I am an AI & ML Associate, Sr. at the Machine Learning Center of Excellence in JPMorgan Chase & Co. working on news analytics and other exciting applied NLP research projects.
I have an MS in Computer Science student from the University of Massachusetts (UMass) Amherst. While doing my master’s, I’ve had the opportunity to work in the Information Extraction and Synthesis Lab headed by Prof.Andrew McCallum. I’ve also collaborated with Taesung Lee and Hessel Tuinhof at IBM Research. I interned for one summer at the Machine Learning Center of Excellence headed by Dr Lidia Mangu at JP Morgan Chase & Co. where I now work full-time.
I am passionate about delivering NLP and LLM-based solutions that satisfy users’ requirements, ensuring they effectively address their needs and enhance their overall experience.
My research interests are primarily linked to Natural Language Understanding. I am interested in what NLU sytems can tell us about human behavior and in what human cognition can teach us about building better NLU models. I am also interested in ethical, and explainable NLP and applying it towards social good.
Previously, I was a software engineer at Microsoft working on Azure and obtained my undergraduate degree in Computer Science from Manipal Institute of Technology, India.
In my free time, I enjoy reading and board gaming.
MS in Computer Science, 2022
University of Massachusetts Amherst
BE in Computer Science, 2018
Manipal Institute of Technology
Minimal web page allowing users to upload files and encrypt them with AES.
Trained a GPT-2 based Question Generation Model on the QuAC dataset and experimented with using generated questions to enhance training of BERT-based Question Answering Model
Addressed the task of verified claim retrieval - linking an unseen claim to previously-seen claims which have already been fact-checked. Used supervised clustering approach which defined a similarity measure between claims and facts using BERT-based representations.
Emotion classification on Reddit comments using BERT-base finetuned on GoEmotions dataset. Studied relationships between emotions expressed and upvotes given.