Raif Rustamov

Recent Alum

Email: raifrustamov at gmail dot com
Website: https://sites.google.com/site/raifrustamov/

Research Statement

    My research interests lie in developing tools for processing of geometric data -- triangle meshes, volumes, point clouds, and weighted graphs -- arising in computer graphics, computer aided design, protein bioinformatics, medical imaging, and analysis of high-dimensional data sets. My current work focuses on the use of spectral methods and their extensions for processing of large collections of deformable surfaces and volumes. Another thread in my current research is constructing wavelets and other multiscale structures suitable for analyzing of and on geometric data.

Recent Publications

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J. Solomon, R. Rustamov, L. Guibas, and A. Butscher, Earth Mover’s Distances on Discrete Surfaces, Proc. SIGGRAPH (2014).
@article{srgb-emdds-14,
 author = {Solomon, Justin and Rustamov, Raif and Guibas, Leonidas and Butscher, Adrian},
 title = {Earth Mover's Distances on Discrete Surfaces},
 journal = {ACM Trans. Graph.},
 volume = {33},
 number = {4},
 month = jul,
 year = {2014},
 pages = {67:1--67:12},
} 
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J. Solomon, R. Rustamov, L. Guibas, and A. Butscher, Wasserstein Propagation for Semi-Supervised Learning, Proc. International Conference on Machine Learning (ICML 2014).
@inproceedings{srgb-wpssl-14, 
    Author = {Justin Solomon and Raif Rustamov and Guibas Leonidas and Adrian Butscher}, 
    Url = {http://jmlr.org/proceedings/papers/v32/solomon14.pdf}, 
    Title = {Wasserstein Propagation for Semi-Supervised Learning}, 
    Pages = {306--314}, 
    Year = {2014}, 
    Booktitle = {Proceedings of the 31st International Conference on Machine Learning} 
   }
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N. Hu, R. Rustamov, and L. Guibas, Stable and Informative Spectral Signatures for Graph Matching, CVPR2014
@article{hrg-sissgm-2014,
author = {Nan Hu and Raif Rustamov and Leonidas Guibas},
title = {Stable and Informative Spectral Signatures for Graph Matching},
journal = {CVPR},
year = {2014},
}
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R. Rustamov, L. Guibas, Hyperalignment of Multi-Subject fMRI Data by Synchronized Projections, NIPS Workshop on Machine Learning and Interpretation in Neuroimaging (MLINI) 2013.
@incollection{rg-hmsfdsp-2013,
title ={Hyperalignment of Multi-Subject {fMRI} Data by Synchronized Projections},
author={Raif M. Rustamov and Leonidas Guibas},
booktitle = {Proceedings of the 3rd NIPS Workshop on Machine Learning and Interpretation in Neuroimaging ({MLINI})},
year = {2013},
}
Teaser Image
Raif M. Rustamov and Leonidas Guibas, Wavelets on Graphs via Deep Learning, NIPS 2013
@incollection{rg-wgdl-2013,
title ={Wavelets on Graphs via Deep Learning},
author={Raif M. Rustamov and Leonidas Guibas},
booktitle = {Advances in Neural Information Processing Systems 26},
year = {2013},
}
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Raif M. Rustamov, Maks Ovsjanikov, Omri Azencot, Mirela Ben-Chen, Frederic Chazal, and Leonidas Guibas. Map-based exploration of intrinsic shape differences and variability. ACM Trans. Graph. (Proc. SIGGRAPH) 32, 4, Article 72 (July 2013).
@article{roabcg-mbeisdv-2013,
 author = {Rustamov, Raif M. and Ovsjanikov, Maks and Azencot, Omri and Ben-Chen, Mirela and Chazal, Fr{'e}d{'e}ric and Guibas, Leonidas},
 title = {Map-based exploration of intrinsic shape differences and variability},
 journal = {ACM Trans. Graph.},
 issue_date = {July 2013},
 volume = {32},
 number = {4},
 month = jul,
 year = {2013},
 issn = {0730-0301},
 pages = {72:1--72:12},
 articleno = {72},
 numpages = {12},
 url = {http://doi.acm.org/10.1145/2461912.2461959},
 doi = {10.1145/2461912.2461959},
 acmid = {2461959},
 publisher = {ACM},
 address = {New York, NY, USA},
 keywords = {data-driven methods, shape comparison, shape matching, shape variability},
} 
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Nan Hu, Raif M. Rustamov, and Leonidas Guibas, Graph Matching with Anchor Nodes: A Learning Approach, CVPR2013
@InProceedings{hrg-gmanla-2013,
author = {Nan Hu and Raif M. Rustamov and Leonidas Guibas},
title = {Graph Matching with Anchor Nodes: A Learning Approach},
journal = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2013},
pages = {2906-2913}
}
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