Daniel S
Research Assistant at Vector Institute
Kingston, Ontario, Canada
Summary
👤
Senior🎓
Top SchoolDaniel S is a research-focused machine learning engineer and team lead with 12 years of experience, currently pursuing a Mathematics and Computer Science degree at the University of Toronto. He leads undergraduate research at UTMIST developing generative models in weight space to tackle inverse problems like binary quantization and machine unlearning, building on flow matching, energy-based models, and equivariant architectures. His work bridges applied domains—from medical image synthesis published in IJCARs to simulation-based inference for stellar streams—and emphasizes principled theory such as optimal transport and equivariance. Daniel has a track record of turning recent ML advances into practical pipelines and publications (ICLR Workshop 2025), and he deliberately explores parameter symmetries to make models that respect network structure. Based in Kingston, Ontario, he frames his research around “AI for a better world,” combining strong theoretical curiosity with hands-on system building.
12 years of coding experience
3 years of employment as a software developer
Sekolah Lentera IndonesiaBachelor's degree Mathematics and Computer Science, Bachelor's degree Mathematics and Computer Science at University of Toronto
Github Skills (35)
spark10
python10
r10
java10
scala10
sql10
cpp10
apache-spark9
jdbc9
machine-learning9
big-data9
tensorflow9
deep-learning9
contrastive-learning9
python-client8
Programming languages (4)
Github contributions (5)
demoonism/WechatApp
Oct 2013 - Jun 2016
Contributions:3 commits, 1 push in 2 years 9 months
demoonism/Kaggle
Jun 2016 - Oct 2016
Contributions:12 commits, 10 pushes, 1 branch in 3 months
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