• 🚀 Payload Subsystem Lead — SC-FRYER CubeSat @ Space Concordia Spacecraft Division (Aug 2025 — Jan 2026)
  Leading the development of an AI-driven payload subsystem for a CubeSat mission:

  • Led an AI-based payload subsystem developed under the Canadian Space Agency’s CUBICS program
  • Defined subsystem requirements and interfaces with Electrical, Command & Data Handling, and Mechanical teams
  • Designed and implemented Python pipelines to train, test, and validate ML models, achieving ~82% inference accuracy on mission datasets
  • Led payload system integration, interface definition, and verification activities
  • Implemented and validated software on an AMD Zynq UltraScale+ FPGA SoC for onboard data processing
  • Brought up and tested HW/SW platforms using vendor documentation and reference designs
  • Debugged hardware–firmware boundary issues using waveform-level analysis, logs, and iterative bring-up testing

• 🤖 Mechatronics Engineer — ARES Drone @ Space Concordia Robotics Division (2025 — Present)
  Working on the full-stack development of an autonomous drone system from the ground up:

  • Designed and built the drone platform using a Tarot 650 frame and Matek F405 flight controller, contributing both mechanical design and full system integration
  • Developed embedded software and communication pipelines enabling coordination between the drone and ground station / rover systems
  • Implemented and tuned PID control systems for stable flight and actuator control
  • Applied Kalman filtering in Simulink to improve IMU fault detection and state estimation robustness
  • Integrated computer vision (YOLO) for onboard perception tasks
  • Developing algorithms for radio repeater systems to extend communication range
  • Performed hands-on flight testing, debugging, and system validation
  • Collaborated with a graduate research team on a stratospheric balloon project for experimental payload testing

• 🔍 Applied AI/ML + Image Processing Research (Concordia University)
  Recently contributed to a research project on rotation-aware object detection in aerial imagery,
  including multi-dataset evaluation (HRSC2016, DOTA, NWPU) and PyTorch implementation
  — as described in my uploaded paper. :contentReference[oaicite:1]{index=1}

• 🧠 Research areas I'm involved/interested in:

  • Aerial & satellite image analysis
  • Oriented object detection
  • Deep learning for onboard systems
  • Signal & sensor processing
  • Applied computer vision
  • Intelligent embedded systems
  • AI for resource-constrained environments (space, robotics, edge devices)

I work across the full stack of intelligent hardware–software systems:

• Embedded Systems & Firmware (C, C++, FPGA Xilinx, ESP32, STM32)
• FPGA Development (Verilog/VHDL, hardware pipelines, DSP, image-processing accelerators)
• Electronics & PCB Design (KiCad, Altium; digital/analog interfaces, sensor boards)
• Robotics & Mechatronics (control systems, actuation, state estimation)
• AI/ML for Edge Devices (quantization, optimization, deployment)
• Computer Vision + Image Processing (OpenCV, PyTorch, RGB/NIR pipelines)
• CAD (mechanical drawing, SolidWorks)

• Languages: C, C++, Python, Verilog/VHDL, MATLAB, HDL-based tooling
• Frameworks: PyTorch, OpenCV, ROS/ROS2
• Hardware: FPGAs, microcontrollers, SBCs (Raspberry Pi, Jetson), sensors, NIR cameras
• Dev Tools: Git, Linux, Docker, Vivado, MATLAB/Simulink, KiCad
• Other Interests: control theory, competitive programming, spacecraft electronics

• Building robots and real-time systems
• Designing electronics and debugging on the oscilloscope
• Writing clean embedded firmware
• Implementing FPGA accelerators for heavy vision workloads
• Doing AI/ML research on real datasets with real constraints
• Working on anything related to space or aerospace autonomy
• Exploring new ideas at the intersection of hardware, software, and intelligence