🔥[NeurIPS'25] DeepFund: Pilot for Your Next Fund Investment

[NeurIPS 2025] A multi-agent framework that leverages LLMs to simulate socio-economic systems

💹 StockSim: Multi-Agent LLM Financial Market Simulator — A realistic trading simulation platform for evaluating large language models in dynamic financial environments.

Simple Finance Forecasting Ai. This Ai Model uses historical price data to forecast future prices. The model is trained on data downloaded from Yahoo Finance using the yfinance library, and predictions are made using a linear regression Ai model from sklearn. The model supports all the symbols supported by Yahoo Finance.

PHD Research Focus

RL Forex Bot with PPO AI-powered trading bot using PPO, dynamic position sizing, AMD GPU acceleration (DirectML/OpenCL), and MetaTrader 5 integration.

Agentic AI involves several key components. This is an AI Agent for trading.These agents typically use reinforcement learning (RL) methods to optimize their behaviour over time through interactions with an environment.

GDSC Solution Challenge - Innovatrix

AI-Powered Credit Scoring System | 99.7% Accuracy | Real-time Risk Assessment Advanced neural network solution for credit risk prediction using customer behavior analysis. Features 99.7% accuracy, real-time processing, and production-ready deployment pipeline for banking institutions. ✨ 99.7% accuracy • Real-time decisions • Multiple ML models

Production-ready RAG financial system with query classification, A/B testing, Streamlit dashboard, and comprehensive evaluation framework.

Production-ready RLAIF trading system with multi-agent Claude AI that learns from market outcomes. Features 60+ indicators, foundation models, and serverless deployment.

Predict crypto prices using neural nets + LLM-powered custom loss functions on real Chainlink data (ETH/USD)

Automated earnings analysis and stock price prediction using LLMs and financial data

A credit risk modeling project to predict loan defaults using financial data from Lending Club. Includes data cleaning, class imbalance handling with SMOTE, model training with LightGBM and SVM, and actionable insights for lenders.