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Agam Shah

language models

data analysis

resources

alignment

monetary policy

claim extraction

cultural bias

financial markets

fomc

data resources

approaches to low-resource settings

2

presentations

1

number of views

SHORT BIO

I am a Machine Learning Ph.D. Candidate in the College of Computing at Georgia Tech, where I have been honored with the prestigious "2023 Rising Star Doctoral Student Research Award". Prior to my doctoral studies, I earned a Bachelor's degree (Hons.) in Information and Communication Technology with a minor in Computational Science from DA-IICT. My academic excellence was acknowledged with the President's Gold Medal for graduating at the top of the 2019 class. Additionally, I hold a Master's degree in Quantitative and Computational Finance (QCF) from Georgia Tech.

My research interests encompass Data Science, Finance, Computational Science, and Natural Language Processing. The outcomes of my research efforts have been published and presented in esteemed journals and conferences such as Expert Systems With Applications, European Journal of Physics, AFA, ACL, EMNLP, and various renowned universities worldwide.

Presentations

Numerical Claim Detection in Finance: A New Financial Dataset, Weak-Supervision Model, and Market Analysis

Agam Shah and 7 other authors

Trillion Dollar Words: A New Financial Dataset, Task & Market Analysis

Agam Shah and 2 other authors

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