About
Sameer Agarwal serves as an Affiliate Professor in the Department of Computer Science & Engineering at the University of Washington, Seattle, while concurrently working as an engineer at Google. His dual affiliation bridges academic research with industrial application in computer vision.
His primary research domains include:
- Computer Vision
- Optimization
- Machine Learning
- Image Processing
- 3D Reconstruction
- Nonlinear Least Squares
Agarwal specializes in developing algorithmic solutions for complex vision problems, particularly through algebraic methods and optimization frameworks. His work has produced influential open-source tools like Ceres Solver for bundle adjustment and contributed to practical global optimization techniques in multiview geometry.
Publication analysis reveals consistent focus on efficient computational methods across vision and graphics, with landmark contributions in multiview geometry (2008), multidimensional scaling (2007), and environment map sampling (2003). His research trajectory emphasizes translating theoretical optimization into robust, deployable systems.
No information regarding student advisement, grant funding, or laboratory teams was provided in the source materials.
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