Dr. Zizhong (Jeffrey) Chen is a faculty member in the Department of Computer Science and Engineering at the University of California, Riverside. He specializes in high performance computing, big data analytics, parallel and distributed systems, numerical algorithms and software, and large scale computer simulations. His research has been supported by National Science Foundation, Department of Energy, CMG Reservoir Simulation Foundation, Abu Dhabi National Oil Company, Nvidia, and Microsoft Corporation. He has published over 100 papers with many in highly competitive conferences and journals such as SC, HPDC, PPoPP, ICS, IPDPS, TPDS, TC, JPDC, PARCO, SIMAX, SISC, and IBMRD. He has received a CAREER Award from the U.S. National Science Foundation and a Best Paper Award from the International Supercomputing Conference. Dr. Chen is a Senior Member of the IEEE and a Life Member of the ACM. He currently serves as a Subject Area Editor for Elsevier Parallel Computing journal (PARCO) and an Associate Editor for IEEE Transactions on Parallel and Distributed Systems (TPDS).

Ms. Elisabeth Giem received a Master's degree in Computational and Applied Mathematics from Rice University, and a Master's degree in Pure Mathematics from the University of California, Riverside (UCR). She received two Bachelor's degree in Pure Mathematics and Music (concentration Performance) from UCR. She won the Chancellor's Scholarship, CMST Fellowship, CTFMS Fellowship, and Gluck Fellowship during her undergraduate tenure. She won the Academic Excellence Award in Mathematics in her senior year. She has been concertmaster, principal violist, and soprano soloist for the UCR Orchestra, UCR Chamber Orchestra, and UCR Chamber Singers. She received the VIGRE Fellowship at Rice University. Ms. Elisabeth Giem joined the SuperLab in Fall 2018, and been awarded the (NICE) Fellowship. Her research interests include but are not limited to high-performance computing, parallel and distributed systems, big data analytics, computational entomology, and numerical linear algebra algorithms and software. She is currently doing an internship at Sandia National Laboratories.

Mr. Jiajun Huang received his Bachelor's degree in Electronic Information Engineering from the University of Electronic Science and Technology of China (UESTC) and the University of Glasgow (Honors of the First Class) in 2021. He won the 1st Class Academic Scholarship, James Watt Innovative Talent Scholarship, UESTC Outstanding Student Scholarship, and Excellent Bachelor's Degree Thesis Award during his undergraduate study. He is a professional saxophone player, a professional table tennis player, and has mastered many other musical instruments. He joined the SuperLab in Winter 2022. His research interests include but are not limited to Distributed and Parallel Computing/System, High Performance Computing, and General Artificial Intelligence. He is currently doing an internship at Argonne National Laboratory.

Mr. Zizhe Jian received his bachelor's degree in Microelectronics and Solid-State Electronics with minor in Computer Science from the School of the Gifted Young of the University of Science and Technology of China (USTC) in 2022. He won Scholarship for Excellent Student in USTC multiple times. He also took part in robotics competitions and received awards. Mr. Jian joined the SuperLab in Fall 2022. His research interests include but not limited to High Performance Computing, GPU computing, and its application in Artificial Intelligence.

Mr. Jinyang Liu received his Master degree in Data Science from Peking University in 2019. He received his Bachelor's degree in Mathematics and applied Mathematics from Peking Univeristy in 2016. Mr. Jinyang Liu won 'Outstanding Research Award' and received 'May 4th Scholarship' from Peking University. He also won 'Outstanding Graduate Award' when he graduated from Peking University in 2019. Mr. Jinyang Liu joined the SuperLab in Fall 2019. His research interests include but are not limited to High Performance Computing, Big Data Alalytics, and Artificial Intelligence. He is currently doing an internship at Argonne National Laboratory.

Mr. Shixun Wu received his Master's degree in Electrical Engineering from Columbia University in 2022. He received his Bachelor,s degree in Computer Science with minor in Economics from Peking University (PKU) in 2020. He received 'May 4th Scholarship' from Peking University. Mr. Shixun Wu joined the SuperLab in Fall 2022. His research interests include but not limited to GPU computing, high-performance machine learning, and Artificial Intelligence.

Mr. Yujia Zhai received a Master's degree in Computational Chemistry from Duke University in 2018. He received his Bachelor's degree in Chemistry from University of Science and Technology of China (USTC) in 2016. He won first prize in National Chemistry Olympics Contest (Anhui Province) in 2011, the Silver Metal in the 25th National Chemistry Olympics Contest in China in the same year, and also Lan-Ying Lin Fellowship, Xue-Zhou Wu Fellowship, Outstanding Freshmen Fellowship and Outstanding Undergraduate Fellowship during undergraduate studies at USTC. His technical skill set spans CUDA, DPC++, SYCL, x86 assembly, SIMD, OpenMP and MPI. He specialized in performance optimization for math libraries on CPUs, GPUs and heterogeneous platforms. He has interned with the XPU Architecture Research team at Intel Corporation working on GPU-accelerated homomorphic encryption in 2021. In 2022 Spring, he has worked on GPU-accelerated ML systems with the AML-MLsys team at ByteDance/TikTok USA. In 2022 Summer, He has been with the Fast Kernels team at NVIDIA Corporation as an engineering intern working on CUTLASS project. He will return to the same team at NVIDIA as a full-time employee after graduation (expected in summer 2023).

