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The University of Texas at Austin
Graduate Research Assistant (Generative AI, LLMs)

Aug 2022 - Present

Currently advised by Dr. Jessy Li, my thesis is focused on investigating large language models and their ability to perceive and interact with human emotions. We recently published a paper, "Large Language Models (mostly) do not consider emotion triggers when predicting emotion", which you can read here. My latest project is focused on understanding the role of emotion triggers in abling LLMs to detect medical misinformation. 

Esperanto Technologies
Machine Learning Research Intern

May 2023 - Aug 2023

I led a team of four interns and designed an end to end pipeline to analyze the capability of state of the art large language models to make accurate moral judgements in socially nuanced situations. We trained multiple LLMs to find that these models do not understand how mental health disorders, socioeconomic status, and stress may affect social interactions. I was also responsible for the testing of these LLMs on various tasks on Esperanto's SOC-1 chip. 

NLP Research Intern

Jan 2022 - July 2022

Under the supervision of Dr. Scott Hale, I developed a system that can identify questions about misinformation with respect to COVID-19 on social media. I also helped perform a large-scale analysis of the geo-demographic variation of these questions using neural embeddings and K-Means Clustering. 

MITACS Global Research Intern 2021
A data driven analysis of user anxiety in social media:

June 2021 - Present

Under the supervision of Dr. Morteza Zihayat and Dr. Rhonda McEwen, I aim to provide an answer to the question, how can machine learning research be employed to provide useful and actionable information for mental health professionals in the identification and monitoring of people suffering from social anxiety? This project seeks to determine the extent to which data patterns that emerge within social media platforms are causally related to information seeking, use, and sharing for those dealing with anxiety. One specific objective of this research is to develop a framework that can reveal behavioral patterns within and among social media to model social anxiety.  

Research Intern at the Centre of Artificial and Machine Intelligence
EMMA-HD: An explainable ensemble model to distinguish threats from hate-speech on Twitter

December 2020 - July 2022

We have developed a dataset of threat tweets and proposed an ensemble model of machine learning classifiers that can distinguish threats from sexist tweets. The research question that motivated this project is, how can we leverage natural language processing to make cyberspace safer for women?​ This paper can be found here.

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