Building intelligent systems from silicon to software
Machine Learning Researcher and Computer Vision Engineer specializing in edge deployment, hardware-accelerated inference, and embedded AI systems. I bridge the gap between cutting-edge ML research and practical silicon implementation.
Currently: M.S. in Electrical & Computer Engineering from Purdue University (Graduated February 2026), focusing on deep learning optimization for resource-constrained environments.
Philosophy: "Understanding AI systems requires fluency from mathematical foundations through hardware constraints—theory without implementation is incomplete."
| Project | Description | Tech |
|---|---|---|
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Wasserstein GAN with Gradient Penalty for image generation |   |
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Deep Learning coursework & implementations |   |
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Neural network from scratch implementation |  |
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Computer Architecture & Systems |   |
| Project | Description | Features | Link |
|---|---|---|---|
| 🖥️ rory.computer | Hacker Terminal & AI Manifesto | Interactive CLI, Easter eggs, Theme switcher, OS shell simulation |  |
| 🧠 r0ry.com | Original ML/CV Portfolio | TensorFlow, PyTorch, OpenCV project showcases |  |
| 🧠 rory.software | AI Knowledge Manifold | CLT visualizations, AI ethics statement, Dyslexic Advantage explorer |  |
| 🏢 rory.engineer | Day in the Life Dashboard | Lithography demos, Interactive roadmaps |  |
| Project | Description | Tech Stack | Status |
|---|---|---|---|
| 🐱 CatNet | AI-powered feline identification with UNet segmentation | PyTorch, OpenCV, Raspberry Pi | 📦 Archived |
| Full-stack CV parking management system | React, Python, TensorFlow | 📦 Archived | |
| 📊 AI Manifold | Interactive knowledge topology visualization | D3.js, React, TypeScript | 🟢 Live |
| 🎭 AI Ethics Statement | Mission statement on responsible AI development | React, TypeScript | 🟢 Live |
| 🧩 Dyslexic Advantage | Interactive visualization of neurodivergent pattern recognition | D3.js, React | 🟢 Live |
| Domain | Purpose | Key Modules | Status |
|---|---|---|---|
| r0ry.com | ML/CV Portfolio & Projects | Project gallery, CV demos | 🟢 |
| rodericklrenwick.com | Professional Hub & Resume | Interactive resume, Ecosystem map | 🟢 |
| rory.engineer | Day in the Life Dashboard | Lithography explorer, Roadmaps | 🆕 |
| rory.computer | Hacker Terminal & AI Manifesto | Terminal CLI, Easter eggs, Themes | 🟢 |
| rory.software | AI Knowledge Manifold | AI Ethics, Dyslexic Advantage, Blog | 🔧 |
| rlr-github.github.io | Static Portfolio | GitHub Pages mirror | 🟢 |
Purdue University | Graduated: February 2026
Focus Areas: Signal & Image Processing, Deep Learning, Computer Vision, Embedded Systems
Key Coursework:
- ECE 59500 - Introduction to Deep Learning
- ECE 62900 - Introduction to Neural Networks
- ECE 69500 - Deep Learning (VLSI Focus)
- ECE 59500 - Computer Vision on Embedded Systems
- ECE 59500 - Intro to Compilers
University of Michigan-Dearborn | Winter 2020 | Graduated with Distinction
Foundation: VLSI Design, Embedded Systems, Autonomous Vehicle Perception
Mentors:
- Dr. Paul Watta - ML/CV & Autonomous Vehicles
- Dr. Adnan Shaout - Hardware & Embedded Systems
Raytheon Technologies Research Center | East Hartford, CT | Summer 2023
- Developed rapid prototyping methods for robotics intelligence
- Implemented smart metal anomaly detection using structured light
- Earned leadership commendation for innovative solutions
University of Michigan Autonomous Vehicle Project | Summer 2018 - Winter 2020
- Core team member for MDAS.ai autonomous shuttle
- Designed sensory data pipeline on NVIDIA TX2
- Contributed to real-time perception systems
Ford Motor Company | Summer 2017
- Gained expertise in functional safety (ISO 26262)
- Worked on battery architecture systems
- AI Arms Race: US-China Competition - Global engineering perspectives
- Hardware Neural Networks - FPGA MLP implementation
- CatNet Smart Door - AI pet access control
- ParkSmart Architecture - CV parking management
- Edge AI optimization & quantization
- Hardware-accelerated neural networks
- Generative model stability (GANs, Diffusion)
- Interpretable & explainable AI
- Real-time computer vision systems
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Dr. Paul Watta - Associate Professor, UMich-Dearborn
- CV/ML Mentor, Autonomous Vehicle Research Supervisor
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Dr. Adnan Shaout - Professor, UMich-Dearborn
- Hardware Neural Network & CatNet Supervisor
- Ozgur Erdinc - Senior Research Scientist, RTRC
- ML Research Internship Director
Open to research collaborations, ML/CV projects, and hardware-AI integration opportunities.
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Adapted from Gil Scott-Heron for the age of artificial intelligence
"Turn on, tune in, add Gaussian noise, and drop out"
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