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
Nicholas Roberts, Vinay Uday Prabhu, Dian Ang Yap, Matthew McAteer
Garbage in, model out: Weight theft with just noise
Dian Ang Yap, Nicholas Roberts, Vinay Uday Prabhu
Deep Connectomics Networks: Neural Network Architectures Inspired by Neuronal Networks
Vinay Prabhu, John Whaley
On grey-box adversarial attacks and transfer learning
Aidan Clark, Vinay Prabhu, John Whaley
A Contextual Discretization framework for compressing Recurrent Neural Networks
Vinay Prabhu, John Whaley
On Lyapunov exponents and adversarial perturbations
Vinay Prabhu, John Whaley
Smile in the face of adversity much? A print based spoofing attack
Aidan Clark, Vinay Prabhu, John Whaley
Weight initialization strategies for Binarized Neural Networks
Nikhil Mehta, Vinay Prabhu, John Whaley
Memorization in Binarized Neural Networks
Vinay Prabhu, John Whaley
Vulnerability of deep learning-based gait biometric recognition to adversarial perturbations
Vinay Prabhu, Paulo Aranted, John Whaley
Multi-sensor data compression using tensor decompositions: A SenTenCE and more
Vinay Prabhu, John Whaley
AcctionNet: A Dataset Of Human Activity Recognition Using On-phone Motion Sensors
Vinay Prabhu, Ph.D. 
John Whaley, Ph.D. 
Professor Lorrie Cranor 
Professor Lujo Bauer 
Professor Dawn Song 
Professor Mayank Goel 
Professor Vishnu Boddeti 
Professor Dan Boneh 
Professor Weiqing Gu 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.
Fellows:
Angela Gu, Avoy Datta, Bowen Jing, Chris Waites, Daniel Wu, Andrew Guan, Jonathan Mak, Katherine Lamb