Lei Deng received his B.E. degree and Ph.D. degree from University of Science and Technology of China, Hefei, China, and Tsinghua University, Beijing, China, in 2012 and 2017, respectively. He is currently a Postdoc working with Professor Yuan Xie at Scalable Energy-Efficient Architecture Lab (SEAL), Department of Electrical and Computer Engineering, University of California, Santa Barbara, CA, USA. His research interests include computer architecture, machine learning, brain-inspired computing, tensor analysis, and complex networks. 

Maohua Zhu is now a PhD candidate in ECE Department of University of California, Santa Barbara (UCSB). He received both M.S and B.S. degree in Electronics Engineering from Tsinghua University in 2011 and 2007. After graduation from Tsinghua University, he joined AMD Research Beijing as a research engineer. In June 2015, he started the doctoral program in UCSB supervised by Prof. Yuan Xie. Maohua used to work for AMD and Microsoft Research Asia as an intern during his master program in Tsinghua University. His research interest is hardware acceleration of machine learning algorithms.

Dylan Stow started at the University of California, Santa Barbara in Fall 2015 as a PhD student working with Professor Yuan Xie. Dylan received his M.S in Computer Architecture and VLSI/CAD from UCSB in 2017 and his B.S. degree from Harvey Mudd College in 2013. After graduating, he joined AMD as a physical circuit designer and contributed to the floating-point hardware in the recently-released Zen core.
His current research interests are (1) Architecture and design for emerging die-integration methodologies (e.g. 3D, 2.5D, FOWLP) with a focus on cost-driven design, IP reuse, and heterogeneous process integration, (2) hardware security, with an emphasis on hardware
techniques to prevent side-channel information leakage and IP piracy, and (3) efficient brain-inspired hardware that leverages emerging NVM and packaging technologies. Previously, he researched 3D machine learning accelerators for Qualcomm, floating point microarchitectures for Intel and Oracle Labs, and near-threshold CMOS cell design for yield-driven ultra-low power circuits.

 

Wenqin Huangfu received his B.S. degree from Department of Electronic Engineering, Tsinghua University, in 2016. He started pursuing his Ph.D. degree from the Department of Electrical and Computer Engineering, University of California, Santa Barbara, under the supervision of Professor Yuan Xie in fall 2016. Wenqin’s research interests include hardware acceleration, non – volatile memory, novel computer architecture and design of energy efficient system. 

Tianqi Tang received her B.S. degree in 2014 and her M.S. degree in 2017 from Department of Electronic Engineering in Tsinghua University, Beijing, China, and she is currently a Ph.D. student in UCSB under the supervision of Prof. Yuan Xie. Ms. Tang’s research mainly focuses on (1) Hardware Modeling and Domain Specific Accelerator Design (Project Site: http://mlpat.org/), (2) Processing-In-Memory and Non Volatile Memory. Before joining UCSB, she worked on neural network compression and quantization as an intern in Deephi (a start-up company now acquired by Xilinx) during her master program.

Since 2017, Bangyan Wang works in SEAL lab as a PhD student, advised by Prof. Yuan Xie. His current research area is architecture design for tensor process, especially for sparse tensor, low rank tensor analysis.

Xinfeng Xie started the journey of pursuing his Ph.D. degree from Fall 2017 working with Prof. Yuan Xie in the University of California, Santa Barbara (UCSB). He received his B.S. degree from Peking University, Beijing, China in June 2017 prior to joining UCSB. His current research interests include domain-specific architecture designs for emerging applications and programming language supports for these architectures.