Computational sciences gets a Harvard institute

Projects such as looking at blood flow in the coronary arteries highlight the value of computation to understand problems in a variety of disciplines, including engineering, medicine, biology, the physical sciences and business.

Seeing the need to expand course offerings and graduate student research opportunities, Cherry Murray, dean of the Harvard School of Engineering and Applied Sciences, announced in September the formation of a new Institute of Applied Computational Sciences, directed by Efthimios Kaxiras, John H. Van Vleck Professor of pure and applied physics at Harvard.

So far, the idea is to expand course offerings while building a full curriculum, Kaxiras says. This fall the university began assembling an advisory committee including Harvard faculty from engineering and physical sciences and the medical and business schools.

“We are bringing together a range of people who have knowledge in computation but also interest in pursuing computational approaches,” Kaxiras says. That focus also extends outside the academy to include individuals from industry and national laboratories to understand computational needs in “the real world.”

David Brown, deputy associate director for science and technology at Lawrence Livermore National Laboratory and an advisor to the new program, says that “like experimentation, computation is a scientific approach, and there is a learning curve. We need scientists who are conversant in computation, which is only just starting to gain the maturity of experimentation and observation.”

Brown noted that Harvard students have access to an IBM Blue Gene testbed, a small machine that shares architecture with the massively parallel supercomputers at the national laboratories. “It enables students to get the codes running there at the Institute, then take them to a big machine and run their simulations.”

In the spring, Harvard plans to offer a few new computational courses that could include computational approaches in fluids or materials science or stochastic methods in computational science. Over the next few years, Kaxiras hopes that the curriculum and framework might be in place for a full-fledged computational science graduate program.