PostDocs and Visitors-Machine Learning Department - Carnegie Mellon University

Danny Bickson

Danny Bickson

Project Scientist

Website: http://www.cs.cmu.edu/~bickson/

I am interested in bridging machine learning and parallel/distributed computing domains, typically by borrowing ML algorithms, distributing them and applying them to real large scale problems.

Brian Murphy

Brian Murphy

Project Scientist

Website: http://www.cs.cmu.edu/~bmurphy/

My interest is in understanding the fine grain of how language is processed in the mind. I apply machine learning methods to derive models of language from the bottom up, based on large scale corpora, and on EEG, MEG and fMRI recordings of speakers' brain activity.

Saket Navlakha

Saket Navlakha

PostDoc

Website: http://www.cs.cmu.edu/~saketn/

I am interested in developing algorithms to solve problems that are inspired by biology.
I enjoy learning about network theory and evolution, graph clustering and compression,and otherwise cool optimization techniques

Burr Settles

Burr Settles

PostDoc

Website: http://www.cs.cmu.edu/~bsettles/

My work is mainly focused on application of machine learning to natural language processing and bioinformatics. In particular, I am developing efficient active learning and multiple-instance learning algorithms to facilitate real-world applications in information extraction, information retrieval, and data mining from social and biological networks.

Partha Talukdar

Partha Talukdar

PostDoc

Website: http://talukdar.net/

I am broadly interested in machine learning, natural language processing, and data integration. My recent research has focused on graph-based learning algorithms for large-scale information extraction and data integration.

Sinead Williamson

Sinead Williamson

PostDoc

I am interested in Bayesian inference for machine learning. In particular, I am interested in nonparamteric Bayesian methods, and am working on new non-parametric priors for latent variable models. I have worked on applications including text modeling, recommender systems and survival analysis.

Yisong Yue

Yisong Yue

PostDoc

Website: http://www.yisongyue.com/

 
My research interests lie in structured prediction, information retrieval, and online algorithms. I am primarily interested in designing new methods for analyzing and accessing information, as well as understanding how users interact with and derive utility from information systems.

Emily Fox

Emily Fox

Visiting Faculty, University of Pennsylvania, Wharton Statistics Department

Website: http://www.mit.edu/~ebfox/

My research interests include Bayesian and nonparametric Bayesian approaches to time-series and longitudinal data analysis. A focus of my work has been in developing methodology to flexibly learn models of complex dynamical phenomena ranging from human motion to stochastic volatility of stock indices. Recent emphasis has been on employing sparsity-inducing priors to allow extensions to high-dimensional data. This research has been motivated by a broad range of applications in statistical signal processing, machine learning, and econometrics.

Dhruv Batra

Dhruv Batra

Visiting Faculty, Toyota Technological Institute at Chicago

Website: http://ttic.uchicago.edu/~dbatra/

My research interests include machine learning and computer vision -- inference and learning in structured-output model (like undirected graphical model), max-margin methods, co-segmentation in multiple images, and interactive 3D modelling. I am also interested in applications of combinatorial optimization algorithms to learning and vision tasks.

Pengtao Xie

Pengtao Xie

Visiting Scholar

Website: http://www.cs.cmu.edu/~pengtaox/

My research interests lie in developing machine learning algorithms for large scale vision and text mining problems. Currently, I am working on web scale image understanding using parallel machine learning algorithms.