Dylan Everingham
Research Associate Doctoral Candidate
Berlin, Germany
Summary
👤
Senior🎓
Top SchoolDylan Everingham is a computational scientist and doctoral researcher at TU Berlin with a decade of experience applying machine learning, mathematical modeling, and high-performance computing to real-world instrumentation and sustainability problems. He built flight-control and modeling software at NASA JPL for missions including Mars2020 and ECOSTRESS, then earned dual MSc degrees cum laude while developing topology-optimization and physics-informed neural network methods for metamaterial optics. At the Zuse Institute he explored network-attached FPGA accelerators to improve energy efficiency of scientific codes, and his current work models performance of cutting-edge ML architectures on distributed hardware. Comfortable moving between firmware, HPC system design, and applied math, he combines hands-on engineering with rigorous research—and outside the lab he’s also an active musician and lifelong tinkerer.
10 years of coding experience
8 years of employment as a software developer
University of California, San DiegoStudy Abroad as Part of BSc, Computer Science, Study Abroad as Part of BSc, Computer Science at Utrecht UniversityMaster of Science - MS, Scientific Computing, