معرفی
Suzanne Shontz is a Professor at the Department of Electrical Engineering and Computer Science and Department of Mechanical Engineering at the University of Kansas. She serves as Associate Dean for Research in the School of Engineering and directs the Mathematical Methods in Interdisciplinary Computing Research Center. Her educational background includes a Ph.D. in Applied Mathematics from Cornell University (2005), M.S. degrees in Computer Science and Applied Mathematics from Cornell (2002), and dual B.A. and B.S. degrees in Mathematics and Chemistry from the University of Northern Iowa (1999).
- Ph.D.: Applied Mathematics, Cornell University (2005)
- M.S.: Computer Science (2002), Applied Mathematics (2002)
- B.A./B.S.: Mathematics/Chemistry, University of Northern Iowa (1999)
Research Interests focus on parallel scientific computing and mesh generation, particularly for computational medicine, imaging sciences, and materials science. Her work addresses unstructured meshing algorithms, numerical optimization, and model order reduction in domains ranging from medical devices to solid mechanics. Key projects include NSF CDS&E (2018-2021), NSF CISE (2017-2021), and NSF CAREER (2011-2017) grants.
Scientific Awards include the prestigious NSF PECASE (2011), International Meshing Roundtable Fellow (2021), Miller Professional Award (2021), and Big 12 Faculty Fellowship (2015). She has mentored over 30 students across multiple departments and institutions, including Ph.D. candidates in Computer Science, Bioengineering, and Mechanical Engineering.
- NSF PECASE Awardee (2011)
- International Meshing Roundtable Fellow (2021)
- Miller Scholar Award (2016)
- Big 12 Faculty Fellowship (2015)
Collaborators span institutions like University of Waterloo, University of Minnesota, Lawrence Livermore National Laboratory, and Iowa State University. Her teaching portfolio includes graduate courses in Scientific Computing, Parallel Computing, and Numerical PDEs, alongside outreach initiatives such as high school summer camps on computer-aided engineering.
