People

Filter by application area: Astrophysics, Computational Biology, Health, Natural Language, Network Science, Neuroscience, Robotics, Speech, Vision

To find many more JHU faculty in each application area, follow links from the research page. This page lists only members of the cross-cutting machine learning group.

Core ML Faculty

  Raman Arora
Dept: Computer Science |  Centers: CLSP
Research interests: Dimensionality reduction, statistical signal processing, online learning, adversarial learning, stochastic approximation
Applications: Speech
Teaching: CS 675: Statistical Machine Learning, CS 479/679: Representation Learning

  Joel Bader
Dept: Biomedical Engineering, Computer Science |  Centers: IBBS
Research interests: Graphical models
Applications: Computational Biology, Network Science

  Alexis Battle
Dept: Computer Science, Biostatistics |  Centers: CCB, IGM
Research interests: Graphical models, transfer learning, structured regularization
Applications: Computational Biology

  Mark Dredze
Dept: Computer Science |  Centers: CLSP, HLTCOE
Research interests: Bayesian models, topic models, online learning, transfer learning, semi-supervised learning, structured prediction
Applications: Natural Language, Speech, Health
Teaching: CS 475: Machine Learning

  Jason Eisner
Dept: Computer Science, Cognitive Science |  Centers: CLSP, HLTCOE
Research interests: Structured prediction (including inference over unbounded objects), graphical models, policy learning for fast approximate inference, nonparametric Bayes, grammar induction, unsupervised learning, interactive learning
Applications: Natural Language
Teaching: CS 325/425: Declarative Methods, CS 465: Natural Language Processing, CS 765: Selected Topics in Natural Language Processing

  Donald Geman
Dept: Applied Mathematics and Statistics |  Centers: CIS, ICM
Research interests: Graphical models, small sample learning, nonparametric statistics, model selection, active testing
Applications: Vision, Computational Biology
Teaching: AMS 437: Statistical Learning with Applications, AMS 635: Topics in Bioinformatics

  Mauro Maggioni
Dept: Mathematics, Applied Mathematics and Statistics |  Centers: IDIES
Research interests: Statistical learning, high-dimensional probability, spectral graph theory, stochastic dynamical systems, time series analysis, signal processing
Applications: Vision, Health

  Carey Priebe
Dept: Applied Mathematics and Statistics, Computer Science |  Centers: CIS, HLTCOE
Research interests: Computational statistics, kernel and mixture estimates, statistical pattern recognition, statistical image analysis, dimensionality reduction, model selection, and statistical inference for high-dimensional and graph data
Applications: Network Science, Neuroscience, Vision
Teaching: AMS 730: Statistical Pattern Recognition, AMS 735: Topics in Statistical Pattern Recognition

  Suchi Saria
Dept: Computer Science, Health Policy and Management
Research interests: Graphical models, Bayesian models, time series modeling, non-parametric Bayes applications, hierarchical models, transfer learning
Applications: Health, Robotics
Teaching: CS 476/676: Machine Learning in Complex Domains (How to Become a Data Ninja)

  Ilya Shpitser
Dept: Computer Science
Research interests: Causal discovery, mediation analysis, statistical and causal inference in graphical models
Applications: Health, Computational Biology
Teaching: CS 477/677: Causal Inference

  René Vidal
Dept: Biomedical Engineering, Computer Science |  Centers: ICM, CIS, LCSR
Research interests: Manifold learning, manifold clustering, kernels for time series data, sparse representation, classification and clustering of high-dimensional datasets
Applications: Vision, Robotics, Health, Neuroscience

  Joshua Vogelstein
Dept: Biomedical Engineering |  Centers: ICM, CIS
Research interests: Statistical inference for high-dimensional and graph data
Applications: Network Science, Neuroscience, Vision

  Alan Yuille
Dept: Cognitive Science, Computer Science |  Centers: CIS
Research interests: Mathematical modeling, probabilistic inference, neural networks
Applications: Vision
Teaching: CS 485: Probabilistic Models of the Visual Cortex, CogSci 814: Research Seminar in Computer Vision

Affiliated ML Faculty

  Tamás Budavári
Dept: Physics and Astronomy
Research interests: Computational statistics, Bayesian modeling, unsupervised learning, low-dimensional embedding
Applications: Astrophysics


  Philippe Burlina
Dept: Applied Physics Laboratory, Computer Science, Wilmer Eye Institute
Research interests: Pattern recognition, anomaly detection, PDF estimation, Bayesian filtering, data assimilation
Applications: Vision

  Brian Caffo
Dept: Biostatistics
Research interests: Applications of ML to imaging problems, boosting, random forests, unsupervised clustering
Applications: Neuroscience, Computational Biology, Vision

  Kevin Duh
Dept: Human Language Technology Center of Excellence |  Centers: HLTCOE, CLSP
Research interests: Neural networks, structured prediction, semi-supervised learning, multi-objective optimization
Applications: Natural Language, Speech

  Elana Fertig
Dept: Oncology Biostatistics
Research interests: Cross-platform data and model integration, Markov chain Monte Carlo, matrix factorization
Applications: Computational Biology

  Jeffrey Gray
Dept: Chemical and Biomolecular Engineering
Research interests: Protein structure prediction and design
Applications: Computational Biology
Teaching: ChemBE 416: Current Topics in Protein Structure Prediction

