Carnegie Mellon University

Maria Balcan

Maria Florina Balcan

Associate Professor, Co-Director of ML Master's Programs

Address
5000 Forbes Avenue
Pittsburgh, PA 15213

Bio

Nina's main research interests are in machine learning and theoretical computer science.
Current research focus includes:
• Developing foundations and principled, practical algorithms for important modern learning paradigms. These include interactive learning, distributed learning, multi-task learning, and never ending learning. Her research formalizes and explicitly addresses all constraints and important challenges of these new settings, including statistical efficiency, computational efficiency, noise tolerance, limited supervision or interaction, privacy, low communication, and incentives.
• Machine learning and game theoretic tools for analyzing the overall behavior of complex systems in which multiple agents with limited information are adapting their behavior based on past experience, both in social and engineered systems contexts.
• Analysis of algorithms beyond the worst case and more generally identifying interesting and realistic models of computation that provide a better alternative to traditional worst-case models in a broad range of optimization problems (including problems of extracting hidden information from data).

Ziv Bar-Joseph

Ziv Bar-Joseph

Professor

Address
5000 Forbes Avenue
Pittsburgh, PA 15213

Bio

Dr. Bar-Joseph's work focuses on the analysis of high throughput biological data. His group is using machine learning, statistical algorithms and signal processing techniques to address problems ranging from experimental design to data analysis, pattern recognition and systems biology. Specifically they have focused on integrating multiple biological data sources to infer dynamic regulatory networks and other interaction networks in the cell.

William Cohen

William Cohen

Professor, Co-Director of ML Master's Programs, Director of ML Minor

Address
5000 Forbes Avenue
Pittsburgh, PA 15213

Bio

Dr. Cohen's research interests include information integration and machine learning, particularly information extraction, text categorization and learning from large datasets. He holds seven patents related to learning, discovery, information retrieval, and data integration, and is the author of more than 100 publications.

Christos Faloutsos

Christos Faloutsos

Professor

Address
5000 Forbes Avenue
Pittsburgh, PA 15213

Bio

Dr. Faloutsos is working in databases. His research interests include data mining for streams and sensors; pattern discovery in large graphs, and indexing methods for multimedia and biological databases.

Katerina Fragkiadaki

Katerina Fragkiadaki

Assistant Professor

Address
5000 Forbes Avenue
Pittsburgh, PA 15213

Bio

Dr Fragkiadaki's interests are in learning from videos, unsupervised learning, and learning policies of visual processing. She is currently looking into learning algorithms with weak supervision from videos for extracting geometry and semantics, learning a parsing of a video scene that allows prediction of its future evolution. She likes compositional  architectures of visual processing as a means towards better generalization and  general-purpose platforms to support multiple skill formation and action in the world.

Geoffrey Gordon

Geoffrey Gordon

Associate Professor, Associate Department Head for Education

Address
5000 Forbes Avenue
Pittsburgh, PA 15213

Bio

Dr. Gordon is interested in multiagent learning and planning, statistical models of difficult data (examples include natural-language text and maps of a robot's surroundings), game theory, and computational learning theory.

Matt Gormley

Matt Gormley

Assistant Teaching Professor

Address
5000 Forbes Avenue
Pittsburgh, PA 15213

Bio

Matt's research focuses on machine learning for natural language processing. His interests include global optimization, learning under approximations, hybrids of graphical models and neural networks, and applications where supervised resources are scarce.

Robert Kass

Robert Kass

Professor

Address
5000 Forbes Avenue
Pittsburgh, PA 15213

Bio

Dr. Kass has long-standing interests in the Bayesian approach to statistical inference, and has contributed to the development of Bayesian methods and their computational implementation. Over the past 10 years he has focused on statistical problems in neuroscience, especially in the analysis of signals coming from single neurons and from multiple neurons recorded simultaneously.

Ann Lee

Ann Lee

Associate Professor

Address
5000 Forbes Avenue
Pittsburgh, PA 15213

Bio

Dr. Lee's research interests are pattern analysis and high-dimensional inference. She is currently developing statistical methods and models for analyzing and representing low-dimensional structures embedded in high dimensions with noise. Her work includes spectral data analysis and multi-scale methods with applications in population genetics, astrostatistics and vision.

