Calgary, Alberta, Canada
I'm a Software Engineering student at the University of Calgary with a passion for building intelligent, real-world systems that blend hardware and software. My interests lie in embedded systems, real-time data processing, and how low-level systems interact with the physical world. At BMERIT, I developed embedded systems for a biomedical mobility-assistive device, programming ESP32 microcontrollers to collect patient data from various sensors and transmit it via BLE to a custom frontend. At Schneider Electric, I applied data analysis and process mapping techniques to improve industrial workflows. On the Schulich Space Rover Team, I contributed to sensor integration and computer vision systems, gaining hands-on experience in robotics and embedded development. I'm especially drawn to the intersection of data, devices, and design, whether that’s through embedded development, AI/ML integration, or full-stack software systems. I value clean, maintainable code, systems thinking, and solving meaningful problems that bridge software and hardware. Currently seeking a full-time internship for Fall 2025 in embedded systems, software development, or data engineering, where I can grow with a passionate team and contribute to impactful, interdisciplinary projects. Let’s connect!
- Contributed to the development of a novel assistive mobility device designed to collect and analyze real-time gait and movement data using embedded systems and sensors (e.g., IR, Hall Effect). - Programmed ESP32 microcontrollers to interface with multiple sensors and transmit data via Bluetooth Low Energy (BLE) to a custom React-based frontend. - Collaborated closely with researchers and clinicians to translate user needs into functional prototypes and participated in iterative testing and debugging cycles. - Gained hands-on experience with biomedical device prototyping, embedded systems design, Bluetooth communication, and real-world data visualization techniques.
- Explored process mining techniques to analyze and optimize internal workflows related to energy management and automation systems. - Used Python and data visualization tools to clean, transform, and analyze operational data. - Created clear, actionable insights through dashboards and reports to support strategic decision-making and improve process performance. - Collaborated with engineers and analysts to align findings with technical and business requirements, contributing to continuous improvement initiatives. - Gained hands-on experience with industrial data systems and developed a deeper understanding of digital transformation in the energy sector.