  Gregory Hager
Dept: Computer Science |  Centers: CISST, LCSR
Research interests: Time-series modeling, high-dimensional problems, weakly supervised learning
Applications: Vision, Robotics, Health
Teaching: CS 361/461: Computer Vision, CS 336: Algorithms for Sensor-Based Robotics

  Justin Halberda
Dept: Psychological and Brain Sciences
Research interests: Neural networks, Bayesian models, pattern recognition
Applications: Vision

  Bruno Jedynak
Dept: Applied Mathematics and Statistics |  Centers: CIS
Research interests: Entropy pursuit, active testing, decision and classification trees, dynamic programming
Applications: Vision, Robotics
Teaching: AMS 431: Statistical Methods in Imaging

  Abhinav K. Jha
Dept: Radiology and Radiological Sciences
Research interests: Statistical signal processing, unsupervised clustering, no-gold-standard evaluation methods
Applications: Health

  Rachel Karchin
Dept: Biomedical Engineering, Computer Science |  Centers: ICM, IGM
Research interests: Supervised learning, small sample learning, graphical models
Applications: Computational Biology, Health
Teaching: BME 488/688: Foundations of Computational Biology & Bioinformatics II

  Sanjeev Khudanpur
Dept: Electrical and Computer Engineering, Computer Science |  Centers: CLSP, HLTCOE
Research interests: Statistical modeling of signals and systems, information theoretic methods in statistics
Applications: Speech, Natural Language
Teaching: ECE 447: Introduction to Information Theory and Coding, ECE 674: Information Theoretic Methods in Statistics, ECE 651: Random Signal Analysis, ECE 666: Information Extraction from Speech and Text

  Marin Kobilarov
Dept: Mechanical Engineering |  Centers: LCSR
Research interests: Planning, control, active sensing, active sampling
Applications: Robotics

  Philipp Koehn
Dept: Computer Science |  Centers: CLSP
Research interests: Discriminative structured prediction
Applications: Natural Language
Teaching: CS 768: Selected Topics in Machine Translation

  Nam Lee
Dept: Applied Mathematics and Statistics
Research interests: Statistical inference for stochastic processes
Applications: Network Science

  Daniel Naiman
Dept: Applied Mathematics and Statistics
Research interests: Statistical inference, computational statistics, probabilistic modeling
Applications: Computational Biology, Health, Finance
Teaching: AMS 430: Introduction to Statistics

  Fernando Pineda
Dept: Molecular Microbiology and Immunology
Research interests: Neural networks, signal processing, statistical physics
Applications: Computational Biology

  Daniel Robinson
Dept: Applied Mathematics and Statistics
Research interests: Optimization in machine learning
Applications: Speech
Teaching: AMS 661: Nonlinear Optimization I, AMS 662: Nonlinear Optimization II

  Michael Rosenblum
Dept: Biostatistics
Research interests: Statistical inference, construction of confidence intervals, causal inference
Applications: Health
Teaching: BioStats 646-649: Essentials of Probability and Statistical Inference I-IV

  Reza Shadmehr
Dept: Biomedical Engineering
Research interests: Bayesian learning
Applications: Computational Biology, Neuroscience
Teaching: BME 491/691: Learning Theory I

  James Spall
Dept: Applied Physics Laboratory, Applied Mathematics and Statistics
Research interests: Stochastic systems, stochastic optimization and learning, Monte Carlo methods, neural networks, feedback control systems, system identification, optimization theory, uncertainty calculation
Applications: Defense, Transportation
Teaching: AMS 663: Stochastic Search and Optimization, AMS 433: Monte Carlo Methods

  Alex Szalay
Dept: Physics and Astronomy, Computer Science
Research interests: Outlier detection, streaming data, big data, dimensionality reduction
Applications: Astrophysics

  Benjamin Van Durme
Dept: Computer Science |  Centers: CLSP, HLTCOE
Research interests: Bayesian models, Randomized/streaming algorithms
Applications: Natural Language, Speech

  Yanxun Xu
Dept: Applied Mathematics and Statistics
Research interests: Bayesian statistics, nonparametrics, graphical models, high-dimensional -omics data, clinical trial design
Applications: Computational Biology, Health
Teaching: AMS 632: Bayesian Statistics, AMS 633: Advanced Topics in Bayesian Statistics

  David Yarowsky
Dept: Computer Science |  Centers: CLSP, HLTCOE
Research interests: Co-training, weakly supervised learning
Applications: Natural Language
Teaching: CS 466: Information Retrieval and Web Agents

  Laurent Younes
Dept: Applied Mathematics and Statistics |  Centers: CIS, ICM
Research interests: Statistical properties of Markov Random fields, Image analysis, deformation analysis, shape recognition, computational anatomy
Applications: Computational Biology, Vision, Neuroscience
Teaching: AMS 640: Machine Learning, AMS 643: Graphical Models, AMS 493: Mathematical Image Analysis

  Scott Zeger
Dept: Biostatistics, Epidemiology
Research interests: Statistical inference, time series analysis, empirical Bayes, model evaluation
Applications: Neuroscience

Research Scientists

  Glen Coppersmith
Dept: Electrical and Computer Engineering |  Centers: CLSP, HLTCOE
Research interests: Graph theory, pattern recognition, statistical inference
Applications: Network Science, Natural Language, Neuroscience, Computational Biology

  Daniel DeMenthon
Dept: Applied Physics Laboratory
Research interests: Object recognition, activity recognition in video, applications of NLP to scene understanding
Applications: Vision, Robotics