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• Postdoctoral Appointee at Sandia National Laboratories. I completed my Ph.D. in Statistics at Iowa State University.
• My research involves designing advanced Bayesian models for complex scientific challenges. This includes creating surrogates (emulators) for large-scale computer experiments like climate models (E3SM) and fusion energy simulators, and developing expressive hidden Markov models to detect cyber threats.
• R is for data munging, data visualization, and more stats-y modeling, Python for ML/DL modeling and deployment, C++ for performance, LaTeX for typesetting, GNU Make for pipelining, Unix Shell for system automation, Org-mode for note taking and planning, GNU Emacs for the ultimate text editing experience, Arch Linux for gluing it all together.
• Tackling a new problem? keep it simple and straightforward, light weight is the right weight, premature optimization is the root of all evil, don't repeat yourself (too often).
• Huge fan of note taking and list keeping, see it by yourself.
• I’ll trade off measure theory for linear algebra.