faculty
Scott Field, PhD
Associate Professor
Mathematics
Research Website
Contact
508-999-8281
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Liberal Arts 394E
Education
2011 | Brown University | PhD |
2006 | University of Rochester | BS |
Teaching
Programs
Programs
- Data Science BS, BS/MS
- Data Science Graduate Certificate
- Data Science MS
- Engineering and Applied Science PhD
- Mathematics BA, BS
Teaching
Courses
Topics in high performance computing (HPC). Topics will be selected from the following: parallel processing, computer arithmetic, processes and operating systems, memory hierarchies, compilers, run time environment, memory allocation, preprocessors, multi-cores, clusters, and message passing. Introduction to the design, analysis, and implementation, of high-performance computational science and engineering applications.
Research
Research awards
- $ 189,022 awarded by NATIONAL SCIENCE FOUNDATION for Collaborative Research: CDS&E: Data-Driven Discovery of Neural ODE Dynamics, Astrophysical Models, and Orbits (Neural ODE DynAMO)
- $ 349,101 awarded by National Science Foundation for Developing High Order Stable and Efficient Methods for Long Time Simulations of Gravitational Waveforms
- $ 13,000 awarded by Mathematical Association of America for Mixed Model Implicit and IMEX Runge-Kutta Methods
- $ 438,284 awarded by Office of Naval Research for UMassD MUST IV: Learning Nonlinear Dynamical Systems from Sparse and Noisy Data: Applications to Signal Detection and Recovery
- $ 650,000 awarded by National Science Foundation for Implementation of a Contextualized Computing Pedagogy in STEM Core Courses and Its Impact on Undergraduate Student Academic Success, Retention, and Graduation
Research
Research interests
- Gravitational wave data science
- Discontinuous Galerkin methods
- Large-scale Scientific Computation
- Computational general relativity and fluid dynamics
- Numerical analysis
Latest from Scott
Mentioned in
- Feb 6, 2024 NASA, ESA move forward on science supported by UMass Dartmouth faculty
- Oct 20, 2023 UMassD PhD students and faculty gain new insights on binary black holes
- Jan 31, 2022 UMass Dartmouth professor and students discover fast-moving black hole
- Oct 29, 2020 Mathematics Professor builds model to help detect black hole mergers