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Ryan McClarren

Ryan McClarren


Phone: 574-631-5430

Office: 368 Fitzpatrick Hall


Ph.D., University of Michigan, 2007

M.S.E., University of Michigan, 2004

B.S.E., University of Michigan, 2003


Ryan McClarren joined Notre Dame's Department of Aerospace Engineering after spending 8 years in the Department of Nuclear Engineering at Texas A&M University.  Prior to that he was a postdoctoral researcher, and later staff member, in the Computational Physics and Methods Group at Los Alamos National Laboratory, where he is still active as a guest scientist. In 2017 he was awarded the Texas A&M Engineering Experiment Station Young Faculty Fellow award for excellence in research.  Dr. McClarren is a member in the American Nuclear Society (ANS) and the Society of Industrial and Applied Mathematics (SIAM).

His research interests include the application of machine learning and compressed sensing to numerical simulation, numerical methods for x-ray radiative transfer and particle transport, and uncertainty quantification.  He is the author of the book Computational Nuclear Engineering and Radiological Science using Python published Fall 2017 by Academic Press, as well as the children's book Radiation and You that teaches elementary-aged students about the applications of radiation in the world around them from smoke detectors to medical devices.


McClarren Publishes Textbook on Computational Nuclear Engineering 
and Radiological Science

April 28, 2018

Ryan McClarren’s new book, Computational Nuclear Engineering and Radiological Science Using Python, offers a sharp contrast to traditional texts that focus on theory and those that promote the use of legacy programming languages for nuclear engineering and radiological science applications. An associate professor of aerospace and mechanical engineering at the University of Notre Dame, McClarren uses Python, a modern and easy-to-learn programming language, to teach numerical methods for engineering. He also provides the reader with a toolbox of numerical techniques to handle the breadth of problems engineers often face.