# Robert Calderbank

- Charles S. Sydnor Professor of Computer Science
- Professor of Computer Science
- Director of the Rhodes Information Initiative at Duke
- Professor of Electrical and Computer Engineering (Joint)
- Professor of Mathematics (Joint)

**External address:**140 Science Drive, 317 Gross Hall, Durham, NC 27708

**Internal office address:**Campus Box 90984, 140 Science Drive, Durham, NC 27708

**Phone:**(919) 613-7874

### Research Areas and Keywords

##### Algebra & Combinatorics

##### Analysis

##### Computational Mathematics

##### Number Theory

##### Physical Modeling

##### Probability

##### Signals, Images & Data

Robert Calderbank is Director of the Information Initiative at Duke University, where he is Professor of Electrical Engineering, Computer Science and Mathematics. He joined Duke in 2010, completed a 3 year term as Dean of Natural Sciences in August 2013, and also served as Interim Director of the Duke Initiative in Innovation and Entrepreneurship in 2012. Before joining Duke he was Professor of Electrical Engineering and Mathematics at Princeton University where he also directed the Program in Applied and Computational Mathematics.

Before joining Princeton University Dr. Calderbank was Vice President for Research at AT&T. As Vice President for Research he managed AT&T intellectual property, and he was responsible for licensing revenue. AT&T Labs was the first of a new type of research lab where masses of data generated by network services became a giant sandbox in which fundamental discoveries in information science became a source of commercial advantage

At Duke, Dr. Calderbank works with researchers from the Duke Center for Autism and Brain Development, developing information technology that is able to capture a full spectrum of behavior in very young children. By supporting more consistent and cost-effective early diagnosis, the team is increasing the opportunity for early interventions that have proven very effective.

At the start of his career at Bell Labs, Dr. Calderbank developed voiceband modem technology that was widely licensed and incorporated in over a billion devices. Voiceband means the signals are audible so these modems burped and squeaked as they connected to the internet. One of these products was the AT&T COMSPHERE^{®} modem which was the fastest modem in the world in 1994 – at 33.6kb/s!

Together with Peter Shor and colleagues at AT&T Labs Dr. Calderbank developed the group theoretic framework for quantum error correction. This framework changed the way physicists view quantum entanglement, and provided the foundation for fault tolerant quantum computation.

Dr. Calderbank has also developed technology that improves the speed and reliability of wireless communication by correlating signals across several transmit antennas. Invented in 1996, this *space-time coding* technology has been incorporated in a broad range of 3G, 4G and 5G wireless standards. He served on the Technical Advisory Board of Flarion Technologies a wireless infrastructure company founded by Rajiv Laroia and acquired by Qualcomm for $1B in 2008.

Dr. Calderbank is an IEEE Fellow and an AT&T Fellow, and he was elected to the National Academy of Engineering in 2005. He received the 2013 IEEE Hamming Medal for contributions to coding theory and communications and the 2015 Shannon Award.

Renna, F., et al. “Compressive sensing for incoherent imaging systems with optical constraints.” *Icassp, Ieee International Conference on Acoustics, Speech and Signal Processing Proceedings*, Oct. 2013, pp. 5484–88. *Scopus*, doi:10.1109/ICASSP.2013.6638712.
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Goparaju, S., et al. “Data secrecy in distributed storage systems under exact repair.” *2013 International Symposium on Network Coding, Netcod 2013*, Sept. 2013. *Scopus*, doi:10.1109/NetCod.2013.6570831.
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Jacobvitz, A. N., et al. “Coset coding to extend the lifetime of memory.” *Proceedings International Symposium on High Performance Computer Architecture*, July 2013, pp. 222–33. *Scopus*, doi:10.1109/HPCA.2013.6522321.
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Duarte, M. F., et al. “Performance of the Delsarte-Goethals frame on clustered sparse vectors.” *Ieee Transactions on Signal Processing*, vol. 61, no. 8, Apr. 2013, pp. 1998–2008. *Scopus*, doi:10.1109/TSP.2013.2242064.
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Harms, A., et al. “A constrained random demodulator for sub-nyquist sampling.” *Ieee Transactions on Signal Processing*, vol. 61, no. 3, Feb. 2013, pp. 707–23. *Scopus*, doi:10.1109/TSP.2012.2231077.
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Wang, L., et al. “Designed measurements for vector count data.” *Advances in Neural Information Processing Systems*, Jan. 2013.

