I am a researcher in Computer Architecture at Microsoft Research (MSR). I am also an affiliate associate professor at the Department of Computer Science and Engineering at University of Washington.

My research lies at the intersection of computer architecture, systems, and biology. As traditional semiconductor scaling has started to slow down, I investigate alternative approaches to continue the improvement we have been seeing in computer systems over the last few decades. Approaches I have been studying include hardware accelerators for machine learning, emerging memory technologies, and the use of biotechnology to the benefit of the IT industry. I also work on system software for these new architectures.

Lately, my focus has been on creating an end-to-end system that stores digital data in DNA. I have the privilege to work with a team of brilliant researchers and we have been making quite a lot of progress. Check out our latest announcement.

I received my PhD in Computer Science from University of Illinois at Urbana-Champaign in 2007. During my studies, I’ve collaborated very closely with top-notch researchers at IBM Research, where I also worked on the Blue Gene project. After graduating, I worked for almost 2 years at AMD Research, where I also had amazing colleagues.

For a complete list of publications, please click the tab “Publications” above.

If you are interested in DNA storage, click here.



Established: June 2, 2015

File System for Approximate Storage Approximate storage allows tradeoffs between data storage precision and other desirable characteristics such as energy savings, higher performance or higher density. It consists of placing different sets of data in memories or storage with different precision guarantees. For example, data may be partitioned into a “precise” portion with the highest possible reliability and fidelity in storage (e.g., 10-16 unrecoverable bit error rate) and an “approximate” portion with lower reliability (e.g.,…


Established: April 17, 2015

The Kamino project explores ways in which systems should adopt new memory technologies including SSDs (NAND-Flash), battery-backed DRAM and emerging non-volatile memory technologies (phase change memory, memristors, spin-torque transfer memory, etc.) for increased performance and efficiency. The project explores how to best leverage such new memory technologies inside systems of all sizes and shapes: from mobile to data center scale. Interns Jian Huang, Georgia Tech (2013, 2014, & 2015) Jing Li, UCSD (2013) Yanqi Zhou,…

DNA Storage

Established: January 1, 2015

The amount of digital data produced has long been outpacing the amount of storage available. This project enables molecular-level data storage into DNA molecules by leveraging biotechnology advances in synthesizing, manipulating and sequencing DNA to develop archival storage. Microsoft and University of Washington researchers are collaborating to use DNA as a high density, durable and easy-to-manipulate storage medium. Demand for data storage is growing exponentially, but the capacity of existing storage media is not keeping…



A DNA-Based Archival Storage System
James Bornholt, Randolph Lopez, Douglas Carmean, Luis Ceze, Georg Seelig, Karin Strauss, in ASPLOS 2016 (International Conference on Architectural Support for Programming Languages and Operating Systems) - to appear, ACM – Association for Computing Machinery, April 1, 2016, View abstract, Download PDF






Pocket Cloudlets
Emmanouil Koukoumidis, Dimitrios Lymberopoulos, Karin Strauss, Jie Liu, Doug Burger, in ASPLOS 2011 (International Conference on Architectural Support for Programming Languages and Operating Systems, ACM, March 1, 2011, View abstract, Download PDF








An Overview of the Blue Gene/L System Software Organization
George Almasi, Ralph Bellofatto, José Brunheroto, Călin Caşcaval, José G. Castaños, Luís Ceze, Paul Crumley, C. Christopher Erway, Joseph Gagliano, Derek Lieber, José E. Moreira, Alda Sanomiya, Karin Strauss, in EuroPar 2003 (International Conference on Parallel and Distributed Computing), Association for Computing Machinery, Inc., August 1, 2003, View abstract, Download PDF