zhengyaZhengya Zhang zhengya at
Associate Professor, Department of Electrical Engineering and Computer Science

Prof. Zhang has been with the Department of EECS at the University of Michigan since 2009. His group’s research is in the area of low-power and high-performance VLSI circuits and systems for computing, communications and signal processing. He received his B.A.Sc. degree in computer engineering from the University of Waterloo in 2003, and M.S. and Ph.D. degrees in electrical engineering from UC Berkeley in 2005 and 2009.


Postdoctoral Researcher

weiWei Tang weitang at
Research Fellow

Dr. Tang received the B.S. degree from National Chiao Tung University, Hsinchu, Taiwan, in 2011, and the M.S. and Ph.D. degrees in electrical engineering from the University of Michigan at Ann Arbor, Ann Arbor, MI, USA, in 2019. He was a Visiting Ph.D. Student with Lund University, Lund, Sweden, and a Graduate Research Intern with Intel Labs, Santa Clara, CA, USA. He is currently a Post-Doctoral Research Fellow with the University of Michigan at Ann Arbor. His research interests are in IC designs for communications and machine learning.

Ph.D. Students

chesterChester Liu (Ph.D. 2020) cwhliu at
B.S., Electrical Engineering, National Tsing Hua University, Taiwan
M.S., Electrical Engineering, National Taiwan University, Taiwan

Chester’s interests are in machine learning technologies, processor architecture, and chip design for real-time applications such as autonomous driving and robotics. Chester dabbles in design methodology, compilers and embedded systems. Before coming to Michigan, Chester was a R&D engineer at MediaTek in Hsinchu, Taiwan.


sunggunSung-Gun Cho (Ph.D. 2020) sunggun at
B.S., Electrical Engineering, KAIST, Korea
M.S., Electrical Engineering, KAIST, Korea

Sung-Gun’s interests are in microarchitecture and circuit design for neuromorphic computing, and applying signal processing techniques to overcome nonidealities of emerging devices. Sung-Gun was previously trained in communication systems and memory ECC. He worked at SK Hynix in Korea before joining the group.


alexChing-En (Alex) Lee (Ph.D. 2021) lchingen at
B.S., Electrical Engineering, National Tsing Hua University, Taiwan
M.S., Electrical Engineering, UCLA

Alex’s research focus is on modern machine learning, deep learning, computer vision and their realization in high-performance energy-efficient SoCs and domain-specific computing systems. His research drives the next-generation scale-up and scale-out computing acceleration solution for cognition and learning in intelligent machines. He interned at the Nvidia Architecture Research Group (ARG) in Santa Clara, CA, focusing on machine learning accelerator and processor architectures. He was a research scientist at Intel Labs at Hillsboro, OR, from 2015 to 2016, working on next-generation baseband processors integrating digital self-interference cancellation for full duplex communication.

teyuhTeyuh Chou (Ph.D. 2021) teyuh at
B.S., Electrical Engineering, National Central University, Taiwan
M.S., Electrical Engineering, National Chiao Tung University, Taiwan

Teyuh’s interests are in designing compute systems using nano devices. She is currently working on a co-processing microarchitecture to realize in-memory, scientific computing. Teyuh worked on RRAM-based hardware neural network systems for her M.S. thesis at NCTU. She previously interned in the Memory Solution Division at TSMC in Hsinchu, Taiwan.


jie-fangJie-Fang Zhang (Ph.D. 2022) jfzhang at
B.S., Electrical Engineering, National Taiwan University, Taiwan

Jie-Fang’s interests are in efficient and high-performance microarchitectures and design methodologies. He is currently involved in designing deep CNN accelerators for real-time, embedded applications. He is also developing design methodologies to automate the mapping of neural networks to configurable hardware.

jacobJacob Botimer (Ph.D. 2022) botimerj at
B.S., Electrical Engineering, University of Michigan

Jacob is interested in mixed-signal circuits including ADCs, DACs, and timing circuits for peripherals, I/Os and links that connect high-performance compute and memory blocks. He is currently working on the interface circuits for in-memory compute systems.


reidReid Pinkham (Ph.D. 2022) pinkhamr at
B.S., Physics and Electrical Engineering, University of Michigan

Reid is focusing on developing hardware accelerators for neural networks. He is currently working on a flexible FPGA based accelerator with the initial application of performing image segmentation in real time. Reid did research at CERN while he was an undergrad. He contributed to high-performance FPGA designs for the instrumentation at CERN to analyze high-energy particles.


jerryJunkang Zhu (Ph.D. 2023) jkzhu at
B.S., Electrical Engineering, Nanjing University, China

Junkang’s interest is in processor design and digital architecture. He is currently working on processor design and system integration for AI accelerator based on RRAM crossbar devices.



yaoyuYaoyu Tao (Ph.D. 2021) taoyaoyu at
B.S., Electrical Engineering, University of Michigan
M.S., Electrical Engineering, University of Michigan/Stanford University




Visiting Graduate Students

Yi-Chung Wu, National Taiwan University, 2019-2020
Haolei Ye, Australian National University, 2019-2020


Group Alumni

Doctoral Graduates
Thomas Chen (Ph.D. 2019)
Wei Tang (Ph.D. 2019), University of Michigan, Ann Arbor, MI
Shiming Song (Ph.D. 2018), Cadence, San Jose, CA
Shuanghong Sun (Ph.D. 2017), Intel, San Jose, CA
Phil Knag (Ph.D. 2015), Intel Labs, Hillsboro, OR
Jung Kuk Kim (Ph.D. 2015, Co-Advised by Prof. Jeff Fessler), Apple, Cupertino, CA
Chia-Hsiang Chen (Ph.D. 2014), Apple, Cupertino, CA
Youn Sung Park (Ph.D. 2014), Syntiant, Irvine, CA

Co-Advised Doctoral Graduates
Hsi-Shou Wu (Ph.D. 2018, Co-Advised with Prof. Marios Papaefthymiou)
Shengshuo Lu (Ph.D. 2017, Co-Advised with Prof. Marios Papaefthymiou), AMD, Austin, TX

M.S. Graduates
Vishishtha Bothra (M.S. 2016), Apple, Cupertino, CA

2018-2019: Jacqueline Disanto, Ian Fan
2017-2018: Carl Steinhauser, Yueying Li, Austin Xu
2016-2017: Jacob Cooper, Katherine Banas
2014-2015: Zelin Zhang, Scott Su, Yue Cao, Kyle Yan
2013-2014: Dike Zhou, Yanran Yang, Matthew Lindstrom, Tie Chen
2012-2013: Kamal Knight, Bochao Wang, Yiqun Zhang
2011-2012: Paul Rigge, Mario Admon, Xiaojue Zeng, Haoran Li
2010-2011: Kai Boon Ee, Katherine Dropiewski, Hao Shi, Wenjia Liu