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Over the last ten years, MIT has provided doctoral-level education in computational science and engineering (CSE) solely through an interdisciplinary initiative tailored for students applying computation within a chosen science or engineering discipline.

As enthusiasm increased among students primarily concentrating on enhancing CSE techniques, it became evident that a specific academic establishment for this cohort — students and faculty deeply dedicated to the principles of computational science and engineering — was essential.

Now, with a separate CSE PhD program, they have not only a venue for nurturing exploration in the interrelated methodological dimensions of computational science and engineering but also a close-knit community.

“This program acknowledges the existence of computational science and engineering as a unique discipline, allowing you to engage in this work independently from mechanical or chemical engineering, but rather on its own merit,” states Nicolas Hadjiconstantinou, co-director of the Center for Computational Science and Engineering (CCSE).

Launched by CCSE in 2023, the independent program merges both coursework and a thesis, similar to other MIT PhD programs, yet its methodological emphasis distinguishes it from other offerings at the Institute.

“What’s distinctive about this program is its independence from any single department. The independent program focuses fundamentally on computational science and interdisciplinary methodology. We link this research with individuals across a variety of application sectors, including oceanographers, materials scientists, and those concentrated on aeronautics and astronautics, among others,” explains outgoing co-director Youssef Marzouk, now the associate dean of the MIT Schwarzman College of Computing.

Widening perspectives

Hadjiconstantinou, the Quentin Berg Professor of Mechanical Engineering, and Marzouk, the Breene M. Kerr Professor of Aeronautics and Astronautics, have guided the center’s initiatives since 2018 and collaboratively shaped the program and curriculum. They purposefully designed a program that cultivates students’ individual research while simultaneously exposing them to the breadth of the field.

To broaden students’ perspectives and foster a collaborative environment, the PhD in CSE program includes two well-received seminar series: weekly community seminars that primarily feature internal presenters (current graduate students, postdocs, research scientists, and faculty), along with monthly distinguished seminars in CSE that are Institute-wide and invite external speakers from various institutions and industry sectors.

“Something unexpected about the program has been the seminars. I anticipated it would include the same individuals I encounter in my classes and labs, but it’s much wider than that,” remarks Emily Williams, a fourth-year PhD student and a Department of Energy Computational Science graduate fellow. “One of the most intriguing seminars covered simulating fluid dynamics for biomedical purposes. My expertise lies in fluid dynamics, so I comprehend that aspect, but witnessing it applied in a completely different domain than my own was enlightening,” explains Williams.

That seminar, “Astrophysical Fluid Dynamics at Exascale,” delivered by James Stone, a professor in the School of Natural Sciences at the Institute for Advanced Study and at Princeton University, exemplified one of many occasions for CSE students to interact with specialists in small groups, gaining academic insights as well as a broader view on potential career paths.

Crafting for impact

The interdisciplinary PhD program acted as a starting point from which Hadjiconstantinou and Marzouk developed a new offering that was distinctly its own.

For Marzouk, this meant emphasizing the expansion of the independent program to continuously evolve and adapt, maintaining relevance as technology advances rapidly: “In my perspective, the vitality of this program stems from the fact that science and engineering applications today fundamentally rely on computation, whether it involves engineering design or scientific discovery. Therefore, it is crucial to conduct research on the fundamental aspects of this computation. This research must also be influenced by how we implement it so that scientists or engineers will effectively utilize it,” says Marzouk.

The curriculum is organized around six core focus areas, or “ways of thinking,” essential to CSE:

• Discretization and numerical techniques for partial differential equations;
• Optimization strategies;
• Inference, statistical computing, and data-driven modeling;
• High-performance computing, software development, and algorithms;
• Mathematical foundations (e.g., functional analysis, probability); and
• Modeling (i.e., a subject that addresses computational modeling in any scientific or engineering discipline).

Students curate and assemble their own thesis committee that includes faculty from various MIT departments, not exclusively those affiliated with CCSE. The integration of a curriculum that is “contemporary and relevant to what employers seek in both industry and academia,” according to Williams, along with the ability to construct a team of engaged advisors, facilitates a level of specialization hard to find elsewhere.

“Academically, I find that this program is crafted in a highly adaptable and interdisciplinary manner. You possess considerable control regarding the direction you wish to pursue,” says Rosen Yu, a PhD student. Yu’s research centers on engineering design optimization, an interest she identified during her initial year of research at MIT with Professor Faez Ahmed. The CSE PhD was about to commence, and it became evident that her research interests were more aligned with computation than the existing mechanical engineering program; it felt like a natural match.

“At other institutions, you typically encounter either a pure computer science program or an engineering department with minimal overlap. However, I enjoy describing this CSE program as the ‘adhesive’ between these two communities,” shares Yu.

That “adhesive” is strengthening, with an increasing number of students enrolling each year, along with more Institute faculty and staff becoming affiliated with CSE. While the thesis topics of students span from Williams’ stochastic methods for model reduction of multiscale chaotic systems to scalable and robust GPU-based optimization for energy systems, the core aim of the program remains unchanged: to cultivate students and research that will create a significant impact.

“That’s why MIT is known as an ‘Institute of Technology’ and not a ‘university.’ There is always this inquiry, regardless of your field of study: what is its purpose? Our students will proceed to work in systems biology, climate simulation models, electrification, hypersonic vehicles, and beyond, but the fundamental objective is that their research contributes to meaningful advancements,” asserts Hadjiconstantinou.

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