Data-driven learning and adaptation.
Cornell researchers develop statistical and computational frameworks that transform how machines learn from complex data. Their work advances core mathematical foundations in statistical learning, probabilistic modeling, and optimization, while creating novel algorithms for pattern recognition and neural architectures.
Faculty studying machine learning.
Ahmed El Alaoui
Office:
Computing and Information Science Building 312
Thorsten Joachims
Jacob Gould Schurman Professor of Computer Science and Information Science, Director, Cornell AI Initiative, Vice Provost for AI Strategy
Thorsten Joachims
Office:
Computing and Information Science Building
Phone:(607) 255-5593
David S. Matteson
Professor of Statistics and Data Science, Director of the National Institute of Statistical Sciences
Matteson <at> cornell <dot> edu
David S. Matteson
Office:
Computing and Information Science Building 328
Yang Ning
Associate Professor of Statistics and Data Science, Director of Graduate Studies, Statistics and Data Science
Yang Ning
Office:
Computing and Information Science Building 306
Phone:(607) 255-3759
David Ruppert
Andrew Schultz Jr. Professor of Engineering, School of Operations Research and Information Engineering, Professor of Statistics and Data Science
Kilian Weinberger
Office:
Computing and Information Science Building 475
Martin T. Wells
Charles A. Alexander Professor of Statistical Sciences, Director of Undergraduate Studies, Statistics and Data Science
Xiaolong Yang
Teaching Professor of Statistics and Data Science, Director, MPS program in Data Science and Applied Statistics
Xiaolong Yang
Office:
Computing and Information Science Building 338
Phone:(607) 254-7273
