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Brown launches master’s program in data-enabled computational engineering and science

Brown launches master’s program in data-enabled computational engineering and science

A new one-year master’s program will take a deep dive into the state-of-the-art simulation, modeling and data science techniques widely used across engineering disciplines.

PROVIDENCE, R.I. [Brown University] — Drawing on longstanding research and teaching strengths in engineering and applied mathematics, Brown University is launching a new one-year master’s program in data-enabled computational engineering and science.

The program, which is now accepting applicants, aims to provide students with a comprehensive understanding of the computational modeling and data science techniques that have become standard in industry and academia.

“Computational modeling and simulation are the primary means of analysis in national laboratories and industry,” said Yuri Bazilevs, a professor at Brown’s School of Engineering and the program’s director. “Realistic applications in computational science and engineering involve highly complex datasets that need to be incorporated in simulations for validation and robust predictions. Our program will prepare students to use such state-of-the-art modeling techniques, as well as to properly interpret and utilize the output they produce.”

Modeling and simulation has become ubiquitous in a wide variety of engineering applications, from testing the physical properties of structures and materials to understanding the flow of fluids through pipes or over airplane wings. These techniques include finite element analysis — a powerful method of modeling highly complex systems by dividing systems into smaller (finite) parts. Brown’s new program will teach these techniques, which are implemented in widely used finite element software systems such as ABAQUS. The curriculum will also include cutting-edge machine learning and artificial intelligence methods, which are increasing used alongside simulation techniques.

“Brown has nationally recognized and highly ranked programs in engineering and applied mathematics, and this new program was created as a partnership between these two disciplines,” Bazilevs said. “Many of our faculty, both in engineering and in applied mathematics, are working on developing state-of-the-art numerical methods and machine learning approaches, with applications that are of particular relevance to the new program.”

Bazilev’s own work uses such techniques to address complex problems in environmental engineering, such as assessing damage to wind turbines in harsh offshore environments, or in biomedical engineering applications, such as assessing blood flow through vessels or the heart. Other program faculty have used the techniques to model disease processes, to predict fluid flow speed just by examining images of the system, to calculate melting points for hypothetical materials and in many other applications.

These experts and others will teach classes in fluid and solid mechanics, material science, chemical and biomedical engineering as well as relevant courses in mathematics, and computation and data science.

Students with recent bachelor of science degrees in engineering, applied mathematics, computer science and related disciplines pursuing careers that involve advanced modeling and simulation in engineering and physical sciences are encouraged to apply. Additional information is available at computational.engineering.brown.edu. The first cohort is expected to begin the program in fall 2022.