A comprehensive collection of mathematical tools and utilities designed to support Lean Six Sigma practitioners in their process improvement journey

💻 Workflow Data For Github Actions & Linux Server Testing of Lockdown Enterprise Content 💻

Data-driven computer-aided molecular and process design

A hybrid modeling framework combining neural networks with physics-based constraints for bioreactor process optimization and control.

Generative AI-based system for simulating industrial processes, enabling predictive maintenance, process optimization, and energy efficiency using GANs and IoT sensor integration

A Python web app using Streamlit & PuLP for ILP-based production scheduling. Maximizes profits by assigning products to machines, factoring in batch sizes, setup times, rates, costs, & demand. User-friendly, flexible, & ideal for manufacturing.

This tool models and optimizes user tasks based on real-world behaviors. It transforms individual task models into unified, constraint-driven representations, using examples like Wordle to demonstrate its effectiveness. The tool visualizes task flows for better design and efficiency.

💻 Workflow Data For Github Actions & Windows Server Testing of Lockdown Enterprise Content 💻

Evaluación de KPIs y rendimiento operativo para identificar áreas de mejora en servicios de telecomunicaciones.

Evidence Based Decisions Using Big Data Analytics

Reduce laboratory Turnaround Time by identifying bottlenecks across the accession → collection → receipt → analysis → verification → report workflow. Deliverables: KPI dashboard, bottleneck analysis, and optimization recommendations.

A High Distinction (HD) project focused on Enterprise Architecture design, BPMN 2.0 process modeling, and system performance optimization for complex service ecosystems.

Anki Flashcards for 3rd Year Courses

Strategic framework for digital transformation in multi-national manufacturing. designed for conservative organizations

Data-driven optimization of Teradyne’s excess inventory approval process using Python, lead-time adjusted demand modeling, and financial risk analysis to improve capital efficiency and reduce excess spend.

This repository contains machine learning models for predicting the degree of SiO2 extraction from iron ore tailings using aqueous solution of ammonium bifluoride (NH4HF2). The prediction models take into account three key parameters: temperature, reaction time, and NH4HF2 concentration.

Python automation tool for bulk YouTube transcript extraction | Built for CCNA study workflow

QA test case simulating AWS Support workflow automation for MFA removal. Includes bug documentation, test cases, and efficiency analysis built from SME-level experience in account security.

This presents my portfolio of services and skills.

Docs-as-Code CV | GenAI-driven process optimization | Clarity, collaboration & continuous improvement.