Tristan Engst is a CS PhD student at Simon Fraser University with 11 years of experience building and evaluating machine learning and computer vision systems. His research focuses on learned neural representations and algorithms that make those representations more sample-efficient, building on prior work that reduced labeling needs by an order of magnitude. He has translated research into impact through internships and projects—improving ontology extraction richness 4x at Parabole.ai and boosting model F1 beyond IBM Watson via Bayesian tuning at KPMG. An award-winning TA and undergraduate researcher from Cornell, Tristan blends rigorous academic training with practical engineering: he routinely rewrote pipelines for better linguistic structure and automated data-cleaning macros that doubled throughput. He’s currently seeking research-oriented internship opportunities and brings a knack for squeezing more signal out of limited labels.
11 years of coding experience
1 year of employment as a software developer
Regents Diploma with Advanced Designation, Mastery in Science and Mathematics, Regents Diploma with Advanced Designation, Mastery in Science and Mathematics at Ithaca High School
Bachelor of Science - BS, Computer Science, Bachelor of Science - BS, Computer Science at Cornell University
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Simon Fraser University
Contributions:2 PRs, 991 pushes, 2 branches in 2 months
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