John Wright
John Wright develops theory and algorithms for learning from high-dimensional data. His research studies sparse vectors, low-rank matrices and nonconvex optimization. Wright earned an Illinois computer-engineering bachelor’s degree in 2004, an electrical-engineering master’s in 2007 and a doctorate in 2009. He conducted research at Microsoft Research Asia from 2009 to 2011. His later shared work addressed robust sparse-vector and low-rank matrix recovery from corrupted observations. His group develops computational methods to recover low-complexity models from noisy, incomplete or corrupted observations. Collaborators worked with him on sparse dictionary learning and geometric analysis of nonconvex learning problems.
- Now at
- Columbia University
- Works
- 141
- Citations
- 32,734
- h-index
- 42
Publication numbers from OpenAlex, as of 14 October 2026.
Timeline
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2004–2009
Illinois engineering education
Wright earned an Illinois computer-engineering bachelor’s degree in 2004, an electrical-engineering master’s in 2007 and a doctorate in 2009.
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2009–2011
Microsoft Research Asia
He conducted research at Microsoft Research Asia from 2009 to 2011. His later shared work addressed robust sparse-vector and low-rank matrix recovery from corrupted observations.
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As of October 2026
Structured recovery and learning
His group develops computational methods to recover low-complexity models from noisy, incomplete or corrupted observations. Collaborators worked with him on sparse dictionary learning and geometric analysis of nonconvex learning problems.
Sources and credits
Photo: www.engineering.columbia.edu; John Wright profile photograph; creator not stated. License: Not stated by source. Source: engineering.columbia.edu. Cropped to a square and resized. Ask us to remove or replace this photo.