Nokleby, M., et al. “Toward resource-optimal consensus over the wireless medium.” *Ieee Journal on Selected Topics in Signal Processing*, vol. 7, no. 2, Jan. 2013, pp. 284–95. *Scopus*, doi:10.1109/JSTSP.2013.2246765.
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Chi, Y., and R. Calderbank. “Coherence-based performance guarantees of Orthogonal Matching Pursuit.” *2012 50th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2012*, Dec. 2012, pp. 2003–09. *Scopus*, doi:10.1109/Allerton.2012.6483468.
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Nokleby, M., et al. “Toward resource-optimal averaging consensus over the wireless medium.” *Conference Record Asilomar Conference on Signals, Systems and Computers*, Dec. 2012, pp. 1197–201. *Scopus*, doi:10.1109/ACSSC.2012.6489211.
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Jacobvitz, A. N., et al. “Writing cosets of a convolutional code to increase the Lifetime of Flash memory.” *2012 50th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2012*, Dec. 2012, pp. 308–18. *Scopus*, doi:10.1109/Allerton.2012.6483234.
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## Pages

Boche, H., et al. *A survey of compressed sensing*. no. 9783319160412, 2015, pp. 1–39. *Scopus*, doi:10.1007/978-3-319-16042-9_1.
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Rodrigues, M., et al. *Compressive classification: Where wireless communications meets machine learning*. no. 9783319160412, 2015, pp. 451–68. *Scopus*, doi:10.1007/978-3-319-16042-9_15.
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Wang, L., et al. “Nonlinear information-theoretic compressive measurement design.” *31st International Conference on Machine Learning, Icml 2014*, vol. 4, 2014, pp. 2896–907.

Bajwa, W. U., et al. “Average case analysis of high-dimensional block-sparse recovery and regression for arbitrary designs.” *Journal of Machine Learning Research*, vol. 33, 2014, pp. 57–67.

Harms, Andrew, et al. “Shaping the Power Spectra of Bipolar Sequences with Application to Sub-Nyquist Sampling.” *2013 Ieee 5th International Workshop on Computational Advances in Multi Sensor Adaptive Processing (Camsap 2013)*, IEEE, 2013, pp. 236-+.

Harms, Andrew, et al. “Resource-Efficient Parametric Recovery of Linear Time-Varying Systems.” *2013 Ieee 5th International Workshop on Computational Advances in Multi Sensor Adaptive Processing (Camsap 2013)*, IEEE, 2013, pp. 200-+.

Calderbank, Robert, et al. “A Sublinear Algorithm for Sparse Reconstruction with (2) Recovery Guarantees.” *2009 3rd Ieee International Workshop on Computational Advances in Multi Sensor Adaptive Processing (Camsap)*, 2009, pp. 209–12.

Chi, Yuejie, et al. “Golay Complementary Waveforms for Sparse Delay-Doppler Radar Imaging.” *2009 3rd Ieee International Workshop on Computational Advances in Multi Sensor Adaptive Processing (Camsap)*, 2009, pp. 177–80.

Zoltowski, Michael D., et al. “Channel Estimation for MIMO-OFDM using Complementary Codes.” *Rws: 2009 Ieee Radio and Wireless Symposium*, 2009, pp. 151-+.

Souvik, D., et al. “Linear-time decodable secrecy codes for binary erasure wiretap channels.” *43rd Annual Allerton Conference on Communication, Control and Computing 2005*, vol. 3, 2005, pp. 1548–56.