Hongchao Zhou

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Other Post:hongchao@sdu.edu.cn


Alma Mater:Caltech


I am a professor in the School of Information Science and Engineering at Shandong University. I was a postdoctoral associate in Professor Gregory Wornell's group at the Massachusetts Institute of Technology. I received my Ph.D. degree and M.S. degree in Electrical Engineering from the California Institute of Technology in 2012 and 2009, respectively, advised by Professor Jehoshua (Shuki) Bruck.  From 2004 to 2008, I studied at Tsinghua University, where I received my M.S. degree in control science supervised by Professor Xiaohong Guan and my B.S. degree in physics and mathematics.

My current research interests include information/coding theory and machine learning, in particular interested in the intersections of information (math), systems and underlying physics. I am also an engineer building/built a number of systems, such as cloud-native data lakehouse, photonic design system, and the first version of IBM Smartcloud docs (2006-2008). I am a recipient of the 2013 Charles Wilts Prize for the best doctoral thesis in EE at Caltech, ISIT Student Paper Award Finalist, and the IEEE distinguished student humanitarian prize. 

Some of my research works include:

(1) Unsupervised Deep Learning.  Introduced 'Activation Learning,'[paper] a new biologically-plausible learning paradigm that achieves comparable performance to backpropagation on some tasks; Studied unsupervised deep learning for segmentation, compression, 3D computer vision and photonic design. 

(2) Security and Privacy. We first extent Shannon's work on information-theoretic security from point-to-point communication to arbitrary networks, raising the topic of "network information-theoretic security"[paper]. Other work on efficient homomorphic  encryption [paper].

(3) Computing and Randomness. We introduced the first known optimal algorithm to generate random bits from an arbitrary Markov chain, a 40-years open question first proposed by Paul Samuelson (Nobel Laureate) in 1968 [paper], and the model of stochatic flow network [paper] for stochastic computing.

(4) Coding for Storage/Communication. We invented balanced modulation (dynamic reading thresholds) [paper] and systematic rank modulation [paper] for storage devices to improve capacity, and proposed layered scheme [paper] for high-dimensional quantum communication [paper] as so-far the most efficient coding scheme.

Educational ExperienceMore>>

2012.7 2015.5

  • Massachusetts Institute of Technology
  • EECS
  • Postdoc

2008.9 2012.7

  • California Institute of Technology
  • EE
  • Master & PhD

2006.9 2008.7

  • Tsinghua University
  • Center for Intelligent and Networked Systems
  • Master

Work Experience

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