I. B.

Computational Scientist

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Experience: 10 Years
Location: Washington, DC

Overview

My specialty is implementing algorithms for tightly coupled, massive high performance computing (HPC) numerical simulations and calculations. Efficient use of computing resources is critical, as is performance optimization and engineering. The main languages I use are Modern Fortran and Python with MPI, OpenMP, and Coarray Fortran.

I have developed algorithms for numerically robust, one pass, constant memory footprint, parallel computation of a variety of descriptive statistics as part of my Doctoral dissertation research, that also allow the user to monitor convergence and errors.

Through my dissertation, I have worked with massive aerodynamics and turbulence data sets, about 10 TB each, and have gained an appreciation for efficient algorithms, and ways to amortize costs associated with memory hierarchies and disk IO.

I enjoy mentally stimulating projects and contributing to open source software such as:

- OpenCoarrays, the GFortran official coarray fortran runtime middleware
- JSON-Fortran, a JSON parser and manipulation library for Modern Fortran, and I implemented the ISO 10646/UCS4 support
- bash3boilerplate

@zbeekman on [you must be logged in to see this link]

Experience

OpenCoarrays quality assurance (QA) and continuous integration (CI) implementation using [you must be logged in to see this link], Travis-CI and codecov.io. Project management, coordinating developers, reviewing code, publishing releasesTau Commander from ParaTools Inc. "Performance engineering for the rest of us"
Use Tau Commander, a user friendly front end to the TAU Performance System (TM) to profile codes like NASA's FUN3D and work on porting to KNL and GPU. Also contribute to the development of Tau Commander
Faculty Research Assistant, Aerospace Eng., University of MD, College Park
Conduct massive HPC aerodynamics simulations using thousands of MPI ranks.
Extend numerical simulation code for new capabilities.
Fixed numerous bugs.
Algorithm development for processing large data sets
Princeton University Graduate Research Assistant
Conduct massive HPC aerodynamics simulations using thousands of MPI ranks.
Extend numerical simulation code for new capabilities.
Fixed numerous bugs.
Algorithm development for processing large data sets
JSON-Fortran: QA and CI implementation, and Extension for ISO 10646 supportbash3boilerplate: Numerous contributions to command line/usage parsing, bug fixes etc.

Agencies I've Worked For

Princeton University
University of Maryland
Sourcery Institute
ParaTools Inc.

Education / Qualifications

Doctoral Candidate, ET/DCC, Mechanical and Aerospace Engineering, Princeton University, Anticipated graduation: Spring 2017M.A. Mechanical and Aerospace Engineering, Princeton University, June 2010Visiting Graduate Student, Aerospace Engineering, University of Maryland, College Park, June 2009 - Sept. 2014B.S. Mechanical and Aerospace Engineering, The George Washington University, May 2007

Skills

Automated TestingBashCluster ComputingContinuous IntegrationData ScienceDistributed computing
FortranLaTeXMake Build ScriptObject oriented designPerformance testingPython
Regression testingRegular ExpressionsScientific WritingTest Driven DevelopmentUnit TestingWeb design

Awards

Barry M Goldwater ScholarAlfred Fruedenthal Award for highest academic achievement in graduating SEAS class, The George Washington University

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