UnifyID Labs

UnifyID Labs is the research-oriented arm of UnifyID. It focuses on research collaborations with both academia and industry in the areas of security, machine learning, behavioral biometrics, and passive authentication.

Publications and Presentations

Dian Ang Yap, Nicholas Roberts, Vinay Uday Prabhu

Grassmannian Packings in Neural Networks: Learning with Maximal Subspace Packings for Diversity and Anti-Sparsity

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Nicholas Roberts, Vinay Uday Prabhu, Dian Ang Yap, Matthew McAteer

Garbage in, model out: Weight theft with just noise

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Dian Ang Yap, Nicholas Roberts, Vinay Uday Prabhu

Deep Connectomics Networks: Neural Network Architectures Inspired by Neuronal Networks

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Fall 2019 AI Fellowship

The UnifyID AI Fellowship is a great opportunity for students and researchers to engage in groundbreaking, interdisciplinary research, and investigate relevant questions that have been uncovered through the research and development of UnifyID’s core technologies. These cover a broad set of domains in Security, Machine Learning, Higher Order Signal Processing, Optimization Theory, On-Device ML, Passive-Behavioral Motion Analysis, and last but not least AI Ethics and Journalism in AI.

Fall 2019 Fellows:
Angela Gu, Avoy Datta, Bowen Jing, Chris Waites, Daniel Wu, Andrew Guan, Jonathan Mak, Katherine Lamb