Projects

ML-Driven Poker Analytics & Bluff Prediction Platform

LSTM

Deep Learning

Time Series

Poker

Developed an end-to-end machine learning pipeline that extracts, cleans, and feature-engineers over 5.7k real-money hand histories from PokerNow.club. Leveraging advanced feature engineering (bet ratios, decision times, board evaluations with Ace detection, and dynamic positional metrics) and a custom LSTM model with dynamic bucketing, the system predicts bluff versus value betting with a test AUC of 0.77. Hyperparameter tuning, cross-validation, and class balancing were key to optimizing performance.

Computer Vision-Based Pickleball Analytics System

Computer Vision

A system that leverages YOLOv8 and a fine-tuned ResNet50 model to track players and ball in real time—automating shot speed, player positioning, and court analysis.

Algorithmic Trading System for ORB Strategy

Financial Machine Learning

Simulated an ORB day trading strategy on TQQQ by testing multiple interval sizes and leveraging XGBoost with an SQL-based data pipeline to predict optimal trade conditions, achieving a 19.1% annualized return improvement.

CNN-Based Age Prediction System

CNN’s

Trained a CNN-based age prediction model using PyTorch, the UTK dataset, and a ResNet10 architecture to predict ages with an average error of ±4 years—optimized via hyperparameter tuning and deployed with a Streamlit UI for real-time inference.

Ethereum Smart Contract for NFT Generation & Minting

Crypto

Algorithmic Art Generation

Designed and deployed an Ethereum smart contract for NFT generation and minting, supporting 10,000+ unique ERC-721 assets with an optimized Python image pipeline, reduced gas fees by 15%, and a user-friendly UI that facilitated over 1,000 transactions.