About me

Electrical and Computer Engineer with a strong background in embedded systems, machine learning, biomedical engineering, and substation design. Experienced in developing real-time sensor systems, robotics applications, and AI deployments on edge devices. Passionate about learning, innovation, and translating complex data into actionable insights.

What I Am Working On

  • Embedded Systems

    Developing embedded systems, focusing on robotics, wearable technologies, and sensor systems.

  • Machine Learning

    Data analytics and computer vision projects, building models that extract insights and enable automation.

  • Power Systems

    Designing substation schematics, wiring diagrams, and bills of materials for electrical infrastructure projects.

  • Biomedical Engineering

    Applying technology to healthcare by building tools for gait analysis and histological image processing.

Other Things I Like

  • Basketball

    Captain of my high school's basketball team and have been playing for over 15 years.

  • Travelling

    Travelled through 20 states in the US and 7 different countries. Europe is next on my list.

  • Computer Components

    Building custom computers and mechanical keyboards and have helped many friends with their setups.

  • Pets

    My favorite way to unwind at the end of the day is spending time with my two cats, Aslan and Celeste.

Daniel lewis
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Daniel lewis

Richard was hired to create a corporate identity. We were very pleased with the work done. She has a lot of experience and is very concerned about the needs of client. Lorem ipsum dolor sit amet, ullamcous cididt consectetur adipiscing elit, seds do et eiusmod tempor incididunt ut laborels dolore magnarels alia.

Resume

Experience

  1. Dashiell Corporation

    Design Engineer I March 2024 – Current

    • Design and validate electrical drawings (schematics, wiring diagrams, cable schedules, and bills of materials) for over 10 substations' protection and control systems using Bluebeam and AutoCAD.
    • Collaborated with clients to ensure on-time delivery of deliverables and full compliance with IEEE standards.

  2. Scale AI

    AI Data Analyst (Contract) January 2024 – September 2024

    • Utilized Reinforcement Learning from Human Feedback (RLHF) to enhance the large language models (LLMs) data processing and model training pipelines, leading to a 25% increase in efficiency and a 15% enhancement in output precision across varied tasks.
    • Evaluated AI-generated responses using a Side-by-Side (SxS) scoring system, enhancing model accuracy by ranking based on key dimensions.
    • Performed quality control for Python, C++, MATLAB, and SQL codes generated by the LLMs and peer-reviewed the work of others.

  3. Caterpillar Inc.

    Graduate Researcher September 2023 – December 2023

    • Trained a ResNet50 model in a Docker container with CUDA using Python, PyTorch, and Linux.
    • Deployed the model on the Xilinx ZCU104 FPGA using AMD Vitis AI for real-time segmentation of Caterpillar construction equipment with a precision of 0.26 mAP at 12 FPS.

  4. The University of Alabama

    Graduate Research Assistant August 2021 – December 2023

    • Designed an intelligent shoe sensor system with an IMU and foot pressure sensors to collect human movement data using Python and Arduino, building a comprehensive dataset for motion analysis and wearable technology research.
    • Built and trained machine learning models using Tensorflow on movement datasets, achieving 87.8% accuracy in classifying human subjects based on gait patterns.
    • Developed a MATLAB algorithm using Kalman filter to calculate stride length in real-time with an accuracy of 98%.

  5. CYOBot

    Software Engineer Intern May 2022 – August 2022

    • Developed 10 robotics projects using Python and Arduino to control the GPIOs, LED displays, and mechanical movements, and created instructional tutorials tailored for college students.
    • Integrated the system with the RPLIDAR using Linux and ROS, built and trained machine learning models using PyTorch for lane detection and path planning.
    • Developed computer vision applications using Raspberry Pi Camera and OpenCV, including OCR document scanning, real-time projectile prediction, and rock-paper-scissors hand-sign recognition.

Education

  1. The University of Alabama

    Master of Science in Electrical Engineering, December 2023

    • GPA: 3.75/4.00
    • Coursework: Sensor Signal Processing, Digital Signal Processing, Communications, Data Analytics, Thin Film Technology

  2. The University of Alabama

    Bachelor of Science in Computer Engineering, May 2021

    • Minors: Mathematics, Computer Science
    • GPA: 3.99/4.00 (Summa Cum Laude)
    • Honors: Fred R. Maxwell Jr. Award, John Key McKinley Research Scholarship, Presidential Scholarship, President’s List
    • Coursework: Computer Architecture, Electronics, Embedded Systems, Digital Systems, Data Structures and Algorithms

Skills

  • Domains

    Wearable Technology, Biomedical Engineering, Machine Learning, Deep Learning, Signal Processing, Embedded Systems, Robotics, Computer Vision

  • Programming Languages

    Python, C, C++, MATLAB, Arduino

  • Tools & Technologies

    Linux, Git, Raspberry Pi, LiDAR, IMU, Meridian, AutoCAD, ROS, LTspice, PSpice, OrCAD, PCB Artist, FPGA

  • Libraries

    TensorFlow, PyTorch, Keras, Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn

Publication

Contact

Contact Form (Future Work)