Aydın Buluç (Principal Investigator), is a Senior Scientist at the Lawrence Berkeley National Lab and an Adjunct Assistant Professor of Electrical Engineering and Computer Sciences at UC Berkeley. Previously, he was a Luis W. Alvarez postdoctoral fellow at LBNL and a visiting scientist at the Simons Institute for the Theory of Computing. He received his PhD in Computer Science from the University of California, Santa Barbara in 2010 and his BS in Computer Science and Engineering from Sabanci University, Turkey in 2005. Dr. Buluç is a recipient of the DOE Early Career Award in 2013 and the IEEE TCSC Award for Excellence for Early Career Researchers in 2015. He was also a founding associate editor of the ACM Transactions on Parallel Computing. More info in his personal website:

Oguz Selvitopi is a Research Scientist in the Performance and Algorithms group of Computer Science Department at Lawrence Berkeley National Laboratory, where he was previously a Postdoctoral Research Fellow. His research interests are high performance computing, parallel sparse matrix computations, combinatorial scientific computing, and bioinformatics. Oguz received his Ph.D. in computer engineering from Bilkent University, Turkey in 2016.

Yu-Hang Tang is a Research Scientist at the Lawrence Berkeley National Laboratory. His recent research centers around the development of machine learning algorithms, in particular graph-based methods, for solving problems found in many science disciplines such as chemistry, materials, and traffic modeling. Prior to that, he has years of experience in designing computational method and software stacks for modeling microscopic and mesoscopic systems. He is the author of several open-source software packages, including the LAMMPS USER-MESO GPU-accelerated package for Dissipative Particle Dynamics (DPD) and Smoothed Particle Hydrodynamics (SPH), the Multiscale Universal Interface library for coupling standalone solvers to perform multiscale simulations, and the OpenRBC code for simulating red blood cells at protein resolution. Yu-Hang received his Ph.D. in applied mathematics from Brown University in 2017, and his B.E in polymer science from Zhejiang University in 2011.

Can Kizilkale is a postdoctoral fellow with the Performance and Algorithms Group. His research interests are Optimization (Convex, Combinatorial), Mathematical Modeling, Matrix Analysis, and Game Theory. His recent focus is on fast first order methods. He received his PhD. degree in Computer Science from University of California Santa Barbara in Summer 2019

Helen Xu is a postdoctoral research fellow in the Performance and Algorithms group of the Computer Science Department at Lawrence Berkeley National Laboratory. Her research interests include parallel computing, cache-efficient algorithms, and performance engineering. She received her PhD from MIT in 2022. For more information, please visit her website.

Giulia Guidi is a Ph.D. student in Computer Science at UC Berkeley and a graduate research assistant at the Computational Research Division of Lawrence Berkeley National Laboratory advised by Aydın Buluç and Kathy Yelick. Giulia is a 2020 SIGHPC Computational & Data Science Fellow. She received both my M.Sc. in Biomedical Engineering and B.Sc. in Biomedical Engineering at Politecnico di Milano. Giulia's research is focused on the development of a novel algorithm to de novo assemble genomes in distributed memory using long-read sequencing data as part of the ExaBiome Project. Giulia is interested in the intersection of HPC and Computational Biology as enabling technology for faster, high-quality bioinformatics and biomedical research. More info in her personal website:

Alok Tripathy is a Ph.D. student at UC Berkeley interested in designing algorithms and programming models that leverage high-performance systems, particularly heterogeneous systems. He graduated with a B.S. in Computer Science from Georgia Tech. Alok is a NSF GRFP fellow. More info on his personal website:

Vivek Bharadwaj is a PhD student at UC Berkeley. His interests include sparse linear algebra kernels, tensor decomposition, and machine learning - more on his personal website (link: He received his BS from Caltech, where he majored in Computer Science and Mathematics. Vivek is a DOE CSGF fellow (2021-2025).

Tianyu Liang is a Ph.D. student at UC Berkeley advised by Aydın Buluç and James Demmel. His research interests are numerical linear algebra, parallel/distributed computing, and fast algorithms. Tianyu is a NSF GRFP fellow.

Gabriel Raulet is a Computer Systems Engineer at Lawrence Berkeley National Lab. His interests include graph algorithms, computational biology, parallel computing, and theory of computation. He graduated with a B.S. from UC Davis, where he majored in Computer Science and minored in Mathematics.

Koby Hayashi is a PhD student in the College of Computing at the Georgia Institute of Technology. Recently, he has begun working on methods for mining complex patterns in various types of graphs such as signed graphs, oriented graphs, and hypergraphs. Previously, he worked on constrained low-rank approximation with a focus on parallel algorithms. Algorithms developed compute dense Non-negative Tensor Factorizations and Symmetric Non-negative Matrix Factorizations. Both of which are available in the software package Parallel Low-rank Approximation with Non-negativity Constraints. His studies are supported by the Computational Science Graduate Fellowship.

Past members (some before the group/team/lab was even named)

Past visitors:

  • Caitlin Whitter (Purdue), CSGF Summer Student at LBNL (2019)

  • Sureyya Emre Kurt (Utah), Summer Research Intern at LBNL (2019).

  • Elizabeth Koning (Calvin College), Summer Research Intern at UC Berkeley (2019)

  • Yusuke Nagasaka (Tokyo Institute of Technology), Summer Research Intern at LBNL (2017).

  • Patrick Flick (Georgia Tech), Summer Research Intern at LBNL (2016).

  • Adam Sealfon (MIT), CSGF Summer Student at LBNL (2015)

  • Adam Lugowski (UCSB), Summer Research Intern at LBNL (2012).