I'm a Research Fellow at the PROSE team at Microsoft, where I work on evaluating and designing agentic AI tools for programmers and end users, guided by Dr. Emerson Murphy-Hill, Dr. Gustavo Soares and Dr. Sumit Gulwani. By investigating interactions with agents, I aim to understand how we can better design them to collaborate effectively with users. I completed my bachelor's degree in Computer Science and Engineering at Indian Institute of Technology Kanpur, where I was fortunate to be advised by Prof. Sruti Ragavan. During this time, I investigated the opportunities and challenges of using LLMs for programming education.
My research interests lie at the intersection of human-computer interaction, generative AI, and software engineering. I am particularly interested in exploring human-AI collaborations that improve upon the individual capabilities of both humans and AI and facilitate growth and long-term benefits for users.
ASE 2025 (To appear)
An empirical study to understand the strategies developers use when collaborating with AI agents on real-world tasks and the challenges to effective collaborations.
ToCHI 2025
Developing and evaluating a multi-agentic AI tool that assists end-users in creating new spreadsheets.
Pre-print
A mixed methods study comparing how CS2 students learn programming concepts using LLMs versus traditional online methods, examining information gathering approaches and outcomes across both scenarios.
Pre-print
An examination of the cultural biases shown by a variety of LLMs in the symbols that they generate, and experimenting with prompting techniques to reduce such biases.
SIGCSE 2024
A survey-based study examining how trust in GenAI and the factors affecting this trust influence students' adoption of GenAI and their performance in CS courses.
VL/HCC 2023
An analysis of the participant recruitment biases in end-user programming research and recommendations for more inclusive approaches.
Pre-print
Defining and evaluating with real users a novel approach to extract tables from semi-structured input text utilizing both neurosymbolic methods as well as LLMs.
Course Project
Designed a high-fidelity prototype for an app that supports people struggling with binge eating by applying fundamental interaction design principles.
Semester Project, ML4ED Lab, EPFL
Built on the paper by Cock et al. to analyze the impact of intersectionality on different oversampling strategies for a behavioural predictive model in education.
A choose-your-own-adventure style interactive game written in C++ (name inspired from a Netflix Show).