I am a third year Ph.D. student in the
Machine Learning Department
My advisor is Aarti Singh
I received a B.Sc. in Computer Science from Duke University, where I was a member of the
Systems Networking Research Group (SyNRG)
advised by Romit Roy Choudhury
My research was in mobile computing, specifically designing new methods of utilizing sensors
on mobile devices for localization.
I am currently researching feature selection methods for high dimensional, noisy, and not fully observed clustering problems.
I am also interested in so called safe
semi-supervised learning methods, i.e. semi-supervised learning algorithms that take advantage of unlabeled data when possible, but gracefully reduce to supervised learning
when unlabeled data are not helpful.
My other areas of interest include general entropy learning theory, and subspace detection and learning under compressive measurment models.
Density-Sensitive Semisupervised Inference
Martin Azizyan, Aarti Singh, Larry Wasserman
Annals of Statistics, 2013. (accepted; arXiv version)
Subspace detection of high-dimensional vectors using compressive sampling
Martin Azizyan, Aarti Singh
IEEE Statistical Signal Processing Workshop, 2012. (full text of revised version)
"Did You See Bob?": Human Localization using Mobile Phones
Ionut Constandache, Xuan Bao, Martin Azizyan, Romit Roy Choudhury
ACM MobiCom, September 2010. (full text)
SurroundSense: Mobile Phone Localization Via Ambience Fingerprinting
Martin Azizyan, Ionut Constandache, Romit Roy Choudhury
ACM MobiCom, September 2009. (full text)