Henry Pfister

Henry Pfister
  • Professor in the Department of Electrical and Computer Engineering
  • Associate Professor of Mathematics (Secondary)
External address: 140 Science Dr., 305 Gross Hall, Durham, NC 27708
Internal office address: 90984, 315 Gross Hall, Durham, NC 27708
Phone: (919) 660-5288

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.

Education & Training
  • Ph.D., University of California - San Diego 2003

Häger, C., et al. “Revisiting multi-step nonlinearity compensation with machine learning.” Iet Conference Publications, vol. 2019, no. CP765, Jan. 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

Rengaswamy, N, Calderbank, R, Pfister, HD, and Kadhe, S. "Synthesis of Logical Clifford Operators via Symplectic Geometry." Ieee International Symposium on Information Theory Proceedings 2018-June (August 15, 2018): 791-795. Full Text

Hager, C., and H. D. Pfister. “Deep Learning of the Nonlinear Schrödinger Equation in Fiber-Optic Communications.” Ieee International Symposium on Information Theory  Proceedings, vol. 2018-June, Aug. 2018, pp. 1590–94. Scopus, doi:10.1109/ISIT.2018.8437734. Full Text

Santi, E., et al. “Decoding Reed-Muller Codes Using Minimum- Weight Parity Checks.” Ieee International Symposium on Information Theory  Proceedings, vol. 2018-June, Aug. 2018, pp. 1296–300. Scopus, doi:10.1109/ISIT.2018.8437637. Full Text

Hager, C., and H. D. Pfister. “Approaching Miscorrection-Free Performance of Product Codes with Anchor Decoding.” Ieee Transactions on Communications, vol. 66, no. 7, July 2018, pp. 2797–808. Scopus, doi:10.1109/TCOMM.2018.2816073. Full Text

Häger, C., and H. D. Pfister. “Nonlinear interference mitigation via deep neural networks.” Optics Infobase Conference Papers, vol. Part F84-OFC 2018, Jan. 2018. Scopus, doi:10.1364/OFC.2018.W3A.4. Full Text

Luo, Yi, and Henry Pfister. “Adversarial Defense of Image Classification Using a Variational Auto-Encoder.Corr, vol. abs/1812.02891, 2018.

Häger, C., and H. D. Pfister. “Miscorrection-free Decoding of Staircase Codes.” European Conference on Optical Communication, Ecoc, vol. 2017-September, Sept. 2017, pp. 1–3. Scopus, doi:10.1109/ECOC.2017.8345919. Full Text

Pages

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.

Pfister, H. D., et al. “Symmetric product codes.” 2015 Information Theory and Applications Workshop, Ita 2015  Conference Proceedings, 2015, pp. 282–90. Scopus, doi:10.1109/ITA.2015.7309002. Full Text

Li, S., et al. “On the limits of treating interference as noise for two-user symmetric Gaussian interference channels.” Ieee International Symposium on Information Theory  Proceedings, vol. 2015-June, 2015, pp. 1711–15. Scopus, doi:10.1109/ISIT.2015.7282748. Full Text

Rengaswamy, N., and H. D. Pfister. “Cyclic polar codes.” Ieee International Symposium on Information Theory  Proceedings, vol. 2015-June, 2015, pp. 1287–91. Scopus, doi:10.1109/ISIT.2015.7282663. Full Text

Hager, C., et al. “On parameter optimization for staircase codes.” Conference on Optical Fiber Communication, Technical Digest Series, vol. 2015-June, 2015. Scopus, doi:10.1364/ofc.2015.th3e.3. Full Text

Häger, C., et al. “On parameter optimization for staircase codes.” Optical Fiber Communication Conference, Ofc 2015, 2015.

Vem, A., et al. “Multilevel lattices based on spatially-coupled LDPC codes with applications.” Ieee International Symposium on Information Theory  Proceedings, 2014, pp. 2336–40. Scopus, doi:10.1109/ISIT.2014.6875251. Full Text

Kumar, S., et al. “Spatially-coupled codes for side-information problems.” Ieee International Symposium on Information Theory  Proceedings, 2014, pp. 516–20. Scopus, doi:10.1109/ISIT.2014.6874886. Full Text

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