Reinforcement learning based optimizer with extensible architecture. Using plug-ins it can be used for trading strategy, porfolio or hyperparameter optimization, using optimization methods like genetic algorithms or q-learning, and diverse agent types as heuristic strategies or using machine learning on observations to produce agent control actions

An advanced platform for quantitative trading strategies, including AI-driven price prediction models and user management systems. Emulating institutional-grade practices like Citadel, it facilitates the development, training, and deployment of machine learning models for precise market forecasting.

Implementing Agentic AI frameworks to facilitate strategic dialogue and complex reasoning in global tax policy.

Monte Carlo Discounted Cash Flow (MCDCF)

The goal of this project is to analyze customer behavior for Goldman Sachs' credit card division to develop a data-driven marketing strategy. By leveraging K-Means Clustering, we segment the customer base into distinct personas, allowing the bank to move from a "one-size-fits-all" approach to hyper-personalized financial products.

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A mini deep learning project integrating predictive modeling with a web interface to estimate the financial impact of data breaches.