Machine Learning Groups

The Machine Learning Groups of Microsoft Research include a set of researchers and developers who push the state of the art in machine learning. We span the space from proving theorems about the math underlying ML, to creating new ML systems and algorithms, to helping our partner product groups apply ML to large and complex data sets.


Sumit Basu 

Interactive machine learning, interactive tutoring systems, educational data mining, dynamic languages for scientific computation, machine learning for creativity applications, machine learning for systems applications, auditory analysis and synthesis


Misha Bilenko 

Learning from user behavior, predictive personalization, scaling up machine learning, learning applications in online advertising, adaptive similarity functions, building tools for improving predictive accuracy

Leon Bottou

Large-scale learning, statistical machine learning, structured learning systems, stochastic gradient learning, transduction, causality and machine learning, kernel methods, neural networks, interactive machine learning, reasoning and machine learning, machine learning and semantics, compound image compression


Chris Burges (Manager)

Machine learning algorithms, optimization, machine reading, ranking for web search, dimension reduction, audio fingerprinting 

Denis Charles

Algorithms, Complexity Theory, Graph Theory, Game Theory and Mechanism Design, Web Scale Computing, Computational Number Theory, Algebraic Number Theory and Algebraic Geometry 


Max Chickering  

Practical applications of machine learning, learning graphical models, human computation and methods for coxswain displacement


Silviu-Petru Cucerzan 

Natural language processing, information extraction from large text collections, semantic modeling, information retrieval


Ofer Dekel 

Supervised learning algorithms, learning theory, online prediction, optimization, building large-scale machine learning systems, web search


Ran Gilad-Bachrach 

Learning theory, hypothesis testing, continuous sensing, machine learning engineering principles


Asela Gunawardana 

Temporal modeling and forecasting of events, modeling user intent, recommender systems, online advertising


Chuck Jacobs 

Dynamic language tools, machine learning, GPGPU, data visualization, adaptive document layout


Lihong Li

Reinforcement learning, multi-armed bandit, online learning, recommendation, computational advertising


Chris Meek (Manager)

Graphical models (from various perspectives: inference, learning, relational, representation, algebraic, causal), temporal models (events, sequence data), and scalable algorithms


Andrzej Pastusiak 

Machine learning algorithms, natural language modeling, HPC, GPGPU


John Platt (Manager)

Improving the data/human interface, fast machine learning, automatically discovering representations


Erin Renshaw 

Software development, large-scale data analysis and algorithms, numerics


Matthew Richardson 

Web search, online advertising, query log analysis, online privacy, community question answering, social networks, Markov logic, collective knowledge, crowdsourcing


Patrice Simard (Manager)

Interactive machine learning, active labeling, active featuring, large data sets, generalization, regularization, exploitation/exploration, neural networks


Lin Xiao 

Convex optimization, first-order and online algorithms, interior point methods, optimization software, machine learning algorithms, sparsity recovery, parallel and distributed computing


Scott Yih 

Semantic similarity and relevance, spam filtering, structured-output learning, information extraction, natural language processing, information retrieval


Dengyong Zhou 

Supervised learning, algorithmic crowdsourcing (human computing), learning representations, large-scale learning, nonparametric statistics, probabilistic modeling, and their applications to web search and social media


Applying for Positions

  • Apply here for a Postdoctoral Researcher position for 2014 and have your application material (including references) sent to
  • Apply here for a summer internship for 2014 and inform us that you have applied by emailing We only consider Ph.D. students. (closed)
Recent Publications