Roy Maxion

Roy Maxion

Research Professor

Address
5000 Forbes Avenue
Pittsburgh, PA 15213

Bio

Dr. Maxion's research is centered on learning decision models based on system and user behaviors.  His current focus is on keystroke forensics -- a type of biometric -- in which a user's typing is monitored, and a model of the typing style, or rhythm, is learned.  Based on this rhythm, users can be placed into different classes (like blood types), and users can be discriminated from one another, or even identified uniquely.  The results are used in two-factor and continuous authentication, authorship attribution, and tracking/tracing cyber-criminals across the Internet.

Tom Mitchell

Tom Mitchell

University Professor

Address
5000 Forbes Avenue
Pittsburgh, PA 15213

Bio

Dr. Mitchell works on new learning algorithms, such as methods for learning from labeled and unlabeled data. Much of his research is driven by applications of machine learning such as understanding natural language text, and analyzing fMRI brain image data to model human cognition.

Alan Montgomery

Alan Montgomery

Professor

Address
5000 Forbes Avenue
Pittsburgh, PA 15213

Bio

Dr. Montgomery works on the application of data mining and statistical analysis to solve marketing problems. His research has focused on developing price and promotional strategies from purchase transaction data and the analysis of clickstream data to predict consumer behavior in online environments.

Andrew Moore

Andrew W. Moore

Professor, Dean of the School of Computer Science

Address
5000 Forbes Avenue
Pittsburgh, PA 15213

Bio

Dr. Moore's research interest is data mining...the exciting world of algorithms for finding all the potentially useful and statistically meaningful patterns in massive sources of data.

Robert Murphy

Robert Murphy

Professor, Department Head of Computational Biology

Address
5000 Forbes Avenue
Pittsburgh, PA 15213

Bio

Dr. Murphy's principal interest is in computational biology, the application of computers to solve problems in biology. In particular, he is interested in the application of machine learning methods to biological images (especially microscope images depicting subcellular location), the application of active learning methods for analyzing and modeling complex biological phenoma, and the development of knowledge bases relating to protein properties from both text and images in online sources.

Barnabás Póczos

Barnabás Póczos

Assistant Professor

Address
5000 Forbes Avenue
Pittsburgh, PA 15213

Bio

Dr. Póczos' research interests lie in the theoretical questions of statistics and their applications to machine learning, computer vision,astronomy, and bioinformatics.

Pradeep Ravikumar

Pradeep Ravikumar

Associate Professor

Address
5000 Forbes Avenue
Pittsburgh, PA 15213

Bio

Dr. Ravikumar's research interests are in the area of statistical machine learning broadly. The core problem here has a "comptastical" imperative that combines the statistical imperative of inferring reliable conclusions from limited observations or data, with the computational imperative of doing so with limited computation. His recent research has been on the foundations of such statistical machine learning, with particular emphasis on graphical models, optimization and high-dimensional statistical inference.

Roni Rosenfeld

Roni Rosenfeld

Professor

Address
5000 Forbes Avenue
Pittsburgh, PA 15213

Bio

Dr. Rosenfeld’s ML-related work focuses on modeling the evolution of viral epidemics.  He uses machine learning, large scale simulations, network analysis and stochastic process theory to try to answer research questions such as: 

            1.  How, and to what extent, can the evolution of infectious diseases like Influenza be predicted?

            2.  How, and to what extent, is the evolution of viral disease like Influenza affected by public health interventions such as vaccination, antiviral drug use, school closures and travel restrictions?

Dr. Rosenfeld models the spread of epidemics in the population as well as the evolution of the virus itself, such as changes in its virulence, pathogenicity, drug resistance, or antigenicity (immune escape).

Ruslan Salakhutdinov

Ruslan Salakhutdinov

Associate Professor

Address
5000 Forbes Avenue
Pittsburgh, PA 15213

Bio

Dr. Salakhutdinov's primary interests lie in artificial intelligence, machine learning, deep learning, and large-scale optimization. His main research goal is to understand the computational and statistical principles required for discovering structure in large amounts of data.

