Department of Electrical and Computer Engineering
Office: EERC 513
Voice: (906) 487-3116
Email: zhuofeng at mtu dot edu
Group Website: VLSI Design Automation Group
Zhuo Feng received the Ph.D. degree in Electrical and Computer Engineering from Texas A&M University, College Station, TX in 2009, the M.Eng. degree in Electrical and Computer Engineering from National University of Singapore, Singapore, in 2005 and the B.Eng. degree in Information Engineering from Xi'an Jiaotong University, China, in 2003. As of July 2009, he has been a faculty member at the Department of Electrical and Computer Engineering, Michigan Technological University, Houghton, MI, where he is affiliated with the Computer Engineering Group. He received a Faculty Early Career Development (CAREER) Award from the National Science Foundation (NSF) in 2014, a Best Paper Award from ACM/IEEE Design Automation Conference (DAC) in 2013, and two Best Paper Award Nominations from IEEE/ACM International Conference on Computer-Aided Design (ICCAD) in 2006 and 2008. He has served on the technical program committees of major international conferences related to electronic design automation (EDA), including DAC, ICCAD, ASP-DAC, ISQED, and VLSI-DAT, and has been a technical referee for many leading IEEE/ACM journals in VLSI and parallel computing. He also serves as a panelist/reviewer for the National Science Foundation (NSF) and Department of Energy (DoE). He is a Senior Member of IEEE. In 2016, he became a co-founder of LeapLinear Solutions to provide highly scalable software solutions for solving sparse matrices and analyzing graphs (networks) with billions of elements, based on the latest breakthroughs in spectral graph theory.
(12/2017) We received a research award from Keysight Technologies that will support our work on spectral methods for radio-frequency integrated circuit partitioning and analysis.
(11/2017) Our latest paper, "Similarity-Aware Spectral Sparsification by Edge Filtering", is now available on arXiv!
(10/2017) Our latest paper, "Towards Scalable Spectral Clustering via Spectrum-Preserving Sparsification", is now available on arXiv!
(09/2017) Our spectral graph sparsification engine is available for download now! It can robustly preserve the important spectral (structural) graph properties while dramatically reducing the complexity of general large-scale networks, such as social networks, big data graphs, VLSI circuit networks, etc. Check it out!
(09/2017) Prof. Feng is organizing the International Workshop on Design Automation for Analog and Mixed-Signal Circuits. This workshop is co-located with the 2017 International Conference on Computer-Aided Design (ICCAD). The deadline for poster abstract submissions is September 25, 2017.
(07/2017) Prof. Feng gave a research talk entitled: "Towards Practically-Efficient Spectral Sparsification of Graphs" at the SIAM Annual Meeting (AN17) and Carnegie Mellon University, Pittsburgh, PA. (PPT slides)
(06/2017) Our paper, "SAMG: Sparsified Graph Theoretic Algebraic Multigrid for Solving Large Symmetric Diagonally Dominant (SDD) Matrices", has been accepted to IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 2017. Congratulations! (Preprint)
(02/2017) Our paper, "A Spectral Graph Sparsification Approach to Scalable Vectorless Power Grid Integrity Verification", has been accepted to IEEE/ACM Design Automation Conference (DAC), 2017. Congratulations! (PPT slides)
GRASS: GRAph Spectral Sparsifier (download link)
2017 F: EE5496 GPU and Multicore Programming
2017 S: EE5900 Advanced Computational Methods in Computer Engineering
2016 S: EE5780 Advanced VLSI CAD
2015 F: EE4271 VLSI Design
Technical Program Committee Member for:
ACM/IEEE Design Automation Conference (DAC), 2014, 2015, 2016
IEEE/ACM International Conference on Computer-Aided Design (ICCAD) 2015, 2016, 2017
Technical Referee for:
Other Professional Services:
Panelist/Reviewer for NSF and DoE, 2012-
Best Paper Selection Committee, ACM/IEEE Design Automation Conference (DAC)
Several Research/Teaching Assistant (RA/TA) positions are immediately available.
Last updated in September 2017. Copyright by Zhuo Feng.