Faculty
Stephen Becker (assistant professor in Applied Math)
PhD Students
 Algorithmic and statistical aspects of modeling and optimization for big data analytics
 Scalable computational tools for largescale data analysis, statistical signal processing, and machine learning
 Signal and image processing using sparse and lowdimensional models
 Randomized numerical linear algebra
James Folberth (Applied Math)
 Algorithms for kmeans and Gaussian mixture models
 Adjoint operators for first order algorithms
 Blind channel estimation via optimization
Jessica Gronski (Applied Math)
 Nuclear Norms for Collaborative Filtering
 Interior Point Methods
Masters Students Derek Driggs (Applied Math, BS/MS)
 Provably accelerated algorithms for robust principal component analysis
 Parallelizable algorithms for randomized matrix decompositions
 Multilinear methods in bigdata analytics
Undergraduate Students
 Benjamin van Court (20152016, BS Electrical Engineering, BS Engineering Physics)
 Projects: fingerprint analysis using curvelets, formantbased speech editor
