By Andrea Yip on March 18, 2021
In our latest round up of data and AI portfolios, we are featuring recent AI graduates that we met through our collaboration with the Vector Institute. We’ve highlighted projects from each portfolio, showcasing the diversity of ways that folks share and talk about their work.
From graduates who specialize in AI translation and communication to computer vision researchers, we hope you’re inspired by this group of AI graduates and their fantastic collection of portfolios!
If you’re looking for advice on building out your own data/AI portfolio, check out our checklist and our webinar with the Vector Institute on accelerating your career via your online presence.
Sara is a graduate student pursuing her Master of Applied Science at the University of Guelph. She highlights several projects on her site, including one where she co-developed a humanoid robot-infant interaction experiment. The study explored how infants reacted to a humanoid robot that emitted social cues compared to one that did not. Sara was responsible for programming the robot.
Devin is a graduate student completing his Master of Management in AI at Queens University. He organizes his projects by his areas of expertise including computer vision, machine learning, and product management. In one of his computer vision projects, Devin built an advanced lane-finding algorithm using distortion correction, image rectification, color transforms, and gradient thresholding.
Hannah is a recent graduate of the Master of Applied Science in Engineering and AI at the University of Guelph. Her portfolio showcases a diversity of project work including one where she uses machine learning to help predict the placement of Field Programmable Gate Arrays (FPGAs), chips where the hardware on the chip can be changed, or reconfigured, depending on the design.
Jeff is a PhD student in computational biology at the University of Toronto. His research focuses on building computational methods to reconstruct the evolutionary history of cancer in individual patients. He includes his blog, papers, and talks on his website. Check out his most recent talk on Intelligent Systems for Molecular Biology.
Shakti is a graduate student in the Applied Computing program at the University of Toronto. In his portfolio, he provides a brief 2-3 sentence summary of each project and links to his papers and code.
Diana recently graduated with her Master of Management in AI from Queens University. She links to a project wiki that describes her work in a Kaggle competition focused on extracting text related to emotions found in tweets. Diana, an AI translator, tells the story of her project, from problem definition to lessons learned.
Nil is a data scientist pursuing a PhD in the Department of Molecular Genetics at the University of Toronto. Her website serves as a landing page for all things Nil: from her CV to Github to Google Scholar. She provides a deep dive into her PhD thesis, focused on developing and implementing computer vision and machine learning approaches to analyze microscopy images and elucidate gene function.
Shashank is completing his Master of Applied Science in AI at the University of Guelph. He profiles his projects on Github. In one of his projects, he built a simple clone of the Flappy bird game in pygame. He used character sprites, backgrounds and sound effects from the popular Among Us game.
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