Hi, my name is

Jaspartap Goomer

Embedded Firmware Engineer skilled in C/C++, microcontroller programming, hardware communication protocols, and low-level debugging. Passionate about developing efficient, reliable firmware for real-time and hardware-integrated systems.

About Me

I'm a Computer Science student at Ontario Tech University with a deep passion for embedded systems and firmware development. Currently pursuing my BSc (expected May 2027), I specialize in creating robust, real-time solutions for hardware-integrated systems.

My experience spans across multiple domains including automotive systems (Formula SAE), aerospace (rocketry), and autonomous systems (drone design). I thrive on the challenge of optimizing low-level code and implementing complex communication protocols like CAN, SPI, I2C, and Modbus.

When I'm not coding firmware, you'll find me leading embedded teams, collaborating on technical inspections, or building innovative IoT solutions that bridge the gap between hardware and software.

4+
Active Projects
3
Leadership Roles
10+
Technologies
2027
Expected Graduation
Jaspartap Goomer

Skills & Technologies

Programming & Development

Java Python C++ C HTML/CSS JavaScript RTOS Glassfish Server

Embedded Systems

STM32 ESP32 Raspberry Pi Arduino Linux CANDB++ BUS Master

Software & Tools

Eclipse MATLAB/Simulink VS Code GitHub IntelliJ Arduino IDE Cube IDE CubeMX Microsoft Office

Data & Analysis

NumPy pandas Matplotlib Logic Analyzer

Work Experience

Engineering Student

Ontario Tech University ACE (Automotive Center of Excellence)

May 2025 – Present
  • Designed a diagnostic controller to validate temperature/humidity against time-based thresholds using Modbus TCP/IP and MQTT
  • Developed a Python + Flask API with retry logic and a real-time web dashboard (HTML/CSS/JS) for monitoring, configuration, and control
  • Integrated fault-detection logic with automated SMS/email alerting for critical conditions
  • Prepared detailed software validation test plans covering threshold logic, communication paths, alert triggers, and system reliability

Embedded Systems Lead

Ontario Tech Racing (Formula SAE Team)

Sept 2024 – Present
  • Lead a 6-member embedded team; define coding/documentation standards, development workflows, and train/onboard new firmware contributors
  • Develop ECU firmware in Simulink (Stateflow + Embedded Coder), implementing CAN-based throttle/brake mapping, custom DBCs, and shutdown-circuit/safety-state logic
  • Implement BMS firmware in C/C++ for Analog Devices LTC6813-1: isoSPI communication, cell/temperature acquisition, PEC/open-wire diagnostics, OV/UV/OT/UT fault handling, and passive cell-balancing control
  • Validate ECU and AMS software for HV safety, enabling deterministic monitoring of cell voltages, pack current, thermistors, and automated fault-triggered shutdown sequences
  • Build on-car (ESP32 + HMI) and cloud (Firebase + TypeScript) telemetry stacks delivering real-time battery, performance, and GPS data with integrated fault detection
  • Collaborate with Vehicle Dynamics and HV Systems on telemetry/BMS integration and represent Embedded Systems during FSAE Michigan technical inspections

Software Lead

Aerecon Drone Design Team

Nov 2024 – Present
  • Implemented PID-based flight stabilization for brushless motors using PWM-driven ESCs, with orientation feedback from an IMU transmitted via wireless link
  • Developed Python visualization tools for real-time orientation/acceleration data and integrated GPS for NMEA-based position tracking
  • Engineered a computer vision pipeline on Raspberry Pi using TensorFlow + YOLO for object/face detection from onboard camera streams

Software Engineer

Ontario Tech Space and Rocketry

Nov 2024 – June 2025
  • Developed embedded firmware on STM32 microcontroller for real-time rocket tracking, integrating an IMU for orientation, a barometer for altitude, and flash memory for high-rate data logging
  • Engineered a camera mount with dual-servo actuation and computer vision, enabling automated tracking to keep rockets centered in frame during launch

Featured Projects

Reflow Oven
🔥

Reflow Oven Controller

  • Developed a Human-Machine Interface (HMI) using Nextion Editor to display real-time thermistor readings and oven status.
  • Implemented proportional-only control logic on STM32 to regulate oven temperature; tuned on/off switching behavior to maintain ±3°C accuracy using relay-driven heating.
  • Integrated UART, SPI, and I2C communication protocols for reliable data exchange between STM32, sensors, and actuators.
  • Controlled reflow oven temperature using relay modules driven by PID output.
  • Developed a responsive web interface using Async Web Server and REST API on ESP32 for remote monitoring and control of the reflow process.
STM32 ESP32 UART/SPI/I2C PID Control REST API
FSAE Dashboard
🏎️

FSAE Car Dashboard

  • Developed HMI to display speed, torque, battery temperature, voltage, gyroscope, and GPS coordinates.
  • Designed an ESP32-based dashboard that receives real-time sensor data from the car's ECU via CAN bus.
  • Built a web interface using Async Web Server and REST API to monitor vehicle data remotely.
  • Implemented AJAX and Fetch API for real-time, asynchronous data updates from the ESP32.
ESP32 CAN Bus HMI AJAX GPS
Buzz Me In
🔔

Buzz Me In - IoT Access System

  • Programmed ESP32 to control a servo motor that physically pressed a button, triggered by either buzzer sound detection or remote user command.
  • Integrated analog sound sensor to identify buzzer activation and initiate automated access response.
  • Connected system to the Blynk IoT platform to enable real-time, remote control and status monitoring via mobile app.
  • Built a dual-mode access automation system combining local sound-based triggers with cloud-connected IoT control for seamless interaction.
ESP32 IoT Blynk Servo Control Sound Detection
Camera Gimbal
📹

Computer Vision Camera Gimbal

  • Designed a real-time camera gimbal system with auto-tracking functionality, using a PID control loop to center subjects in the video frame based on facial and object recognition.
  • Integrated YOLO and OpenCV in a continuously running Python process to detect faces and calculate positional error relative to frame center.
  • Transmitted control signals over UART to a 2-axis gimbal, enabling responsive servo-based orientation adjustments.
  • Built a Tkinter-based GUI for manual override and real-time tracking visualization, supporting user interaction and tuning.
  • Achieved smooth, automated object tracking with minimal overshoot, improving target stability and real-time response during motion.
Python YOLO OpenCV PID Control UART Tkinter

Get In Touch

I'm currently seeking opportunities in embedded firmware engineering and real-time systems development. Whether you have a question, want to collaborate, or just want to say hi, feel free to reach out!