npm i react-ghost-text
React, TypeScript, CSS
React component to show ghost text suggestions in an input field (line in VS Code or Gmail Smart Compose)
I am a PhD student in Computer Science at Cornell University advised by Aditya Vashistha. Previously, I was a Research Fellow at Microsoft Research and a Student Researcher at Google DeepMind.
My work sits at the intersection of Natural Language Processing and Human-AI Interaction, where I evaluate and mitigate cultural and social biases in large language models. My aim is to make generative systems value-aligned and globally safe. My research has been published at top-tier venues, open-sourced by Microsoft, and covered by mainstream media. On the side, I love tinkering with AI and building things!
Before Cornell, I graduated magna cum laude in Computer Science from Ashoka University, India. My undergraduate research earned me the Undergraduate Research Excellence award, while my campus leadership was recognized with the Student Life Excellence award. Beyond academics, I've competed at varsity-level in badminton and football/soccer, and represented at the national level in tennis.
Dhruv Agarwal, Anya Shukla, Sunayana Sitaram, Aditya Vashistha
Under Review New
Dhruv Agarwal, Mor Naaman, Aditya Vashistha
CHI 2025 Press Coverage
arXiv | The Atlantic | Fast Company
Taewook Kim, Dhruv Agarwal, Jordan Ackerman, Manaswi Saha
CSCW 2025 New
Dhruv Agarwal
In progress
Farhana Shahid, Dhruv Agarwal, Aditya Vashistha
CSCW 2025
React, TypeScript, CSS
React component to show ghost text suggestions in an input field (line in VS Code or Gmail Smart Compose)
Python (+ Flask), Facebook APIs
A Messenger bot I developed as a weekend hack to give Ashoka University users information about mess menu, shuttle timings and important phone numbers. The bot has received and sent over 80k messages to over 600 unique users since it was started in March 2017.
TF Object Detection API, Socket.io, Python, Node.js
A real-time smart city system for automatic detection and reporting of road accidents, using a machine learning and vision algorithm, for reduced relief response time and avoiding chaining of accidents. Adjudged 5th best project out of 400 teams at HackIIIT-D 2018.
Arduino, Raspberry Pi, Python (+ Flask), MySQL
We developed a device that could be placed in dorm rooms at Ashoka to monitor wastage of energy. We used multiple sensors to detect whether energy was being wasted in the form of unnecessary use of lights and AC, and displayed the information on a user-friendly web app.
Keras, Python, SciPy stack
A machine learning model (autoencoder) to beat common forms of facial obfuscation like blurring and pixelation. In addition, we defined another obfucation model, "blocking", to beat our model and hence show limitations of our model. We also tried generative models like GANs and variational autoencoders, which did not give good results for this task.
Python (+ Flask), PHP, MySQL
An online code judge (like CodeChef) intended to be used for programming contests within my University. This platform was eventually used by the instructor for programming assignment submissions in the CS101 course in Spring 2016.