An interesting interview with Alex Szalay, Professor of Physics and Astronomy at Johns Hopkins University – about data-intensive computing — in Datanami this week:

When it comes to thought leadership that bridges the divides between scientific investigation, technology and the tools and applications that make research possible … Szalay is one of the first scientists that springs to mind.

 

Szalay, whom we will dub “Dr. Data” for reasons that will explained in a moment, is a distinguished professor in the university’s Department of Physics and Astronomy. Aside from his role as a scientist — an end user of high performance computing hardware and applications — he also serves director of the JHU Institute for Data Intensive Engineering and Science.

 

Part of what makes Dr. Szalay unique is that he sees scientific technology from both sides of the fence; both as a physicist reliant on massive simulations and supercomputers — and as a computer scientist probing the underlying performance, efficiency and architectural issues that are increasingly important in the age of data-intensive computing. He is the architect for the Science Archive of the Sloan Digital Sky Survey and project director of the NSF-funded National Virtual Observatory and has penned over 340 journal articles on topics including theoretical cosmology, observational astronomy, spatial statistics, and computer science.

 

Szalay’s world of diverse research hinges on solving big data problems and working with the complex algorithms and applications that are creating it. In addition to his astronomy and physics research, Szalay has been presenting on topics such as “Extreme Data-Intensive Computing with Databases” — a topic that caught our attention recently and prompted the following interview.

 

What is missing in current computing architectures as we look toward the future of data-intensive computing (i.e. involving not just petabytes, but exabytes of data)?

 

» Read more: “The New Era of Computing”