A Computer Science & Data Science graduate dedicated to building scalable software, predictive machine learning models, and custom Android system modules. From high-performance SQL to kernel-level device trees.
I combine solid Computer Science fundamentals with advanced Data Science analytics and Android OS internals hacking to deliver high-performance software and systems.
Proficient in building predictive ML models, time-series anomaly detection, feature engineering, and PySpark big-data processing. MS GPA of 3.89 from the University of Memphis.
Experienced in writing scalable backend Java applications with Spring Boot, optimizing complex SQL queries in Snowflake/PostgreSQL, and shipping cloud-ready REST API microservices.
Core maintainer and developer of custom Android distributions (Infinity-X, Mist OS), Magisk/Xposed system UI modules (PixelXpert), device tree compilations, and SEPolicy kernel fixes.
Three core disciplines: analyze data carefully, design clean backend systems, and optimize low-level software performance.
Predictive modeling, data analytics pipelines, and interactive BI reporting.
Clean backend development, enterprise stability, and REST microservices.
Low-level system architecture, custom ROM maintenance, and kernel tuning.
A curated collection of machine learning experiments, Android OS hacking, and system designs.
Core developer of PixelXpert, a mixed Xposed and Magisk module for system UI customization on Google Pixel ROMs running Android 12+. Hooked SystemUI smart clipboard frameworks using Xposed API overrides.
Created custom Magisk system overrides and SEPolicy rule fixes for Google Pixel 10 Pro XL (mustang). Tunes CPU/GPU thermal throttle configurations and SSD2 disk storage performance.
Developed a robust predictive model for steel industry power usage. Designed and optimized a Random Forest model with 5-fold cross-validation, achieving 95% prediction accuracy.
Core contributor to Project Infinity-X and Project Mist OS, two highly-customized Android OS distributions focusing on performance, custom UI features, and device battery configurations.
Designed a cryptographic testing environment combining classic cryptography with deep learning. Trained Generative Adversarial Networks (GANN) to increase encryption strength.
Designed, tested, and shipped backend upgrades and bug patches for cloud applications during tenure at DATA Bricks. Ensured zero deployment downtime and high code reliability.
A record of roles across data analytics, software development, and academic research.
Whether you have a question about machine learning models, custom Android builds, software engineering opportunities, or just want to connect, my inbox is always open.