Prasun Banerjee
Computer Science at the Georgia Institute of Technology
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My name is Prasun Banerjee. I'm a third year Computer Science student at Georgia Tech specializing in Machine Learning and Mathematical Modeling. My central focus and professional interest is the rich and technically challenging world of Quantitative finance and algorithmic trading. I am currently looking to apply my academic and professional work in machine learning, statistical modeling and working with large, noisy datasets in the Quantitative Finance industry.
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In my rare moments of free time, I enjoy exploring my passion for the culinary arts, as well as playing the ancient Hindustani woodwind instrument the Bansuri, and reading about history, philosophy and markets.
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My Studies & Areas of Interest
Quantitative Finance
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Alpha Research
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Options Theory
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Market Microstructure Modeling ​
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Statistical Arbitrage
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HFT Infrastructure
Machine Learning & NLP
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Statistical Learning
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Optimization Algorithms
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Sentiment Analysis
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MLOps & Systems
Probability & Statistics
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Probability Theory
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Stochastic Processes
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Time-Series Analysis
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Regression Analysis
HPC & Scientific Computing
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Parallel & GPU programming
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Low-Latency C++ programming
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High-Performance Computer Architecture
Numerical Methods
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PDE & Finite Difference Methods
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Numerical Linear Algebra
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Monte Carlo Simulations
Big Data Systems
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Cloud & Distributed Computing
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​Database Systems
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Data pipeline development
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High-Performance Data Processing
My Research & Work
I am extensively involved with research at Georgia Tech. I enjoy utilizing mathematics and programming to chip away at technologically challenging problems that do not necessarily have an existing clear cut solution. Below is a summary of some of my work. More information can be found on the Research page, linked below.
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Quantitative Research - A selective team within the Georgia Tech Trading Club. We conduct thorough research and use advanced mathematical models and programming to identify statistically significant signals and alpha generating opportunities in the cryptocurrency futures market. Projects involve rigorous statistical testing and working with very high-volume order-book data. Using the information derived from this analysis, we can develop advanced trading strategies and collaborate with the Quant Dev. team to deploy our strategies on our custom low-latency Rust infrastructure.
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Natural Language Processing for Finance - An S-1 filing is the initial registration statement a company must submit to the SEC before going public. These documents present preliminary information about a company through several required and optional sections, and this research project with the Financial Services Lab focuses on building scalable infrastructure to pull, store, and parse the filings and apply modern Natural Language Processing techniques to determine if the S-1 filings can be used to identify underpricing or overpricing of the company.
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Machine Learning for Real Estate Valuation - Estimates put cumulative overvaluation of real-estate in flood-prone regions up to $237-billion. In this project, I collaborated with Savannah-based consultants to develop a full-stack Machine Learning system using time-series analysis and hedonic regression to estimate a geographic distribution of real-estate overvaluation on Tybee island. This project has been recognized by the Southeast Coastal Ocean Observing Regional Association.
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Teaching Assistant - I also serve as an Undergraduate Teaching Assistant for Discrete Mathematics and Honors Discrete Math at Georgia Tech. I instruct students in introductory logic, set theory, combinatorics, and algorithms. I have previously TA'd students in Object Oriented Programming in Java.
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My Associations: (Click logos for more info)
