visitor@petitengineer ~ %
M.Eng. graduate in ECE (AI), University of Ottawa (2026), building and evaluating machine learning systems, ranging from data pipelines and modeling to computer vision and robotics, all the while teaching and mentoring fellow engineers.
Here are some of my projects! Full project write-ups are available! :)
I am a 2026 graduate of the Master of Engineering program in Electrical and Computer Engineering at the University of Ottawa, with a concentration in artificial intelligence. My coursework pushed me beyond the standard program requirements, and I keep gravitating toward problems that blend rigorous engineering with applied machine learning.
Professionally, I have split my time between building ML systems and helping others learn the fundamentals. As a consultant machine learning engineer with Synopsys (through the university), I built an automated ML pipeline spanning preprocessing, model deployment with TensorFlow Serving, webhooks, and a small frontend—along with evaluation workflows using charts, confusion matrices, and metrics such as F1, precision, and accuracy. That work also involved MLflow for artifact organization so experiments stayed reproducible when teams iterated quickly.
I have also competed with Quanser’s autonomous racing platform, placing eighth out of forty-two teams. The stack included ROS2 in Docker on NVIDIA Jetson, OpenCV-based perception, and time-triggered driving modes for lane keeping, traffic-light state estimation (including Hough-based logic), and classic vision operators for cones, stop signs, and road edges.
Earlier roles sharpened my software discipline: at Fisheries and Oceans Canada I built a Python library with unit tests to automate validation workflows, and on the University of Ottawa Bionics Team I led electrical development for a four degree of freedom hip-mounted exoskeleton, including an efficient battery pack design.
I am most interested in applied AI that ships—autonomous systems, reliable ML pipelines, and tools that make engineers faster. Outside the lab I enjoy teaching, tinkering with embedded hardware, and exploring how perception and control come together on real platforms.
Today I am comfortable across Python, C++, TensorFlow, OpenCV, Linux, Docker, ROS2, scikit-learn, and Git, with older experience in MATLAB, VHDL, Java, and embedded style tooling. I enjoy teaching as a teaching assistant for digital systems and for circuit theory—writing lab materials, grading carefully, and helping students gain confidence with bench equipment.
