faculty

Scott Field, PhD

Associate Professor

Mathematics

Curriculum Vitae
Research Website

Contact

508-999-8281

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Liberal Arts 394E

Education

2011Brown UniversityPhD
2006University of RochesterBS

Teaching

Programs

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.

Written presentation of an original research topic in Data Science which demonstrates the knowledge & capability to conduct independent research. The thesis shall be completed under the supervision of a faculty advisor. An oral examination in defense is required.

Investigations of a fundamental and/or applied nature representing an original contribution to the scholarly research literature of the field. PhD dissertations are often published in refereed journals or presented at major conferences. A written dissertation must be completed in accordance with the rules of the Graduate School and the College of Engineering. Admission to the course is based on successful completion of the PhD comprehensive examination and submission of a formal proposal endorsed by the student's graduate committee and submitted to the EAS Graduate Program Director.

Investigations of a fundamental and/or applied nature representing an original contribution to the scholarly research literature of the field. PhD dissertations are often published in refereed journals or presented at major conferences. A written dissertation must be completed in accordance with the rules of the Graduate School and the College of Engineering. Admission to the course is based on successful completion of the PhD comprehensive examination and submission of a formal proposal endorsed by the student's graduate committee and submitted to the EAS Graduate Program Director.

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