Daniel Freedman

Senior Research Scientist
HPL Israel: Printing Automation Lab
Haifa

Biography

Daniel Freedman is currently senior research scientist at HP Labs Israel, located in Haifa.  From 2000-2007, he was an associate professor with tenure in RPI's computer science department.  In the year 2007-8, he was a Fulbright Fellow, during which time he was visiting professor of applied math and computer science at the Weizmann Institute of Science. He received his PhD from Harvard University in 2000, his AM from Harvard University in 1996, and his AB (Magna Cum Laude, Phi Beta Kappa, Sigma Xi) from Princeton University in 1993.

Freedman has received the National Science Foundation Career Award and a Fulbright Fellowship. He is a member of IEEE and Sigma Xi.

 

Research interests

Freedman's general research interests are in Computer Vision and Geometric Algorithms. Within the field of Computer Vision, he is interested in the use of mathematical techniques such as geometric partial differential equations and combinatorial optimization, for the formulation of algorithms for tracking and segmentation. These algorithms find applications in medicine, such as image-guided radiotherapy, as well as military scenarios. Within the field of Geometric Algorithms, he has focused recently on problems in algebraic topology, particularly notions of measurement and quantification of homology. Older work centered on the reconstruction of manifolds (curves, surfaces, as well as higher dimensional manifolds) from point clouds.

At HP Labs, Freedman has been focusing on the problems of segmentation, inverse problems related to illumination, and computation of near-isometric deformations, amongst others.

Awards

  • Fulbright Fellowship, 2007-8.
  • NSF CAREER Award 2002.
  • Robert L.Wallace Prize Fellowship, 1998-1999.
  • Harvard University Fellowship, 1996-1998,1999-2000.
  • Graduated Magna Cum Laude in physics (Princeton University, 1993).
  • Phi Beta Kappa (Princeton University, 1993).
  • Sigma Xi (Princeton University, 1993).

