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Ivan Selesnick

Ivan Selesnick

Professor and Department Chair

Electrical & Computer Engineering


Ivan Selesnick is a Professor of Electrical and Computer Engineering at NYU Tandon School of Engineering. Selesnick received BS, MEE, and Ph.D. degrees in Electrical Engineering from Rice University in Houston, TX. As a Ph.D. student, he received a DARPA-NDSEG fellowship in 1991. He joined Polytechnic University in 1997 (now NYU Tandon School of Engineering).

Selesnick received an Alexander von Humboldt Fellowship in 1997 and a National Science Foundation Career award in 1999. In 2003 he received the Jacobs Excellence in Education Award from Polytechnic University. He became an IEEE Fellow in 2016.

Journal Articles

Recent papers:

I. W. Selesnick. Generalized total variation: Tying the knots. IEEE Signal Processing Letters. 22(11):2009–2013, November 2015.

A. Parekh and I. W. Selesnick. Convex denoising using non-convex tight frame regularization. IEEE Signal Processing Letters. 22(10):1786–1790, October 2015.

A. Parekh, I. W. Selesnick, D. M. Rapoport, and I. Ayappa. Detection of K-complexes and sleep spindles (DETOKS) using sparse optimization. Journal of Neuroscience Methods. 251:37–46, 15 August 2015.

Y. Ding and I. W. Selesnick. Artifact-free wavelet denoising: non-convex sparse regularization, convex optimization. IEEE Signal Processing Letters. 22(9):1364–1368, September 2015.

R. Kafieh, H. Rabbani, and I. Selesnick. Three dimensional data-driven multiscale atomic representation of optical coherence tomography. IEEE Transactions on Medical Imaging. 34(5):1042–1062, May 2015.

I. W. Selesnick, A. Parekh, and I. Bayram. Convex 1-D total variation denoising with non-convex regularization. IEEE Signal Processing Letters. 22(2):141–144, February 2015.

S. Miri, E. M. Shrier, S. Glazman, Y. Ding, I. Selesnick, P. B. Kozlowski, and I. Bodis-Wollner. The avascular zone and neuronal remodeling of the fovea in Parkinson disease. Annals of Clinical and Translational Neurology. January 2015. DOI: 10.1002/acn3.146.

I. W. Selesnick, H. L. Graber, Y. Ding, T. Zhang, and R. L. Barbour. Transient artifact reduction algorithm (TARA) based on sparse optimization. IEEE Trans. on Signal Processing. 62(24):6596–6611, December 2014.

X. Ning, I. W. Selesnick, L. Duval. Chromatogram baseline estimation and denoising using sparsity (BEADS). Chemometrics and Intelligent Laboratory Systems. Volume 139, pages 156-167, 15 December 2014. ISSN 0169-7439.

F. Uysal, I. Selesnick, U. Pillai, and B. Himed. Dynamic clutter mitigation using sparse optimization. IEEE Aerospace and Electronic Systems Magazine, 29(7):37-49, July 2014.

I. Naggar, K, Nakase, J. Lazar, L. Salciccioli, I. Selesnick, and M. Stewart. Vagal control of cardiac electrical activity and wall motion during ventricular fibrillation in large animals. Autonomic Neuroscience: Basic and Clinical, volume 183, pp. 12-22, July 2014.

P.-Y. Chen and I. W. Selesnick. Group-sparse signal denoising: non-convex regularization, convex optimization. IEEE Trans. on Signal Processing, 62(13):3464-3478, July 1, 2014.

Y. Ding, B. Spund, S. Glazman, E. M. Shrier, S. Miri, I. Selesnick, and I. Bodis-Wollner. Application of an OCT data-based mathematical model of the foveal pit in Parkinson disease. Journal of Neural Transmission. Vol. 121, issue 11, pages 1367-1376, November 2014.

I. W. Selesnick and I. Bayram. Sparse signal estimation by maximally sparse convex optimization. IEEE Trans. on Signal Processing, 62(5):1078-1092, March 2014.

I. W. Selesnick, H. L. Graber, D. S. Pfeil, and R. L. Barbour. Simultaneous low-pass filtering and total variation denoising. IEEE Trans. on Signal Processing, 62(5):1109-1124, March 2014.

P.-Y. Chen and I. W. Selesnick. Translation-invariant shrinkage/thresholding of group sparse signals. Signal Processing. vol. 94, pp 476-489, January 2014.

X. Ning and I. W. Selesnick. ECG enhancement and QRS detection based on sparse derivatives. Biomedical Signal Processing and Control. vol. 8, no. 6, pp 713-723, November 2013.

B. Spund, Y. Ding, T. Liu, I. Selesnick, S. Glazman, E. M. Shrier, and I. Bodis-Wollner. Remodeling of the fovea in Parkinson disease. Journal of Neural Transmission. vol. 120, no. 5, pp 745-753, May 2013.

I. W. Selesnick, S. Arnold, and V. R. Dantham. Polynomial smoothing of time series with additive step discontinuities. IEEE Trans. on Signal Processing, 60(12):6305-6318, December 2012.

C. Bilen, Y. Wang, and I. W. Selesnick. High-speed compressed sensing reconstruction in dynamic parallel MRI using augmented Lagrangian and parallel processing. IEEE J. Emerging and Selected Topics in Circuits and Systems, 2(3):370-379, September 2012.

I. Bayram and I. W. Selesnick. A dual-tree rational-dilation complex wavelet transform. IEEE Trans. on Signal Processing. 59(12):6251-6256, December 2011.

I. W. Selesnick. Wavelet transform with tunable Q-factor. IEEE Trans. on Signal Processing. 59(8):3560-3575, August 2011.

I. W. Selesnick. Resonance-based signal decomposition: A new sparsity-enabled signal analysis method. Signal Processing. 91(12):2793-2809, 2011.

P. A. Khazron and I. W. Selesnick. Spatiotemporal wavelet maximum a posteriori estimation for video denoising. J. Electron. Imaging. Vol. 19, no. 4, page 043015-1-043015-15, Oct.-Dec. 2010.

I. Bayram and I. W. Selesnick. A subband adaptive iterative shrinkage/thresholding algorithm. IEEE Trans. on Signal Processing. 58(3):1131-1143, March 2010.

A. N. Akansu and W. A. Serdijn and I. W. Selesnick. Emerging applications of wavelets: A review. Physical Communication. Volume 3, Issue 1, pages 1-18, March 2010.


Rice University, 1996

PhD, Electrical Engineering

Rice University, 1991

MSEE, Electrical Engineering

Rice University, 1990

Bachelor of Science, Electrical Engineering

Research Interests

  • Signal Processing
  • Sparse Signal Models and Optimization
  • Biomedical Signal Processing
  • Wavelet Analysis