About me
Computer Science and Applied Mathematics & Statistics Major 👋🏽
Hi, I'm Bhishma Gaudani, a Computer Science and Applied Mathematics & Statistics major at Stony Brook University, New York.
Hi, I'm Bhishma Gaudani, a Computer Science and Applied Mathematics & Statistics major at Stony Brook University, New York.
Stony Brook University · Part-time
Jan 2026 – Present · Stony Brook, New York, United States
CRIZM · Part-time
Jan 2026 – May 2026 · 5 mos · Stony Brook, New York, United States · On-site
Core Engineering Team
Stony Brook University · Part-time
Oct 2025 – Dec 2025 · 3 mos · Stony Brook University, New York, United States
Stony Brook University
Dec 2024 – Present · Stony Brook University, New York, United States
Student Assistant to the Building Manager of the Charles B. Wang Center. Assisted in daily operations and administrative tasks for the Charles B. Wang Center, which hosts conferences, theatrical performances, and other campus events.
Web Development Club of Stony Brook University
Nov 2024 – Present
Clever Harvey · Internship
May 2023 – Aug 2023 · 4 mos · India · Remote
DI Solutions · Internship
May 2021 – Jun 2021 · 2 mos · India · On-site
A convolutional neural network trained on MNIST that classifies handwritten digits (0–9), paired with a Streamlit app where you can draw a digit on a canvas and get a live prediction with confidence scores across all 10 classes. The CNN (two conv+pool blocks feeding a dense head, ~225K params) reaches 99.04% test accuracy, converging to 98.46% validation accuracy after just a single epoch on the standard 60,000/10,000 MNIST split.
A prediction model for the 2026 FIFA World Cup. It builds Elo ratings from 49,000+ international matches dating back to 1872, trains win/draw/loss models on top of them, and runs 50,000 Monte Carlo simulations of the official tournament bracket to generate championship probabilities for all 48 teams. The model is validated with walk-forward testing on the last five World Cups (2006–2022), reaching a log-loss of 0.959, close to the betting-market benchmark of ~0.95. On a harder out-of-sample test (2,673 matches from 2023–2026 never seen during training), it hits 62% accuracy with well-calibrated probabilities.
SeawolfStudy is a web application built with Python, Streamlit, and Geopy that enables students at Stony Brook University to view, track, and update real-time study spot availability on an interactive campus map. The app leverages geofencing to trigger proximity-based prompts and improve decision-making for over 100 pilot users. A SQLite backend with hashed authentication secures user accounts while automated 30-minute rolling updates ensure reliable crowd-level reporting. By integrating interactive maps and notifications, the platform helps students optimize study space selection and reduces inaccurate status logs by 40%.
A team hackathon project (built with Amir Hamza and Ritesh Chavan) that turns Stony Brook course feedback and grading data into actionable insights for students, educators, and administrators. An ETL pipeline built with Pandas processes raw course data, a HuggingFace sentiment pipeline scores feedback text, and Spacy handles NLP query parsing. A Flask web app wraps it all in a chatbot interface powered by OpenAI's GPT-3.5 Turbo, letting users ask natural-language questions about course difficulty, sentiment, and recommendations in real time.
A simple Python project for analyzing and visualizing historical stock data. This project focuses on fetching, processing, and plotting financial data for selected stocks such as Nvidia and Netflix. Since I am interested in quantitative finance, I started with this basic project to learn how to analyze stocks. I created graphs showing the open price, closing price, volume, high price, and low price over a 5-year period for Nvidia and Netflix. I also calculated the daily range and other key metrics to help with valuation, risk analysis, and momentum analysis of the stocks.
Hi, I'm Bhishma Gaudani. I'm an international student at Stony Brook University in New York, double majoring in Computer Science and Applied Mathematics & Statistics.
I've always been drawn to mathematics — not just solving problems, but understanding the logic behind them. That curiosity led me to computer science, where I became fascinated by how logical rules turn into systems that actually work: how computers process information, how algorithms make decisions, and how data can solve real-world problems.
I explore these ideas through programming, data analysis, and AI projects — always looking for something new to build and learn.
Outside academics, soccer has shaped me just as much. I've competed at the national level representing my state in India, and it taught me discipline, consistency, and how to stay focused under pressure — qualities I bring into everything I build.
@BhishmaGaudani on GitHub
Socials
Email: bgaudani@cs.stonybrook.edu
GitHub: GitHub Profile
LinkedIn: LinkedIn Profile