Martin Magill
About Martin Magill
Martin Magill is a Machine Learning Researcher currently working at Borealis AI and Ontario Tech University. He has a strong academic background with a PhD in Modelling and Computational Science and extensive experience in various research and co-op roles.
Current Role at Borealis AI
Martin Magill currently serves as a Machine Learning Researcher at Borealis AI, a position he has held since 2022. His work focuses on advancing the field of machine learning through innovative research and application of deep learning techniques. Borealis AI is known for its commitment to developing cutting-edge artificial intelligence solutions, and Martin contributes to this mission by exploring the integration of differential equations with deep neural networks.
Education and Expertise
Martin Magill has a strong educational background in computational science and applied mathematics. He completed his Doctor of Philosophy (PhD) in Modelling and Computational Science at Ontario Tech University from 2017 to 2021. Prior to that, he earned a Master of Science (MSc) in the same field from 2014 to 2016. Additionally, he holds a Bachelor of Mathematics (BMath) in Applied Mathematics with a Physics Option from the University of Waterloo, which he completed from 2009 to 2014.
Professional Experience
Martin Magill has accumulated diverse professional experience through various co-op positions and research roles. He worked as a co-op student at AECL multiple times between 2008 and 2013, gaining experience in Deep River, Ontario. His other co-op roles include positions at Grand River Hospital, SNOLAB, and Health Canada in 2012, as well as an undergraduate research assistant role at the University of Waterloo in 2014. He also served as a Postgraduate Affiliate at the Vector Institute from 2019 to 2021.
Research Focus
Martin's research is situated at the intersection of computational science and deep learning. He focuses on the integration of differential equations with deep neural networks, aiming to enhance the capabilities of machine learning models. This research area is critical for developing more accurate and efficient algorithms that can solve complex problems across various scientific and engineering domains.
Background
Martin Magill has been involved in academia and research since 2014, currently working as a Graduate Student at Ontario Tech University for the past ten years. His extensive background in machine learning and computational science has equipped him with the skills necessary to contribute significantly to the field. His experiences across multiple institutions and research settings have shaped his expertise and focus in machine learning.