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faculty
Vijay Varma, PhD he/him
Assistant Professor
Mathematics
Contact
508-910-4037
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Spruce Hall 0174
Education
| 2019 | Caltech | PhD |
Teaching
Programs
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.
Research investigations of a fundamental and/or applied nature defining a topic area and preliminary results for the dissertation proposal undertaken before the student has qualified for EAS 701. With approval of the student's graduate committee, up to 15 credits of EAS 601 may be applied to the 30 credit requirement for dissertation research.
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.
An introduction to ordinary differential equations and their analysis. Topics cover first order linear and nonlinear ordinary differential equations, second order and higher order homogeneous and nonhomogeneous linear differential equations, the linear system of ordinary differential equations, qualitative analysis, numerical solutions, series solutions.
A calculus-based introduction to scientific computation, modeling, simulation and visualization using a variety of mathematics programming tools, scripting languages, and other software tools widely used by mathematicians. This course is project-driven and requires a strong background in mathematics. It is intended for students planning to take upper-level courses in applied or computational mathematics.
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 interests
- Gravitational waves
I am an Assistant Professor in the Department of Mathematics at the University of Massachusetts, Dartmouth. Before UMassD, I was a Marie Curie Fellow at the Albert Einstein Institute, Potsdam; a Klarman Fellow at Cornell; a graduate student at Caltech; and an undergrad at BITS, Pilani.