Assistant Professor [IEEE-Style Short Biography, Full CV
Deptatment of Electrical & Computer Engineering,
University of California, Santa Barbara (UCSB)
Deptartment of Computer Science (joint
Department of Mathematics, (joint appointment,
effective in 07/2019), UCSB
Ph.D, Massachusetts Institute of Technology
The University of Hong Kong
Huazhong University of Science & Technology
zhengzhang [AT] ece [dot] ucsb [dot] edu,
Address: 4109 Harold Frank
Hall, University of California, Santa Barbara, CA 93106
Two Postdoc Openings available: On-FPGA tensor
learning, and uncertainty quantification for photonic IC.
please check here
Checklist for paper writing: I have prepared a
detailed checklist to help science/engineering graduate
students improving their paper writing.
We work on two topics of mathematical/computational data science:
uncertainty quantification and tensor computation. We currently focus on
the following application fields:
Design automation methodology of electronic and photonic integrated
circuits (IC) under various uncertainties;
Algorithms and algorithm/hardware co-design of high-dimensional,
safe and robust machine learning;
Quantum computing and the design automation aspects of quantum
Our research is supported by both government funding agencies (e.g., NSF)
and industries (e.g., Facebook, Samsung, Xilinx and NVIDIA).
[Award] 07/12/2020: We received
a Facebook Research Award to investigate software/hardware
co-design of machine learning.
[Award] 05/04/2020: Our paper
"Stochastic collocation with non-Gaussian correlated process
variations: Theory, algorithms and applications" (first author:
Chunfeng Cui) received the yearly Best Journal Paper Award from
IEEE Trans. Components, Packaging and Manufacturing Technology.
[Award] 07/27/2019: Chunfeng Cui is selected as a Rising Star in EECS (Electrical
Engineering and Computer Science). She will attend the Rising
Stars workshop at University of Illinois, Urbana-Champaign.
[Paper] 06/04/2019: Two papers got accepted by ICCAD 2019
(acceptance rate: 23.8%).
One is Zichang He's paper "Efficient uncertainty modeling for
system design via mixed integer programming", which is a joint
work with Weilong Cui and Prof. Tim Sherwhood. The second one
"Tucker tensor decomposition on FPGA" is authored by Kaiqi Zhang
and Xiyuan Zhang (undergraduate researcher).
[Paper] 06/03/2019: Chunfeng's paper "High-dimensional
uncertainty quantification of electronic and photonic IC with
non-Gaussian correlated process variations" is accepted by IEEE
Trans. CAD of Integrated Circuits and Systems.
[Award] 04/03/2019: I received the NSF CAREER
[Award] 02/14/2019: Chunfeng Cui is
selected as one of the "Rising Stars in Computational and Data
Sciences". She will attend the Rising Stars workshop at the
Institute of Computational Engineering and Sciences at the
University of Texas, Austin, on April 9-10 of 2019.
[Paper] 12/31/2018: A paper by Jiali Luan (former
undergraduate researcher), "Prediction of multi-dimensional
spatial variation data via Bayesian tensor completion", is
accepted by IEEE Trans. CAD of Integrated Circuits and Systems.
[Paper] 12/16/2018: Chunfeng's paper "Stochastic
collocation with non-Gaussian correlated process variations:
Theory, algorithms and applications" has been accepted by
IEEE Trans. Components Packaging and Manufacturing Technology.
[Codes] 12/06/2018: We have released
some prototyping Matlab codes of stochastic collocation with
non-Gaussian correlated uncertainties.
Link to the paper.
[Award] 10/17/2018: Chunfeng Cui,
Max Gershman (undergraduate) and I received the Best
Paper Award at the 22nd EPEPS held in San Jose, CA.
Link to the paper.
2020: Best Paper Award of IEEE Trans. on Components,
Packaging and Manufacturing Technology; Facebook Research Award.
2019: NSF CAREER Award; Rising Stars in Computational and Data Sciences (by
my advisee Chunfeng Cui); Rising
Stars in EECS (by my advisee Chunfeng Cui).
2018: Best Paper Award of IEEE Transactions on
Components, Packaging and Manufacturing Technology; Best
Award at IEEE EPEPS.
2016: ACM Outstanding PhD Dissertation Award in
Electronic Design Automation (link);
Best Paper Award at International Workshop on Signal and
2015: MIT Microsystems Technology Labs (MTL)
Doctoral Dissertation Seminar Award (link).
2014: Donald O. Pederson Best Paper Award of IEEE
Transactions on CAD of Integrated Circuits and Systems (
Chinese Government Award for Outstanding Graduate Students Abroad
(link to the news);
Best Paper Nomination at IEEE CICC.
Li Ka-Shing Prize (best M.Phil/Ph.D thesis award) from the
University of Hong Kong (link);
best paper nominations at ICCAD2011 and ASP-DAC2011.
Associate Editor: ACM SIGDA Newsletters
TPC Member: ICCAD (2016-2018), DAC
Award Committee: ACM SIGDA Best
Dissertation Award Committee (2018), DAC Best Paper Award Committee
(2018), ICCAD Best Paper Award Committee (2018)
Z. Liu and Z. Zhang, "Quantum-inspired
Hamiltonian Monte Carlo for Bayesian sampling,"
C. Hawkins and Z. Zhang, "Bayesian tensorized neural networks
with automatic rank selection,"
C. Cui and Z. Zhang, "Stochastic
collocation with non-Gaussian correlated process variations: Theory,
algorithms and applications,"
IEEE Trans. Components, Packaging and Manufacturing
Technology, vol. 9, no. 7, pp. 1362-1375, July 2019.
Yearly Best Paper Award, selected as a
Z. Zhang, K. Batselier, H.
Liu, L. Daniel and N. Wong, "Tensor computation: A new framework for
high-dimensional problems in EDA," IEEE Trans.
Computer-Aided Design of Integrated Circuits and Systems, vol.
36, no. 4, pp. 521-536, April. 2017.
Invited Keynote Paper,
TCAD Popular Paper
Z. Zhang, T.-W. Weng and L. Daniel,
tensor recovery for high-dimensional uncertainty quantification of
process variations," IEEE Trans.
Components, Packaging and Manufacturing Technology, vol. 7, no.
5, pp. 687-697, May 2017. Yearly Best Paper Award
Z. Zhang, T. A. El-Moselhy, I. M. Elfadel and L. Daniel,
"Stochastic testing method for transistor-level uncertainty
quantification based on generalized polynomial chaos,"
Trans. Computer-Aided Design of Integrated Circuits and Systems
(TCAD), vol. 32, no. 10, pp. 1533-1545, Oct. 2013.
Donald O. Pederson TCAD Best Paper Award
Z. Zhang, X. Yang, I. V. Oseledets, G. E. Karniadakis and
L. Daniel, "Enabling high-dimensional hierarchical uncertainty
quantification by ANOVA and tensor-train decomposition,"
IEEE Trans. Computer-Aided Design of Integrated
Circuits and Systems, vol. 34, no. 1, pp. 63-76, Jan. 2015.
Z. Zhang and N. Wong, “An
efficient projector-based passivity test for descriptor systems,”
IEEE Trans. Computer-Aided Design of Integrated
Circuits and Systems (TCAD), vol. 29, no. 8, pp. 1203-1214, Aug.