- Charles S. Sydnor Distinguished 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)
- Professor of Physics (Secondary)
Research Areas and Keywords
Algebra & Combinatorics
error-correcting codes, wireless communication, data storage, discrete harmonic analysis, sphere packing, algorithms, data compression, source classification, representation theory
detection and estimation, discrete harmonic analysis
discrete harmonic analysis, algorithms
error-correcting codes, data storage, discrete harmonic analysis, sphere packing, algorithms, representation theory
wireless communications, data storage, detection and estimation
error-correcting codes, wireless communications, data storage, detection and estimation, algorithms, data compression, source classification
Signals, Images & Data
error-correcting codes, wireless communication, data storage, discrete harmonic analysis, algorithms, data compression, source classification
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.
Goparaju, S., and R. Calderbank. “A new sub-packetization bound for minimum storage regenerating codes.” Ieee International Symposium on Information Theory Proceedings, Dec. 2013, pp. 1616–20. Scopus, doi:10.1109/ISIT.2013.6620500. Full Text
Nokleby, M., et al. “Information-theoretic limits on the classification of Gaussian mixtures: Classification on the Grassmann manifold.” 2013 Ieee Information Theory Workshop, Itw 2013, Dec. 2013. Scopus, doi:10.1109/ITW.2013.6691253. Full Text
Reboredo, H., et al. “Projections designs for compressive classification.” 2013 Ieee Global Conference on Signal and Information Processing, Globalsip 2013 Proceedings, Dec. 2013, pp. 1029–32. Scopus, doi:10.1109/GlobalSIP.2013.6737069. Full Text
Renna, F., et al. “Reconstruction of Gaussian mixture models from compressive measurements: A phase transition view.” 2013 Ieee Global Conference on Signal and Information Processing, Globalsip 2013 Proceedings, Dec. 2013. Scopus, doi:10.1109/GlobalSIP.2013.6736965. Full Text
Wu, T., et al. “Painting analysis using wavelets and probabilistic topic models.” 2013 Ieee International Conference on Image Processing, Icip 2013 Proceedings, Dec. 2013, pp. 3264–68. Scopus, doi:10.1109/ICIP.2013.6738672. Full Text
Xie, Y., et al. “Low-rank matrix recovery with poison noise.” 2013 Ieee Global Conference on Signal and Information Processing, Globalsip 2013 Proceedings, Dec. 2013. Scopus, doi:10.1109/GlobalSIP.2013.6736959. Full Text
Chi, Y., et al. “PETRELS: Parallel subspace estimation and tracking by recursive least squares from partial observations.” Ieee Transactions on Signal Processing, vol. 61, no. 23, Nov. 2013, pp. 5947–59. Scopus, doi:10.1109/TSP.2013.2282910. Full Text
Chi, Y., and R. Calderbank. “Knowledge-enhanced matching pursuit.” Icassp, Ieee International Conference on Acoustics, Speech and Signal Processing Proceedings, Oct. 2013, pp. 6576–80. Scopus, doi:10.1109/ICASSP.2013.6638933. Full Text
Tamo, I., et al. “Cyclic LRC codes and their subfield subcodes.” Ieee International Symposium on Information Theory Proceedings, vol. 2015-June, 2015, pp. 1262–66. Scopus, doi:10.1109/ISIT.2015.7282658. Full Text
Harms, A., et al. “Efficient linear time-varying system identification using chirp waveforms.” Conference Record Asilomar Conference on Signals, Systems and Computers, vol. 2015-April, 2015, pp. 854–58. Scopus, doi:10.1109/ACSSC.2014.7094572. Full Text
Huang, J., et al. “Geometry-aware deep transform.” Proceedings of the Ieee International Conference on Computer Vision, vol. 2015 International Conference on Computer Vision, ICCV 2015, 2015, pp. 4139–47. Scopus, doi:10.1109/ICCV.2015.471. Full Text
Huang, J., et al. “Discriminative robust transformation learning.” Advances in Neural Information Processing Systems, vol. 2015-January, 2015, pp. 1333–41.
Michelusi, N., et al. “Dynamic spectrum estimation with minimal overhead via multiscale information exchange.” 2015 Ieee Global Communications Conference, Globecom 2015, 2015. Scopus, doi:10.1109/GLOCOM.2014.7417532. Full Text
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. Full Text
Xian, Y., et al. “Classification of whale vocalizations using the Weyl transform.” Icassp, Ieee International Conference on Acoustics, Speech and Signal Processing Proceedings, vol. 2015-August, 2015, pp. 773–77. Scopus, doi:10.1109/ICASSP.2015.7178074. Full Text
Huang, J., et al. “Alignment with intra-class structure can improve classification.” Icassp, Ieee International Conference on Acoustics, Speech and Signal Processing Proceedings, vol. 2015-August, 2015, pp. 1921–25. Scopus, doi:10.1109/ICASSP.2015.7178305. Full Text
Huang, J., et al. “Multi-scale Bayesian reconstruction of compressive X-ray image.” Icassp, Ieee International Conference on Acoustics, Speech and Signal Processing Proceedings, vol. 2015-August, 2015, pp. 1618–22. Scopus, doi:10.1109/ICASSP.2015.7178244. Full Text