Jeff Schneider

Jeff Schneider

Research Professor

Address
5000 Forbes Avenue
Pittsburgh, PA 15213

Bio

Dr. Schneider's research interests are in Machine Learning, reinforcement learning, optimization, and decision making. He has applied his methods to business applications ranging from process control, to production scheduling and inventory management, to long range strategic planning.

Nihar Shah

Nihar Shah

Assistant Professor

Address
5000 Forbes Avenue
Pittsburgh, PA 15213

Bio

Nihar's research interests lie in the areas of statistical learning, game theory, and information theory. His current focus is on problems in crowdsourcing and learning from people. 
 

Cosma Shalizi

Cosma Shalizi

Associate Professor

Address
5000 Forbes Avenue
Pittsburgh, PA 15213

Bio

Dr. Shalizi has research interests in Nonparametric model discovery of state-space/hidden Markov models and stochastic automata; dynamical-systems analysis of learning processes; applications of information theory, large deviations and ergodic theory in statistical inference; complex network models; heavy-tailed distributions.

Aarti Singh

Aarti Singh

Associate Professor

Address
5000 Forbes Avenue
Pittsburgh, PA 15213

Bio

Dr. Singh's research interests lie at the intersection of signal processing and statistical machine learning. She is interested in developing techniques that can adaptively exploit the information structure inherent in complex and large-scale systems for efficient inference. The primary thrust of her research is on bridging the gap between theoretically optimal and practically useful methods, for diverse applications ranging from the Internet, wireless and sensor networks, to bioinformatics and brain imaging.

Ryan Tibshirani

Ryan Tibshirani

Associate Professor

Address
5000 Forbes Avenue
Pittsburgh, PA 15213

Bio

Dr. Tibshirani's research interests lie broadly in statistics, machine learning, and optimization. More specifically, he is interested in high-dimensional statistics, post-selection inference, nonparametric estimation, convex optimization, and convex geometry. He likes to think about problems from different angles: applied, theoretical, and computational. He is also interested in developing methods for epidemiological forecasting, particularly flu forecasting.

Manuela Veloso

Manuela Veloso

University Professor, Department Head

Address
5000 Forbes Avenue
Pittsburgh, PA 15213

Bio

Professor Manuela Veloso works in the field of artificial intelligence, including robotics and learning. Her long-term research goal is the effective construction of teams of intelligent physical agents where cognition, perception, and action are integrated to address planning, execution, and learning tasks.

Larry Wasserman

Larry Wasserman

Professor

Address
5000 Forbes Avenue
Pittsburgh, PA 15213

Bio

Dr. Wasserman's research interests include nonparametric inference, multiple testing, asymptotic theory, causality, and applications to astrophysics and genetics.

Eric Xing

Eric Xing

Professor, Associate Head for Research

Address
5000 Forbes Avenue
Pittsburgh, PA 15213

Bio

Dr. Xing's principal research interests lie in the development of machine learning and statistical methodology; especially for solving problems involving automated learning, reasoning, and decision-making in high-dimensional and dynamic possible worlds; and for building quantitative models and predictive understandings of natural and built systems. His current work involves, 1) foundations of statistical learning, including theory and algorithms for estimating time/space varying-coefficient models, sparse structured input/output models, and nonparametric Bayesian models; 2) computational and statistical analysis of gene regulation, genetic variation, and disease associations; and 3) application of statistical learning in social networks, data mining, computer vision.

Yiming Yang

Yiming Yang

Professor

Address
5000 Forbes Avenue
Pittsburgh, PA 15213

Bio

Yiming Yang is a professor in the Language Technologies Institute and the Machine Learning Department in the School of Computer Science at Carnegie Mellon University.  Her research has centered on statistical learning methods and their applications to a variety of challenging problems, including text categorization, utility (relevance and novelty) based information distillation from temporally ordered documents, learning to order interrelated prediction tasks, modeling non-deterministic user interactions in multi-session information filtering, personalized active learning for collaborative filtering, personalized email prioritization using social network analysis, cancer prediction based protein/gene expressions in micro-array data, and protein identification from tandem mass spectra.