Jackson Sheppard is a doctoral student in chemistry with a physics background and eight years of hands-on experience building controls and data-driven systems, most recently integrating motion hardware and device support for experiments at SLAC’s LCLS where he earned a Spot Award for dependability. He combines applied control engineering (EPICS, PLCs, Beckhoff) with data analytics and machine learning skills—Python, SQL, TensorFlow/Keras, PySpark—and a certificate in data analytics to bridge experimental apparatus and analysis pipelines. At UCSB he balances graduate research, teaching, and tutoring while contributing to computational studies of molecular dynamics and FEL beam simulations published with SLAC collaborators. Known for clear technical communication and dependable execution, he excels at integrating heterogeneous devices and producing reproducible data workflows on Linux and cloud-backed systems. An avid learner and problem solver, he brings both lab-scale instrumentation experience and production-oriented software practices to multidisciplinary teams.
8 years of coding experience
3 years of employment as a software developer
Bachelor of Science - BS Physics, Bachelor of Science - BS Physics at UC Santa Barbara
Certificate Data Analytics, Certificate Data Analytics at UC Berkeley Extension
TwinCAT 3 PLC Project for LCLS optics MR1L0 and MR2L0
Contributions:135 pushes, 19 branches, 1 tag in 1 year 3 months
siemensopticstwincatopcuaindustrial-automation
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Jackson Sheppard - Doctoral Student at UC Santa Barbara