Wonho Bae
About Wonho Bae
Wonho Bae is a research intern currently at Borealis AI and a research assistant at The University of British Columbia, with a focus on machine learning and computer vision. He has a diverse academic background, holding degrees in economics, statistics, and computer science, and has worked in various research roles across multiple institutions.
Work at Borealis AI
Wonho Bae has worked at Borealis AI as a Research Intern in two separate periods. His first tenure was in 2022, where he contributed for four months in Vancouver, British Columbia, Canada. He returned to Borealis AI in 2023, continuing his role as a Research Intern for one year. His work primarily focuses on advancing research in machine learning and computer vision.
Current Role at The University of British Columbia
Since 2020, Wonho Bae has been employed as a Research Assistant at The University of British Columbia in Vancouver, British Columbia, Canada. His research activities have contributed to advancements in machine learning and computer vision. He is also pursuing a Doctor of Philosophy (PhD) in Computer Science at the same institution, expected to complete in 2025.
Education and Expertise
Wonho Bae has a strong academic background that includes a progression from economics to statistics, and ultimately to computer science and machine learning. He earned an Associate's degree in Economics from Santa Monica College from 2011 to 2013. He then completed a Bachelor's degree in Statistics at the University of California, Berkeley from 2013 to 2017, followed by a Master of Science in Computer Science at the University of Massachusetts Amherst from 2018 to 2020.
Background in Military Service
Before his academic pursuits, Wonho Bae served in the Republic of Korea Army as a Signals Intelligence Analyst from 2015 to 2016 for one year in Chuncheon, Gangwon-do, Korea. This experience contributed to his analytical skills and understanding of complex systems.
Research Focus and Experience
Wonho Bae's research focus includes machine learning and computer vision, particularly in low supervision regimes such as self-supervised, weakly supervised, active, and meta learning. He has gained experience in both academic and industry research environments, having worked as a Research Assistant at the University of California, Berkeley, and Seoul National University from 2017 to 2020.