VONTOBEL Pascal Olivier

*SHB = Ho Sin Hang Engineering Building, The Chinese University of Hong Kong


Research Interest
  • Graphical models
  • Quantum information processing
  • Error-control coding
  • Information theory
  • Data science
  • Compressed sensing
  • Optimization theory
Courses Taught

  • ENGG1120 Linear Algebra for Engineers
  • ENGG2440 Discrete Mathematics for Engineers
  • IERG6120 Advanced Topics in IE I (Quantum Information Processing)

VONTOBEL Pascal Olivier

Professor
Chairman And Graduate Division Head
FIEEE
Dip, Post-Dip, PhD (ETH Zurich)
(852) 3943-8390
Room 836, SHB*
pascal.vontobel [at] ie.cuhk.edu.hk

Pascal O. Vontobel received the Diploma degree in electrical engineering in 1997, the Post-Diploma degree in information techniques in 2002, and the Ph.D. degree in electrical engineering in 2003, all from ETH Zurich, Switzerland.

From 1997 to 2002 he was a research and teaching assistant at the Signal and Information Processing Laboratory at ETH Zurich, from 2006 to 2013 he was a research scientist with the Information Theory Research Group at Hewlett-Packard Laboratories in Palo Alto, CA, USA, and since 2014 he has been an Associate Professor at the Department of Information Engineering at the Chinese University of Hong Kong. Besides this, he was a postdoctoral research associate at the University of Illinois at Urbana-Champaign (2002-2004), a visiting assistant professor at the University of Wisconsin-Madison (2004-2005), a postdoctoral research associate at the Massachusetts Institute of Technology (2006), and a visiting scholar at Stanford University (2014). His research interests lie in coding and information theory, quantum information processing, data science, communications, and signal processing.

Dr. Vontobel was an Associate Editor for the IEEE Transactions on Information Theory (2009-2012), an Awards Committee Member of the IEEE Information Theory Society (2013-2014), a Distinguished Lecturer of the IEEE Information Theory Society (2014-2015), and an Associate Editor for the IEEE Transactions on Communications (2014-2017). Moreover, he was a TPC co-chair of the 2016 IEEE International Symposium on Information Theory, the 2018 IEICE International Symposium on Information Theory and its Applications, and the 2018 IEEE Information Theory Workshop, along with being the director of the 2021 Croucher Summer Course in Information Theory, co-organizing several topical workshops, and being on the technical program committees of many international conferences. Furthermore, he was multiple times a plenary speaker at international information and coding theory conferences, he received an exemplary reviewer award from the IEEE Communications Society, and was awarded the ETH medal for his Ph.D. dissertation. He is an IEEE Fellow.

Recent / Selected Publications
  • H. Cao and P.O. Vontobel, “Using list decoding to improve the finite-length performance of sparse regression codes,” IEEE Trans. Comm., vol. 69, no. 7, pp. 4282-4293, Jul. 2021.
  • J.X. Li, J.M. Renes, and P.O. Vontobel, “Pseudocodeword-based decoding of quantum color codes,” Proc. IEEE Int. Symp. Inf. Theory, Melbourne, Australia, pp. 1558-1563, Jul. 12-20 2021.
  • Y. Huang and P.O. Vontobel, “Sets of marginals and Pearson-correlation-based CHSH inequalities for a two-qubit system,” Proc. IEEE Int. Symp. Inf. Theory, Melbourne, Australia, pp. 1338-1343, Jul. 12-20 2021.
  • Y. Huang and P.O. Vontobel, “Characterizing the Bethe partition function of double-edge factor graphs via graph covers,” Proc. IEEE Int. Symp. Inf. Theory, Los Angeles, CA, USA, pp. 1337-1342, Jun. 21-26, 2020.
  • M.X. Cao and P.O. Vontobel, “Bounding and estimating the classical information rate of quantum channels with memory,” IEEE Trans. Inf. Theory, vol. 66, no. 9, pp. 5601-5619, Sep. 2020.
  • H.-A. Loeliger and P.O. Vontobel, “Quantum measurement as marginalization and nested quantum systems,” IEEE Trans. Inf. Theory, vol. 66, pp. 3485-3499, Jun. 2020.
Research Interest

  • Graphical models
  • Quantum information processing
  • Error-control coding
  • Information theory
  • Data science
  • Compressed sensing
  • Optimization theory
Courses Taught

  • ENGG1120 Linear Algebra for Engineers
  • ENGG2440 Discrete Mathematics for Engineers
  • IERG6120 Advanced Topics in IE I (Quantum Information Processing)