- Professor in the Department of Electrical and Computer Engineering
- Associate Professor of Mathematics (Secondary)
Henry D. Pfister received his Ph.D. in Electrical Engineering in 2003 from the University of California, San Diego and is currently a professor in the Electrical and Computer Engineering Department of Duke University with a secondary appointment in Mathematics. Prior to that, he was an associate professor at Texas A&M University (2006-2014), a post-doctoral fellow at the École Polytechnique Fédérale de Lausanne (2005-2006), and a senior engineer at Qualcomm Corporate R&D in San Diego (2003-2004). His current research interests include information theory, error-correcting codes, quantum computing, and machine learning.
He received the NSF Career Award in 2008 and a Texas A&M ECE Department Outstanding Professor Award in 2010. He is a coauthor of the 2007 IEEE COMSOC best paper in Signal Processing and Coding for Data Storage and a coauthor of a 2016 Symposium on the Theory of Computing (STOC) best paper. He has served the IEEE Information Theory Society as a member of the Board of Governors (2019-2022), an Associate Editor for the IEEE Transactions on Information Theory (2013-2016), and a Distinguished Lecturer (2015-2016). He was also the General Chair of the 2016 North American School of Information Theory.
Reeves, G., and H. D. Pfister. “The Replica-Symmetric Prediction for Random Linear Estimation With Gaussian Matrices Is Exact.” Ieee Transactions on Information Theory, vol. 65, no. 4, Apr. 2019, pp. 2252–83. Scopus, doi:10.1109/TIT.2019.2891664. Full Text
Yoo, I., et al. “Enhancing Capacity of Spatial Multiplexing Systems Using Reconfigurable Cavity-Backed Metasurface Antennas in Clustered MIMO Channels.” Ieee Transactions on Communications, vol. 67, no. 2, Feb. 2019, pp. 1070–84. Scopus, doi:10.1109/TCOMM.2018.2876899. Full Text
Schmidt, Christian, et al. “Minimal sets to destroy the k-core in random networks.” Physical Review. E, vol. 99, no. 2–1, Feb. 2019, p. 022310. Epmc, doi:10.1103/physreve.99.022310. Full Text
Sheikh, A., et al. “On Low-Complexity Decoding of Product Codes for High-Throughput Fiber-Optic Systems.” International Symposium on Turbo Codes and Iterative Information Processing, Istc, vol. 2018-December, Jan. 2019. Scopus, doi:10.1109/ISTC.2018.8625279. Full Text
Lian, M., et al. “What can machine learning teach us about communications?” 2018 Ieee Information Theory Workshop, Itw 2018, Jan. 2019. Scopus, doi:10.1109/ITW.2018.8613331. Full Text
Häger, Christian, et al. “Revisiting Multi-Step Nonlinearity Compensation with Machine Learning.” Corr, vol. abs/1904.09807, 2019.
Rengaswamy, Narayanan, et al. “Logical Clifford Synthesis for Stabilizer Codes.” Corr, vol. abs/1907.00310, 2019.
Rengaswamy, Narayanan, et al. “On Optimality of CSS Codes for Transversal T.” Corr, vol. abs/1910.09333, 2019.
Fougstedt, C., et al. “ASIC Implementation of Time-Domain Digital Backpropagation with Deep-Learned Chromatic Dispersion Filters.” European Conference on Optical Communication, Ecoc, vol. 2018-September, Nov. 2018. Scopus, doi:10.1109/ECOC.2018.8535430. Full Text
Häger, C., and H. D. Pfister. “Wideband Time-Domain Digital Backpropagation via Subband Processing and Deep Learning.” European Conference on Optical Communication, Ecoc, vol. 2018-September, Nov. 2018. Scopus, doi:10.1109/ECOC.2018.8535251. Full Text
Sabag, O., et al. “A single-letter upper bound on the feedback capacity of unifilar finite-state channels.” Ieee International Symposium on Information Theory Proceedings, vol. 2016-August, 2016, pp. 310–14. Scopus, doi:10.1109/ISIT.2016.7541311. Full Text
Pfister, H. D., and R. Urbanke. “Near-optimal finite-length scaling for polar codes over large alphabets.” Ieee International Symposium on Information Theory Proceedings, vol. 2016-August, 2016, pp. 215–19. Scopus, doi:10.1109/ISIT.2016.7541292. Full Text
Reeves, G., and H. D. Pfister. “The replica-symmetric prediction for compressed sensing with Gaussian matrices is exact.” Ieee International Symposium on Information Theory Proceedings, vol. 2016-August, 2016, pp. 665–69. Scopus, doi:10.1109/ISIT.2016.7541382. Full Text
Hager, C., et al. “Density evolution and error floor analysis for staircase and braided codes.” 2016 Optical Fiber Communications Conference and Exhibition, Ofc 2016, 2016. Scopus, doi:10.1364/ofc.2016.th2a.42. Full Text
Kudekar, S., et al. “Reed-Muller codes achieve capacity on erasure channels.” Proceedings of the Annual Acm Symposium on Theory of Computing, vol. 19-21-June-2016, 2016, pp. 658–69. Scopus, doi:10.1145/2897518.2897584. Full Text
Kumar, S., et al. “Spatially-coupled codes for write-once memories.” 2015 53rd Annual Allerton Conference on Communication, Control, and Computing, Allerton 2015, 2016, pp. 125–31. Scopus, doi:10.1109/ALLERTON.2015.7446994. Full Text
Lian, M., and H. D. Pfister. “Belief-propagation reconstruction for compressed sensing: Quantization vs. Gaussian approximation.” 2015 53rd Annual Allerton Conference on Communication, Control, and Computing, Allerton 2015, 2016, pp. 1106–13. Scopus, doi:10.1109/ALLERTON.2015.7447132. Full Text
Kudekar, Shrinivas, et al. “Reed-Muller codes achieve capacity on erasure channels.” Stoc, edited by Daniel Wichs and Yishay Mansour, ACM, 2016, pp. 658–69.