Henry Pfister

Professor in the Department of Electrical and Computer Engineering

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.

Appointments and Affiliations

  • Professor in the Department of Electrical and Computer Engineering
  • Professor of Mathematics

Contact Information

Education

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

Research Interests

Information theory, communications, probabilistic graphical models, machine learning, and deep neural networks

Awards, Honors, and Distinctions

  • Best Paper Award. Symposium on the Theory of Computation (STOC). 2016
  • 2015-2016 Distinguished Lecturer. IEEE Information Theory Society. 2015
  • NSF CAREER Award. National Science Foundation. 2008
  • 2007 Best Paper in Signal Processing and Coding for Data Storage. IEEE Communications Society . 2007

Courses Taught

  • ECE 392: Projects in Electrical and Computer Engineering
  • ECE 487: System Design for Machine Learning and Signal Processing
  • ECE 494: Projects in Electrical and Computer Engineering
  • ECE 496: Special Topics in Electrical and Computer Engineering
  • ECE 586: Vector Space Methods with Applications
  • ECE 586D: Vector Space Methods with Applications
  • ECE 590: Advanced Topics in Electrical and Computer Engineering
  • ECE 899: Special Readings in Electrical Engineering
  • EGR 393: Research Projects in Engineering
  • MATH 590-02: Advanced Special Topics in Mathematics

In the News

Representative Publications

  • Reeves, Galen, and Henry D. Pfister. “Reed-Muller Codes on BMS Channels Achieve Vanishing Bit-Error Probability for All Rates Below Capacity,” 2021.
  • Reeves, G., and H. D. Pfister. “The replica-symmetric prediction for compressed sensing with Gaussian matrices is exact.” In Ieee International Symposium on Information Theory  Proceedings, 2016-August:665–69, 2016. https://doi.org/10.1109/ISIT.2016.7541382.
  • Kumar, S., A. J. Young, N. Macris, and H. D. Pfister. “Threshold saturation for spatially coupled LDPC and LDGM codes on BMS channels.” Ieee Transactions on Information Theory 60, no. 12 (December 1, 2014): 7389–7415. https://doi.org/10.1109/TIT.2014.2360692.
  • Yedla, A., Y. Y. Jian, P. S. Nguyen, and H. D. Pfister. “A simple proof of maxwell saturation for coupled scalar recursions.” Ieee Transactions on Information Theory 60, no. 11 (January 1, 2014): 6943–65. https://doi.org/10.1109/TIT.2014.2352296.
  • Pfister, H. D., J. B. Soriaga, and P. H. Siegel. “On the achievable information rates of finite state ISI channels.” In Conference Record / Ieee Global Telecommunications Conference, 5:2992–96, 2001.