Publications

  1. D. Freedman and C. Chen. Homology for computer vision. Submitted to International Journal of Computer Vision.
  2. D. Freedman. Sampling and mode-finding: stability results. Submitted to SIAM Journal on Imaging Sciences.
  3. C. Chen and D. Freedman. Hardness results for optimal homology bases. Submitted to Discrete and Computational Geometry.
  4. Z. Karni, D. Freedman, and C. Gotsman.  Energy-based shape deformation.  Submitted to Symposium on Geometry Processing (SGP).
  5. D. Freedman and P. Kisilev. KDE paring and a faster mean shift algorithm. Submitted to IEEE Transactions on Pattern Analysis and Machine Intelligence.
  6. P. Kisilev and D. Freedman.  Transferring photometry. Submitted to IEEE International Conference on Computer Vision (ICCV).
  7. D. Freedman and M. Turek. Graph cuts with many-pixel interactions: theory and applications to shape modeling. Accepted to Image and Vision Computing.
  8. D. Freedman and P. Kisilev. Fast mean shift by compact density representation. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), 2009.
  9. C. Chen and D. Freedman. Measuring and computing natural generators for homology groups. Accepted to Computational Geometry: Theory and Applications.
  10. D. Freedman and P. Kisilev.  Fast data reduction via KDE compression.  In Proceedings of the IEEE Data Compression Conference (DCC), 2009.
  11. C. Chen and D. Freedman. Quantifying homology classes. In Proceedings of the International Symposium on Theoretical Aspects of Computer Science (STACS), 2008
  12. A. Ayvaci and D. Freedman. Joint segmentation-registration of organs using geometric models.  International Conference of the IEEE Engineering in Medicine and Biology Society, 2007.
  13. D. Freedman. An incremental algorithm for reconstruction of surfaces of arbitrary codimension.  Computational Geometry: Theory and Applications, 36(2):106-116, 2007.
  14. M. Turek and D. Freedman. Multiscale modeling and constraints for max-flow/min-cut problems in computer vision. In Proceedings of the IEEE Computer Society Workshop on Perceptual Organization in Computer Vision (in conjunction with IEEE CVPR 2006).
  15. D. Freedman and P. Drineas. Energy minimization via graph cuts: settling what is possible. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), volume 2, pages 939-946, 2005. [Acceptance Rate: 26.8%]
  16. D. Freedman and M. Turek. Illumination-invariant tracking via graph cuts. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), volume 2, pages 10-17, 2005. [Acceptance Rate, Oral Presentation: 6.2%]
  17. D. Freedman and T. Zhang. Interactive graph cut based segmentation with shape priors. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), volume 1, pages 755-762, 2005. [Acceptance Rate: 26.8%]
  18. D. Freedman, R. J. Radke, T. Zhang, Y. Jeong, D. M. Lovelock, and G. T. Y. Chen. Model-based segmentation of medical imagery by matching distributions. IEEE Transactions on Medical Imaging, 24(3):281-292, 2005.
  19. T. Zhang and D. Freedman. Improving performance of distribution tracking through background mismatch. IEEE Transactions on Pattern Analysis and Machine Intelligence, 27(2):282-287, 2005.
  20. D. Freedman. Surface reconstruction, one triangle at a time. In Proceedings of the Sixteenth Canadian Conference of Computational Geometry (CCCG), pages 15-19, 2004.
  21. D. Freedman, R.J. Radke, T. Zhang, Y. Jeong, and G.T.Y Chen. Model-based multi-object segmentation via distribution matching. In Proceedings of the Third IEEE Workshop on Articulated and Nonrigid Motion (in conjunction with IEEE CVPR 2004), 2004.
  22. D. Freedman and T. Zhang. Active contours for tracking distributions. IEEE Transactions on Image Processing, 13(4):518-526, 2004.
  23. T. Zhang and D. Freedman. Tracking objects using density matching and shape priors. In Proceedings of the Ninth IEEE International Conference on Computer Vision (ICCV), volume 2, pages 1056-1062, 2003. [Acceptance Rate: 20.7%]
  24. D. Freedman. Effective tracking through tree-search. IEEE Transactions on Pattern Analysis and Machine Intelligence, 25(5):604-615, 2003.
  25. D. Freedman. Combinatorial curve reconstruction in Hilbert Spaces: a new sampling theory and an old result revisited. Computational Geometry: Theory and Applications, 23(2):227-241, 2002.
  26. Y. Shao, M. Magdon-Ismail, D. Freedman, S. Akella, M. Zaki, and C. Bystroff. Compression of protein conformational space. In 6th Annual International Conference on Research in Computational Molecular Biology (RECOMB02), Washington, DC, April 2002.
  27. D. Freedman. Efficient simplicial reconstructions of manifolds from their samples. IEEE Transactions on Pattern Analysis and Machine Intelligence, 24(10):1349 -1357, 2002.
  28. D. Freedman. Manifold reconstruction from unorganized points. In Proceedings of the Thirty Fourth Annual Asilomar Conference on Signals, Systems, and Computers, volume 2, pages 1744-1748, 2000.
  29. D. Freedman and M. S. Brandstein. Provably fast algorithms for contour tracking. In Proceedings of the 2000 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), volume 1, pages 139-144, 2000.
  30. D. Freedman and M. S. Brandstein. Contour tracking in clutter: a subset approach. International Journal of Computer Vision, 38(2):173-186, 2000.
  31. D. Freedman and M. S. Brandstein. Methods of global optimization in contour tracking. In Proceedings of the Thirty Third Annual Asilomar Conference on Signals, Systems, and Computers, volume 1, pages 725-729,1999.
  32. D. Freedman and M. S. Brandstein. A subset approach to contour tracking in clutter. In Proceedings of the Seventh IEEE International Conference on Computer Vision (ICCV), volume 1, pages 242-247, 1999. [Acceptance Rate: 31%]
  33. R. Taylor, A. Sachrajda, D. Freedman, and P. Kelly. Density of electrons in a lateral quantum dot by semi-classical trajectory analysis. Solid State Communications, 89(7):579-582, 1994.

Professional activities

Current program committees: CVPR 09, EMMCVPR 09, ICCV 09.