What I've Worked On

Incorporating Graph-Based Models in a Deep Learning Framework for Operational Face Recognition

We organize a collection of biometric records (gallery) into a graph structure to aid with face recognition, biographic prediction, and other tasks.

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Auto-Tuned Models (ATM)

ATM attempts to save data scientists time by automating the classifier selection process. Typically, a data scientist will manually select a classifier and attempt to tune the hyperparameters. ATM accepts a feature set and tries a variety of methods as well as find the best hyperparemters.

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Makeup Spoofing

We analyze the vulnerability of face recognition algorithms to spoof attacks, where a subject can use makeup to alter their facial appearance in order to look like someone else.

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Cross Spectral Face Recognition

We created an application that will match face images from different imaging spectra (VIS and NIR).

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Aerial Imagery Feature Evaluation

Evaluation of different features for classification of different scenes in aerial imagery.

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