Machine learning algorithms allow computers to automatically learn from data to perform complicated tasks in vision, natural language processing and many other fields. Research at Duke addresses both theoretical and practical aspects of machine learning. In particular, researchers at Duke have made significant contributions in learning interpretable models, non-convex optimization and theoretical understanding of neural networks.
- Assistant Professor of Biostatistics & BioinformaticsAssistant Professor of Computer Science (Joint)
- Associate Professor of Computer ScienceAssociate Professor of Biochemistry (Joint)
- Yoh Family Associate Professor of Civil and Environmental Engineering
- Assistant Professor in the Thomas Lord Department of Mechanical Engineering and Materials Science
- Assistant Professor of Computer Science
- James B. Duke Distinguished Professor of Computer Science
- Anderson-Rupp Professor of Biomedical Engineering
- Cue Family Associate Professor of Computer Science
- Professor of Computer Science
- Associate Professor of Biostatistics & Bioinformatics
- Professor of Computer Science
- Professor of Computer Science
- Arthur S. Pearse Distinguished Professor of Computer ScienceProfessor of Biostatistics & Bioinformatics, Professor of Electrical and Computer Engineering (Joint)
- Associate Professor of Computer Science
- Gilbert, Louis, and Edward Lehrman Distinguished ProfessorProfessor of Electrical and Computer Engineering, Professor of Statistical Science, Professor of Biostatistics and Bioinformatics (Joint)
- Assistant Research Professor of Computer Science
- Associate Professor of Statistical Science
- Assistant Professor of Biostatistics & Bioinformatics
- Eugene Anson Stead, Jr. M.D. Associate ProfessorAssociate Professor of Biostatistics & Bioinformatics and Associate Professor of Computer Science