Vincent Tran is a sophomore (Class of 2025) at Portola High School, and for the majority of his academic career, he has been interested in the fields of analytical computer science and math. In the context of a mathematical lab, he enjoys reading and understanding proofs in the context of linear algebra and differential equations. He is a one-time AIME qualifier in the year of 2022-2023. Furthermore, in the United States of America Computing Olympiad (formally abbreviated as USACO), Vincent participates in the Platinum division as of December of 2022, which uniquely identifies the top 250 out of 20,000 total contestants. Vincent joined the SuperLab in Spring 2022. His research interests include but not limited to linear algebra software, bid data analytics, and graph algorithms.

Degree: PhD, Spring 2022. (BS from from Peking University (PKU) in 2014).
Internship Experience: Argonne National Laboratory.
Employment: Assistant Professor, University of Alabama at Birmingham.

Degree: PhD, Spring 2022. (BS from University of Electronic Science and Technology of China, 2016).
Internship Experience: Argonne National Laboratory.
Employment: Software Engineer, NVIDIA.

Degree: Ph.D., Fall 2020. (BS from HUST in 2015).
Dissertation: Designing Efficient and Resilient Lossy Compressors for Large-Scale Scientific Computing.
Internship Experience: Argonne National Laboratory.
Employment: Research Scientist, Facebook.

Degree: MS, Fall 2019. (BS from USTC in 2015).
MS Project: Data transfer between scientific facilities - bottleneck analysis, insights and optimizations.
Internship Experience: Argonne National Laboratory (2018-2019)
Employment: Software Engineer, Facebook.

Degree: Ph.D., Fall 2019. (BS from Peking University in 2014).
Dissertation: Toward Resilience and Data Reduction in Exascale Scientific Computing.
Internship Experience: Los Alamos National Laboratory (long term), Pacific Northwest National Laboratory, and Argonne National Laboratory.
Employment: Assistant Professor, University of Kentucky.

Degree: Ph.D., Spring 2019. (BS from BJUT in 2012).
Dissertation: Fault Tolerant and Energy Efficient One-sided Matrix Decompositions on Heterogeneous Systems with GPUs.
Internship Experience: Los Alamos National Laboratory (long term), Pacific Northwest National Laboratory.
Employment: Computer Scientist, Oak Ridge National Laboratory.

Degree: Ph.D., 2018. (BS from USTC in 2013).
Dissertation: Fault Tolerance for Iterative Methods in High-Performance Computing.
Internship Experience: Brookhaven National Laboratory (2018), Argonne National Laboratory (2017), Pacific Northwest National Laboratory (2016).
Employment: Associate Professor, Indiana University Bloomington. IEEE TCHPC Early Career Researchers Award for Excellence in HPC, 2020.

Degree: Ph.D., 2018. (Co-advised with Rajiv Gupta.)
Dissertation: Pre- and Post-Deployment Dynamic Bug Detection Techniques for MPI Programs.
Employment: Software Engineer, Argo AI.

Degree: Ph.D., Fall 2016. (BS from USTC in 2011).
Dissertation: Silent Data Corruption Resilient Matrix Factorizations on Distributed Memory System.
Internship Experience: Los Alamos National Laboratory (summer 2015, fall 2015, and winter 2016), Amazon (summer 2014), Oak Ridge National Laboratory (summer 2013).
Employment: Assistant Professor, University of Houston. NSF CAREER Award, 2022.

Degree: MS, Fall 2016. (BS from Jilin University in 2014).
MS project: Reliable and High Performance BLAS Library.
Employment: Software Engineer, Microsoft.

Degree: Ph.D., Fall 2015. (MS from East China Normal University in 2010)
Dissertation: The Interplay between Energy Efficiency and Resilience in Scalable High Performance Computing Systems.
Internship Experience: Pacific Northwest National Laboratory, 2014.
Employment: Product Manager II Lead, Azure HPC+AI at Microsoft.

Degree: Ph.D., Fall 2014. (BS from Colorado School of Mines in 2009).
Dissertation: Checksum-Based Fault Tolerance for LU Factorization.
Awards: NSF Graduate Fellowship, UCR Dean's Distinguished Fellowship, IEEE TCPP PhD Forum Best Paper Award.

Degree: Ph.D., Spring 2013 (Co-Advised with Tracy Camp).
Dissertation: Parallelization and Fault Tolerance Supporting Near-real-time Data Processing For Bioremediation.
Internship Experience: ConocoPhillips, 2011.
Employment: Director of Data Engineering at ConocoPhillips.

Degree: Ph.D., Fall 2012.
Dissertation: Optimizing Multi-dimensional MPI Communications on Multi-core Architectures.
Employment: Associate Professor, South Dakota School of Mines and Technology.

Position: Visiting Scholar, 2013~2014.
Current Affiliation: Professor and Associate Dean, College of Computer Science and Technology, Beijing University of Technology.

Position: Visiting Scholar, 2013~2014.
Current Affiliation: Professor, School of Computer Science and Technology, Zhejiang University.

Degree: MS, Fall 2013. (BS from USTC in 2011).
Current Employment: Bloomberg LP.

Degree: MS, Summer 2012.
Current Employment: Google Inc.

Degree: MS, Summer 2012.
Current Employment: Mentor Graphics.

Degree: MS, Summer 2011. (MS from Central South University in 2009).
Current Employment: SDL International America Inc.