I am a PhD student at Cornell University, advised by Aditya Vashistha. Previously, I was a Research Fellow at Microsoft Research, where I worked with Tanuja Ganu, Srinivasan Iyengar, Mohit Jain, and Manohar Swaminathan.
I work on Responsible AI and Human-AI Interaction. I study cultural and racial bias in generative AI models. This includes dicovering, benchmarking, and mitigating bias in AI models. I also work on AI for social good, such as in healthcare, misinformation, and sustainability. My work has been published at ACM CSCW, COMPASS, and SenSys, and has also been open-sourced by Microsoft.
Prior to MSR, I graduated magna cum laude in Computer Science from Ashoka University, India. At Ashoka, I was awarded the Undergraduate Research Excellence award. I also won the Student Life Excellence award for my contributions to student life and social impact. I have played varsity-level badminton and football/soccer, and national-level tennis.
Taewook Kim, Dhruv Agarwal, Jordan Ackerman, Manaswi Saha
Under Review
Dhruv Agarwal, Taewook Kim, Manaswi Saha, Jordan Ackerman
In progress
Dhruv Agarwal, Mor Naaman, Aditya Vashistha
Under review
Farhana Shahid, Dhruv Agarwal, Aditya Vashistha
CSCW 2025
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.
NLP (TF-IDF, BoW), Keras, Python, SciPy stack
Undertook the Fake News Challenge to distinguish between the following relationships between a news headline and an article body: unrelated, agree, disagree, discuss. We got comparable (if not better) results than winners of the competition (although we did break some rules of the competition!).
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.