Abanti Basak received her B.S.E. degree in Electrical Engineering from Princeton University in May 2016. She started as a Ph.D. student in the Department of Electrical and Computer Engineering at UCSB under the supervision of Professor Yuan Xie in fall 2016. Her research interests include application-driven computer architecture, specifically benchmarking, performance analysis, and domain-specific architecture for graph workloads.

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.

Ling Liang received his B.S. degree from Beijing University of Posts and Telecommunications in 2015, and his M.S. degree from University of Southern California in 2017. He is currently pursuing the Ph.D. degree from the Department of Electrical and Computer Engineering, University of California, Santa Barbara. Ling’s research interests include tensor computing, neural network security and spiking neural networks.

Gushu Li is currently a Ph.D student at University of California, Santa Barbara since Fall 2017 supervised by Prof. Yuan Xie. He received B.E. in Electronic Engineering from Tsinghua University in 2015 and was a Ph.D student in Computer Science at the University of Chicago from 2015 to 2017.
His research interests are (1) quantum computing architecture and (2) processing-in-memory for emerging techniques.

Personal Website: sites.google.com/view/gushuli

Zheng Qu is currently a Ph.D. student working with Professor Yuan Xie in the University of California, Santa Barbara. He received his B.S. degree in 2018 from Department of Electronic Engineering at Tsinghua University, Beijing, China. Zheng’s research mainly focuses on (1) Energy efficient computing architecture and acceleration for machine learning applications, (2) Tensor application and hardware acceleration.

My name is Yuke Wang, a third-year Ph.D. in computer science at the University of California, Santa Barbara (UCSB), advised by Prof. Yufei Ding.  Before I come to UCSB, I got my B.E. in software engineering from the University of Electronic Science and Technology of China (UESTC).

At UCSB, I have been working on projects in software-hardware co-design for distance-related algorithms, such as KNN, KMeans. I am also interested in deep learning, especially graph neural network (GNN) optimization and acceleration on heterogeneous platforms, such as GPUs.

Anbang Wu is a first-year Ph.D. student in the computer science department with a specialization in quantum computation at the University of California, Santa Barbara. Anbang received both his Master of Engineering degree and Bachelor of Engineering degree in Computer Science from Zhejiang University in China. He is interested in developing quantum computing algorithms and software that squeeze all the computational power out of near-term quantum computers. More specifically, his work examines how to compile quantum programs into efficient and noise-resilient hardware control instructions on specific quantum devices. Recently, he has become interested in quantum machine learning which can describe atypical data patterns that classical machine learning cannot.