Ethan Lavis

I am Ethan Lavis, a recent graduate with a Master’s in Robotics and Artificial Intelligence from the University of Glasgow, and a Bachelor’s in Automation Engineering Technology from McMaster University. With a strong foundation in machine learning, computer vision, and data science, I have gained extensive hands-on experience in developing and deploying machine learning models. My work spans various projects, including object detection, license plate recognition, and real-time embedded systems and data science. I am passionate about leveraging cutting-edge technologies such as deep learning and MLOps tools to streamline model development and optimize workflows. I thrive in collaborative environments and enjoy turning complex data into actionable insights that drive innovation and business solutions.

Throughout my career, I have had the opportunity to work in a range of roles that have shaped my technical skills and problem-solving abilities. As a Lead Developer at Systemiai, I led the development of a real-time marketing app, focusing on both front-end design and back-end integration to create a seamless user experience. At Prodomax Automation, I developed custom desktop applications and automated processes using VB.NET, SQL, and Python, which significantly improved departmental efficiency. My time as a Project Coordinator at Plan Group allowed me to collaborate with cross-functional teams, manage new initiatives, and ensure successful project outcomes. At Magna International, I worked as a Data Analyst, where I streamlined data processing tasks, developed models to improve decision-making, and increased task efficiency by 900%. These experiences have honed my ability to apply technical knowledge to solve real-world challenges and deliver meaningful results.

During my time at the University of Glasgow, where I pursued a Master of Science in Robotics and Artificial Intelligence, I achieved an honors degree for outstanding academic performance. My coursework covered a broad spectrum of topics, including deep learning, conversational interfaces, data science, and robotics. I worked on several practical projects, applying machine learning techniques and developing models from scratch, which enhanced my skills in areas like computer vision and automation. This experience not only deepened my technical expertise but also prepared me for real-world applications in AI and robotics.