Henry Pfister

Henry Pfister

Associate 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 an associate professor in the Electrical and Computer Engineering Department of Duke University with a secondary appointment in Mathematics.  Prior to that, he was a 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).

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 served as an Associate Editor for the IEEE Transactions on Information Theory (2013-2016) and a Distinguished Lecturer of the IEEE Information Theory Society (2015-2016).

His current research interests include information theory, communications, probabilistic graphical models, machine learning, and deep neural networks.

Appointments and Affiliations

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

Contact Information

  • Office Location: 140 Science Dr., 305 Gross Hall, Durham, NC 27708
  • Office Phone: (919) 660-5288
  • Email Address: henry.pfister@duke.edu

Education

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

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

  • COMPSCI 391: Independent Study
  • ECE 485: Digital Audio and Acoustic Signal Processing
  • ECE 590: Advanced Topics in Electrical and Computer Engineering
  • ECE 891: Internship
  • MATH 590-02: Advanced Special Topics in Mathematics

In the News

Representative Publications

  • Reeves, G; Pfister, HD, The replica-symmetric prediction for compressed sensing with Gaussian matrices is exact, vol 2016-August (2016), pp. 665-669 [10.1109/ISIT.2016.7541382] [abs].
  • Kudekar, S; Kumar, S; Mondelli, M; Pfister, HD; Sasoglu, E; Urbanke, RL, Reed-Muller codes achieve capacity on erasure channels., STOC (2016), pp. 658-669 [10.1145/2897518.2897584] [abs].
  • Kumar, S; Young, AJ; Macris, N; Pfister, HD, Threshold Saturation for Spatially Coupled LDPC and LDGM Codes on BMS Channels, IEEE Transactions on Information Theory, vol 60 no. 12 (2014), pp. 7389-7415 [10.1109/TIT.2014.2360692] [abs].
  • Yedla, A; Jian, Y-Y; Nguyen, PS; Pfister, HD, A Simple Proof of Maxwell Saturation for Coupled Scalar Recursions, IEEE Transactions on Information Theory, vol 60 no. 11 (2014), pp. 6943-6965 [10.1109/TIT.2014.2352296] [abs].
  • Pfister, HD; Sason, I; Urbanke, RL, Capacity-achieving ensembles for the binary erasure channel with bounded complexity., IEEE Trans. Information Theory, vol 51 (2005), pp. 2352-2379 [10.1109/TIT.2005.850079] [abs].
  • Pfister, HD; Soriaga, JB; Siegel, PH, On the achievable information rates of finite state ISI channels, Conference Record / IEEE Global Telecommunications Conference, vol 5 (2001), pp. 2992-2996 [abs].