John Edmiston

John Edmiston has a long history of professional experience in the software engineering and data science fields. Starting in 2009, they held the role of Lawrence Scholar at Lawrence Livermore National Laboratory, where they developed an uncertainty quantification approach for X-ray diffraction analysis of individual grains in a polycrystal and constructed a model and alternative constitutive framework for single crystal plasticity. In 2012, they became a Project Engineer at Symplectic Engineering Corporation, where they researched and developed numerical meshfree methods for large deformation, high velocity impact simulation and developed a novel stabilization scheme for MLSPH method. From 2013 to 2015, they were a Postdoctoral Fellow at Lawrence Berkeley National Laboratory, where they developed modeling and simulation capabilities for coupled flow and deformation in porous materials. In 2018, they joined Hinge Health as a Data Scientist, where they were responsible for aggregation and reporting of usage data for business performance, developing pipelines and munging in Python/R, and analyzing performance of experiments via multilevel hierarchical models. In 2019, they worked as a Senior Data Scientist at Proteus Digital Health, Inc and a Senior Engineer and Senior Data Scientist, Quality at MycoWorks, where they developed an in-house MES for task scheduling and recording tool (Flask application). In 2021, they held the role of Staff Data Scientist at both Iterative Scopes and Store No. 8. Currently, they are a Senior Scientific Software Engineer at Cognitive Space.

John Edmiston received their Bachelor of Science in Mechanical Engineering from the University of Minnesota in 2004. John then went on to obtain their Master of Science in Mechanical Engineering from the University of Wisconsin-Madison in 2006. Finally, they obtained their Doctor of Philosophy in Mechanical Engineering from the University of California, Berkeley in 2012.