Toyota Technological Institute at Chicago
6045 S. Kenwood Ave.
Chicago, IL 60637
e-mail gregory at ttic dot edu
tel +1 (773) 834-2572
fax +1 (773) 834-9881
|Research||Teaching||Papers||Personal||Code, data etc.||Vision reading group|
Since February 2008, I am an Assistant Professor at TTI-Chicago, a philanthropically endowed
academic computer science institute located on the University of Chicago campus.
I also hold a part-time faculty appointment at the University of Chicago Department of Computer Science.
We at TTI-Chicago continue to admit students to our PhD program. Please contact me for details.
Prior to coming to TTI-Chicago, I was a post-doctoral researcher at the Department of Computer Science of Brown University where I worked with Michael Black. I received my PhD degree at MIT where I worked at CSAIL with Trevor Darrell on computer vision and machine learning. My thesis topic was Learning Task-Specific Similarity.
Before coming to MIT, I was a graduate student in the Computer Science Department of the Technion, Israel Institute of Technology in Haifa, Israel, where I got my MSc thesis under the advisement of Ran El-Yaniv and Yoram Baram. I got my undergraduate degree in Math and CS from Hebrew University in Jerusalem, Israel.
My CV: PDF
S. Trivedi, D. McAllester, G. Shakhnarovich, "Discriminative Metric Learning by Neighborhood Gerrymandering", NIPS 2014 (to appear)
E. Ahmed, G. Shakhnarovich, S. Maji, "Knowing a Good HOG Filter When You See It: Efficient Selection of Filters for Detection", ECCV 2014 (oral) [pdf]
We are looking for a post-doc in machine learning/vision/NLP applied to sign language analysis.
S. Trivedi, J. Wang, S. Kpotufe, G. Shakhnarovich, "A Consistent Estimator of the Expected Gradient Outerproduct", UAI 2014 (to appear) [pdf]
S. Maji and G. Shakhnarovich, "Part and Attribute Discovery from Relative Annotations", IJCV, vol. 108(1-2), 2014 [pdf]
I have received the IBM Faculty Award
PhD thesis, MIT, 2006: Learning Task-Specific Similarity. Advisor: Trevor Darrell.
MsC thesis, Technion, 2001: Statistical Data Cloning for Machine Learning. Advisors: Ran El-Yaniv and Yoram Baram.
T. Kim, G. Shakhnarovich, K. Livescu, "Fingerspelling recognition with semi-Markov conditional random fields", ICCV 2013 [pdf]
K. Gimpel, D. Batra, C. Dyer, G. Shakhnarovich, "A Systematic Exploration of Diversity in Machine Translation", EMNLP 2013 [pdf]
P. Kisilev, E. Barkan, G. Shakhnarovich, A. Tzadok, "Learning to detect lesion boundaries in breast ultrasound images", Breast Imaging Workshop, MICCAI 2013 [pdf]
P. Yadollahpour, D. Batra, G. Shakhnarovich, "Discriminative Re-Ranking of Diverse Segmentations", CVPR 2013 [pdf]
Z. Ren, G. Shakhnarovich, "Image Segmentation by Cascaded Region Agglomeration", CVPR 2013 [pdf]
S. Maji, G. Shakhnarovich, "Part Discovery from Partial Correspondence", CVPR 2013 [pdf]
D. Glasner, M. Galun, S. Alpert, R. Basri, G. Shakhnarovich, "Viewpoint-aware object detection and continuous pose estimation", Image and Vision Computing, 30(12), 2012.
D. Batra, P. Yadollahpour, A. Guzman, G. Shakhnarovich, "Diverse M-Best Solutions in Markov Random Fields", ECCV 2012 (oral) [pdf including supplementary material]
T. Kim, K. Livescu, G. Shakhnarovich, "American Sign Language Fingerspelling Recognition with Phonological Feature-Based Tandem Models", IEEE SLT 2012 [pdf]
S. Maji, G. Shakhnarovich, "Part Annotations via Pairwise Correspondence", 4th Workshop on Human Computation, AAAI 2012 [pdf]
G. Shakhnarovich, B. Moghaddam, "Face Recognition in Subspaces", In Handbook of Face Recognition, S. Z. Li and A. K. Jain, Ed. Springer-Verlag, 2nd edition, 2011. [pdf]
C. Vargas-Irwin, G. Shakhnarovich, P. Yadollahpour, J. M. K. Mislow, M. J. Black, J. P. Donoghue, "Decoding Complete Reach and Grasp Actions from Local Primary Motor Cortex Populations", The Journal of Neuroscience, 2010.
A. Ritz, G. Shakhnarovich, A. R. Salomon, B. J. Raphael, "Discovery of Phosphorylation Motif Mixtures in Phosphoproteomics Data". Bioinformatics, 2009. abstract
C. Demiralp, G. Shakhnarovich, S. Zhang, D. H. Laidlaw, "Slicing-based coherence measure for refining clusters of 3D curves." Proceedings of MICCAI Conference, 2008. [pdf]
P. K. Artemiadis, G. Shakhnarovich, C. Vargas-Irwin, J. P. Donoghue, M. J. Black, "Decoding grasp aperture from motor-cortical population activity", IEEE Conf. on Neural Engineering, 2007. [pdf]
G. Shakhnarovich, S.-P. Kim, M. J. Black, "Nonlinear physically-based models for decoding motor-cortical population
activity", NIPS 2006. [pdf]
L. Taycher, G. Shakhnarovich, D. Demirdjian, and T. Darrell,
"Conditional Random People: Tracking Humans with CRFs and Grid
Filters". Proceedings IEEE Conf. on Computer Vision and Pattern
Recognition, 2006. [pdf]
Also in MIT CSAIL Technical Report MIT-CSAIL-2005-079, 2006 [pdf]
G. Shakhnarovich, J. Fisher, "Performance of Approximate Nearest Neighbor Classification". Poster presented at Machine Learning Workshop at Snowbird, 2006, with preliminary results (work in progress).
G. Shakhnarovich, T. Darrell, P. Indyk, editors, "Nearest-Neighbors methods in Learning and Vision: Theory and Practice". MIT Press, 2006.
D. Demirdjian, L. Taycher, G. Shakhnarovich, K. Grauman, T. Darrell, "Avoiding the Streetlight Effect: Tracking by Exploring Likelihood Modes", Proceedings of the International Conference on Computer Vision,2005. [pdf]
L. Ren, G. Shakhnarovich, J. Hodgins, H. Pfister, P. Viola, "Learning Silhouette Features for Control of Human Motion", ACM Transactions on Graphics,2005. [pdf]
O. Aranjelovic, G. Shakhnarovich, J. Fisher, R. Cippola, T. Darrell, "Face Recognition with Image Sets Using Manifold Density Divergence", Proceedings IEEE Conf. on Computer Vision and Pattern Recognition, pp. 581--588, 2005. [pdf]
K. Grauman, G. Shakhnarovich, T. Darrell, "Virtual Visual Hulls: Example-Based 3D Shape Inference from a Single Silhouette", Proceedings of the 2nd Workshop on Statistical Methods in Video Processing,2004. [pdf]
G. Shakhnarovich, P. Viola, T. Darrell, "Fast Pose Estimation with Parameter Sensitive Hashing", Proceedings of the International Conference on Computer Vision,2003.[pdf]
K. Grauman, G. Shakhnarovich, T. Darrell, "Inferring 3D Structure with a Statistical Image-Based Shape Model", Proceedings of the International Conference on Computer Vision,2003. [pdf]
K. Grauman, G. Shakhnarovich, T. Darrell, "A Bayesian Approach to Image-Based Visuall Hull Reconstruction", Proceedings IEEE Conf. on Computer Vision and Pattern Recognition,2003.[pdf]
B. Moghaddam, G. Shakhnarovich, "Boosted Dyadic Kernel Discriminants", NIPS, 2002. [ps]
G. Shakhnarovich, J. W. Fisher, T. Darrell, "Face recognition from long-term observations", Proceedings of European Conference on Computer Vision,2002. [pdf]
G. Shakhnarovich, T. Darrell, "On Probabilistic Combination of Face and Gait Cues for Identification", Proceedings of the Int. Conf. on Automatic Face and Gesture Recognition,2002. [pdf]
G. Shakhnarovich, P. Viola, B. Moghaddam, "A Unified Learning Framework for Real Time Face Detection and Classification", Proceedings of the Int. Conf. on Automatic Face and Gesture Recognition,2002. [pdf]
G. Shakhnarovich, R. El-Yaniv, Y. Baram, "Smoothed Bootstrap and Statistical Data Cloning for Classifier Evaluation", Proccedings of International Conference on Machine Learning, 2001. [pdf]
G. Shakhnarovich, L. Lee, T. Darrell, "Integrated Face and Gait Recognition From Multiple Views", Proceedings IEEE Conf. on Computer Vision and Pattern Recognition,2001. [pdf]
Workshop presentation: P. Yadollahpour, D. Batra, G. Shakhnarovich, "M-Best Modes: Diverse M-Best Solutions in MRFs", Workshop on Discrete Optimization in Machine Learning, NIPS 2011.
Workshop presentation: D. Batra, G. Shakhnarovich. "Similarity Sensitive Nonlinear Embeddings", Workshop on Kernels and Distances for Computer Vision, ICCV 2011. [pdf]
|Autumn 2013||TTIC 31020 : Introduction to Statistical Machine Learning|
|Autumn 2013,2012,2011,2010||TTIC 31020, Introduction to Statistical Machine Learning|
|Winter 2013,2012,2011||WIS 20134221, Introduction to Machine Learning (Weizmann Institute of Science)|
|Spring 2010||CS 35040/25040 : Introduction to Computer Vision|
|Spring 2009||TTIC 359 : Large Scale Learning|
|Fall 2006||CS195-5 : CS195-5, Introduction to Machine Learning (Brown)|