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C++ Embedded Systems

Location:
Chandler, AZ
Salary:
75000
Posted:
April 28, 2025

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Resume:

Holmes Joseph

480-***-**** • ********@***.*** • www.linkedin.com/in/holmes-joseph/ • www.github.com/holmesj56 EDUCATION

M.S. Robotics and Autonomous Systems May 2025

Arizona State University, Tempe, AZ 3.79/4.00 GPA

Relevant coursework: Robotics Systems, Applied ML and AI, Real Time DSP, Perception in Robotics, VLSI design automation, Mechatronic Systems, Programming Industrial Robotics Systems, Real time Embedded Systems B.Tech. Electronics and Communication April 2018

Cochin University of Science and Technology, Kerala, India 7.14/10.00 GPA TECHNICAL SKILLS

Programming Languages: Python, C, C++, Java, ROS, MATLAB, Simulink, SQL, Lingua Franca Electronics: Circuit Design, Fabrication, Sensor Integration, Communication Protocols (I2C, UART, SPI etc.) Software and Tools: Eclipse, Keil, Microsoft Visual Studio Code, STM32Cube, Unix/Linux, RTOS, TCP/IP, HTTP Tools and Frameworks: Git, NumPy, Sklearn, TensorFlow, PyTorch, Solid Works, ISSAC SIM Robotics: Cobot, UR5, FANUC robots, PLC, SLAM, Robot Vision, HVAC, Simulation and GUI, Clean Room Robotics PROFESSIONAL EXPERIENCE

Graduate Student Researcher, Neuromuscular Control and Human Robotics LAB(ASU,Voluntary) 12/2023 – 11/2024

● Supported research on shoulder stiffness in Dynamic and Static states with a 3-DOF exoskeleton, incorporating impedance and admittance controllers which led to improvement in understanding human-robot interaction

● Executed and refined experimental protocols for human subjects, resulting in a 30% increase in data accuracy and reliability

● Applied MATLAB for advanced data analysis in neuromuscular research, identifying critical trends and validating findings through comparison with existing data.

Project Developer (Higbec Ltd) 7/2020-6/2023

● Spearheaded multiple automation and IoT projects, including smart irrigation systems and automated lighting, demonstrating technical leadership and adaptability in designing and implementing solutions.

● Designed and built electronic projects by integrating sensors, microcontrollers, and actuators to create cost-effective and efficient IoT-based systems.

● Developed embedded software for ARM Cortex M4 Microcontrollers, enhancing the functionality and performance of IoT devices through optimized code and hardware-software integration.

● Masted I2C and SPI communication protocols, enabling seamless sensor integration in automation projects, significantly improving data accuracy and system responsiveness

PROJECTS

Hill Climbing Robot(GitHub repo) Fall 2024

● Engineered a hill climbing solution on Pololu 3pi+240 robot leveraging gyroscope, encoders and obstacle detection for precise navigation and real-time control without using operating system. Simulated Annealing-Based slicing floorplan for VLSI design (GitHub repo) Spring 2024

● Implemented SA algorithm for Floor planning over 10,000 hard and soft blocks. Utilized Wang Hu algorithm to give random perturbations. Was able to attain less than 20% empty area in all cases LIOSAM for Autonomous Navigation (GitHub repo) Spring 2024

● Integrated LiDAR and IMU data using factor graph optimization in C++ and ROS to compare open-loop and closed-loop control, improving real-time odometry, path planning, and sensor fusion for autonomous navigation Automated Tic Tac Toe Robot with Real-Time Color Recognition (GitHub repo) Fall 2023

● Engineered a Tic Tac Toe-playing robot with advanced color recognition, leveraging Python and OpenCV for real-time analysis and gameplay. This project showcased the integration of computer vision with robotic control, achieving a dynamic interaction model that responded accurately to human moves with a success interaction rate of 90% Machine Learning-Based Fake Job Posting Detection with Synthetic Data Generation (GitHub repo) Fall 2023

● Devised a model to identify fake job postings with an 82% accuracy rate, utilizing decision trees, AdaBoost, and XGBoost algorithms. Enhanced the model's utility by generating synthetic job postings for reference, achieving 85% accuracy using NLP and LSTM methods, addressing a critical need for authenticity in job markets WORK EXPERIENCE

Arizona State University, Tempe, AZ: Graduate Services Assistant -Grader 3/2024 – present



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