FinanceOngoing Prototypes2024 — Present

Quantitative ML & Scientific Computing Research Notebooks

Role: Applied Researcher

Curated repository of Jupyter notebooks covering quantitative finance, stochastic differential equations, machine learning experiments, and exploratory data analysis.

Verified Project Links & Repositories

1 Active Resource

GitHub Repository (Main)

Primary verified codebase, implementation, and commit history

Quantitative ML & Scientific Computing Research Notebooks

Technology Stack & Libraries

PythonJupyter NotebookNumPyPandasMatplotlibSciPyPyTorch

The Challenge / Problem

Context & Objectives

Mathematical theory in textbooks is frequently detached from practical computational code, making it difficult for students and researchers to replicate empirical results.

Architectural Solution

Engineered Approach

Documented rigorous, reproducible Python notebooks pairing formal LaTeX mathematical formulations with clear NumPy and PyTorch implementations.

System Architecture & Pipeline

Mathematical Theory (LaTeX) -> NumPy Vectorized Implementation -> Matplotlib/Seaborn Visualization -> Empirical Validation.

A public collection of reproducible scientific computing notebooks demonstrating applied mathematics and machine learning workflows. Includes Black-Scholes option pricing models, geometric Brownian motion simulations, risk-neutral valuation, and exploratory deep learning architectures.

Engineered Capabilities & Innovations

Monte Carlo exotic option pricing engine with variance reduction techniques

Stochastic volatility modeling comparing Heston simulations with historical implied vol

Time-series forecasting prototypes using recurrent and convolutional architectures

Clean pedagogical markdown cells explaining underlying mathematical lemmas

Empirical Results & Benchmarks

Serves as an open educational and research resource for students studying computational mathematics and quantitative systems.

Have Questions About This System?

I am always glad to discuss technical architecture, benchmarks, or potential collaboration.

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