A Computational Scientist comes armed with expertise in algorithms, fluency in software, and intuition for physical processes of scientific/engineering systems. There are tremendous opportunities in using these powers for good, in impacting industrial applications in improving engineering design, in national security applications for assuring safety, and scientific applications for accelerating discovery. The greatest gains can come from embedding in a specific application area and developing high-functioning interdisciplinary teams with application experts — a process that can take years of investment to come to fruition.
We will discuss the choices in a computational scientist’s career regarding the focus in specific application domains. * How to recognize good opportunities, with a realistic expectation of the investment required to have real impact? * Where do your enthusiasms and strengths lie: in cutting edge discovery of new algorithms, or deploying established algorithms to novel application areas, or some blend? * Are there application talks that you see at SIAM CSE that really excite you, that you think could benefit from the expertise you have, or that you want to learn more about and develop application domain expertise? * Are there presentations at SIAM CSE that are illustrative anecdotes on the amount of investment it takes to embed in an application domain sufficiently to impact it with improved computational science approaches?
What are the relevant conference themes?
Applications in science, engineering, and industry
Andy Salinger is the Manager of the Computational Science department at Sandia National Labs. He was trained as a computational scientist while earning a PhD in Chemical Engineering, with enough luck to have access to a Cray YMP (many MegaFLOPS!). His career has involved the development and integration of scalable algorithms into application areas such as chemical reactor design, incompressible flows, fluids-density functional theory, and ice sheet dynamics. Recently, Andy’s focus has been in the area of Climate Modeling, where he leads development efforts in Software and Algorithms for DOE’s Energy Exascale Earth System Model.
I enjoy mentoring, nurturing careers, and building up people’s confidence to follow their enthusiasm. I very much look forward to engaging with the BE participants, who are earlier in the pipeline than I usually get to work with, to learn about their interests, passions, struggles, and perspective. I see the struggle firsthand in attempting to achieve demographic diversity in my department, and would like to be a positive influence in encouraging careers in computational science.