a minor in Philosophy, Economics, and Politics. During my college years, I worked on projects in various areas of technology, including machine learning, end-to-end software development, and research. I'm proud to have worn many hats.

I'm passionate about combining technology, equity, and humanity. What does that mean? I aim to utilize my technical skills in ML/AI to develop solutions to pressing societal issues and ensure that my work benefits everyone, particularly those from underrepresented communities. I've written about some of my experiences in my blog posts, which might help you understand where I'm coming from. I'm particularly passionate about bringing more women into the technology field.

Publications

Estimating the Spread of COVID-19 Due to Transportation Networks Using Agent-Based Modeling,

Springer Journal, Part of the book series: Lecture Notes in Computer Science (LNAI,volume 14546)

15 March, 2024

Extended version of the previous paper, selected and revised.

Studying the Impact of Transportation During Lockdown on the Spread of COVID-19 Using Agent-based Modeling,

Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART

February 24, 2023

In this study, we analyze the patterns of the spread of infection of COVID-19, recovery, and death specifically for the state of Goa, India, for twenty-eight days. Using agent-based simulations, we explore how individuals interact and spread the disease when traveling by trains, flights, and buses in two significant settings - unrestricted and restricted local movements.

Learning From Biological and Computational Machines: Importance of SARS-CoV-2 Genomic Surveillance, Mutations and Risk Stratification

Frontiers in Cellular Infection and Microbiology

Dec 24, 2021

My work consisted of the analysis and visualization of the clinical data of COVID-19 affected patients to find statistically significant features. We also implemented the Nested Cross-Validation method on 5 different machine learning models to classify the severity of the disease in patients.

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