The Guarini School of Graduate and Advanced Studies this fall is launching a new PhD program in computational science and modeling, a rapidly evolving field that uses mathematical frameworks and large-scale computation to turn vast amounts of data into meaningful insight.
“Many of the most pressing challenges facing society—climate change, energy systems, public health—are fundamentally complex systems problems that cross disciplines,” says Anne Gelb, the John G. Kemeny Parents Professor of Mathematics and the director of the new Computational Science and Modeling Program.
A textbook example is sea ice research, says Gelb, an applied mathematician who leads the Sea Ice Modeling and Data Assimilation project, a multidisciplinary university research initiative sponsored by the Department of Defense through the Office of Naval Research.
The Arctic Ocean is a moving mosaic of ice floes that fracture under stress and drift across vast distances, steered by changes in temperature and wind. Capturing all those interactions in a single framework is nearly impossible without computation.
At Dartmouth, engineers, geophysicists, and mathematicians like Gelb work together to translate the physics of ice into computational models that approximate the tangled equations governing ice motion, thickness, and environmental forces, helping scientists anticipate changes in the Arctic and improve navigation and climate projections.
The new computational science and modeling program aims to equip future researchers with vital tools—strong technical skills and the ability to “speak more than one language” of science—to take on these kinds of complex problems.
“At the Guarini School for Graduate and Advanced Studies, we are building interdisciplinary graduate programs that bring disciplines together and train researchers to tackle complex problems from multiple perspectives with the depth, rigor, and creativity that define research excellence at Dartmouth,” says Guarini Dean Jon Kull ’88.
Another area where computational science and modeling is being applied is in analytical research by Raghav Singal, associate professor of business administration, who leverages data to develop application-driven models that help businesses evaluate current systems and optimize decision-making.
For instance, a new model developed by Singal shows what could happen if health insurers approved care on time, and how those decisions change patient outcomes.
The impetus to establish the program originated from the University Seminar series on computational science coordinated by Gelb in the 2023-2024 academic year.
Gelb commends Dartmouth’s support for establishing the program. “That’s one of the really nice things about Dartmouth. If you have an idea, they let you see if you can work it out.”
Faculty from across the sciences, engineering, and medicine were eager to join the program, says Gelb.
Students will choose from three areas of focus: physical and natural sciences, social and biological sciences, and operations research. They will have the opportunity to pursue their research interests, working with advisers from different departments.
“We are deliberately looking for people who are thoughtful about the problems they are considering and have an appetite for interdisciplinary research,” says Gelb, who believes that co-mentoring students is a strong catalyst for creating new research collaborations.
As scientific questions become more complex and data-rich, computational science and modeling is becoming central to how discovery happens, says Gelb.
“We need to build the infrastructure that allows us to be more interdisciplinary and collaborative and train young people to think this way,” she says.
