Roderick L. Renwick
Computer Engineer | Machine Learning Researcher | Hardware Designer
Computer Engineer | Machine Learning Researcher | Hardware Designer
I am a graduate student in the MSECE program at Purdue University (expected graduation 2025), with a passion for machine learning, computer vision, and hardware design. My academic journey has been focused on developing expertise in both software and hardware aspects of computing systems.
My experience spans from developing state-of-the-art machine learning models to implementing hardware solutions using FPGAs and microcontrollers. I have worked on various projects involving deep learning architectures, computer vision applications, and real-time embedded systems.
I am particularly passionate about advancing the field of machine learning and computer vision, with a focus on developing innovative neural network architectures, optimizing vision algorithms for edge deployment, and creating intelligent systems that can perceive and understand the visual world. My goal is to bridge the gap between cutting-edge ML research and practical, efficient implementations.
Purdue University
Specialization: Signal & Image Processing, Deep Learning, Neural Networks
Expected: 2025
West Lafayette, IN
University of Michigan, Dearborn
Focus: Digital Design, Computer Vision, Autonomous Systems, VLSI Design
Graduated with Distinction | Autonomous Vehicle Research Assistant
2020
Dearborn, MI
Raytheon Technologies Research Center (RTRC)
Summer 2023
University of Michigan - Dearborn
2018 - 2020
Ford Motor Company
Summer 2017
Developed computer vision algorithms for object detection and tracking in autonomous vehicles, contributing to the MDAS.ai project. Implemented real-time tracking systems and optimized deep learning models for edge deployment.
Implemented machine learning models for computer vision applications in defense and aerospace systems. Developed novel approaches to real-time object detection and tracking in challenging environments.
Various embedded systems and hardware projects demonstrating expertise in computer engineering and system design. Includes FPGA implementations, custom PCB designs, and real-time systems development.
ML Engineer & Computer Vision Specialist CV
Comprehensive showcase of AI & vision systems
Academic research on international AI competition
FPGA-based Multi-Layer Perceptron implementation
AI-powered pet identification & access control
Computer vision parking management system design
AI-powered cat identification and access control system. Implemented complete pipeline from image gathering, UNet segmentation, CNN training, to real-time embedded deployment.
Designed and implemented Wasserstein GAN with Gradient Penalty for high-fidelity synthetic image generation. Explored advanced optimization techniques for training stability.
Led senior design team in developing comprehensive parking management system. Integrated computer vision, web backend, and mobile frontend for real-time vacancy detection.
Hardware neural network implementation in VHDL. Translated Python MLP to optimized hardware description with focus on combinational logic reduction.
Comprehensive system architecture diagram illustrating the RVS implementation, including data flow, component interactions, and system boundaries.
Detailed visualization of the MIPS32 RISC processor architecture, highlighting key components, data paths, and control flow mechanisms.
I'm always interested in hearing about new opportunities in machine learning, computer vision, and AI research. Feel free to reach out if you'd like to collaborate or discuss potential projects.
