Ben Sherman, PhD has a diverse work experience in various roles and industries. Starting in 2014, they worked as a Software Intern at Intel Corporation. In 2015, they joined Conceptual Estimates as a Full Stack Developer, where they developed a Node.js web application for cost analysis in the architecture and engineering field. In 2016, they worked as a Computer Engineer at WSBF-FM Clemson. From 2017 to 2021, they served as a Graduate Research Assistant at Clemson University, where they wrote GPU kernels, built Nextflow pipelines, and developed Nextflow-API for managing and executing pipelines on Kubernetes clusters. In 2020, they worked as a Student Assistant at Berkeley Lab, where they developed a software pipeline and implemented a machine learning approach to analyze job performance on the Cori supercomputer. Currently, Ben is a Software Engineer at Seqera Labs since January 2022.
Ben Sherman, PhD, obtained their Doctor of Philosophy (PhD) in Computer Engineering from Clemson University from 2017 to 2021. Prior to that, from 2013 to 2017, they completed their Bachelor of Science degree in Computer Engineering at the same institution.
In addition to their academic achievements, Dr. Sherman has obtained several certifications. In 2019, they became an AWS Academy Graduate, specializing in AWS Academy Cloud Architecting, certified by Amazon Web Services (AWS). Ben also pursued various certifications from the NVIDIA Deep Learning Institute, including "Scaling CUDA C++ Applications to Multiple Nodes" in September 2021, "Applications of AI for Anomaly Detection" in April 2021, "Fundamentals of Accelerated Computing with CUDA C/C++" in February 2020, "Fundamentals of Accelerated Computing with CUDA Python" in February 2020, and "Fundamentals of Accelerated Data Science with RAPIDS" in February 2020.
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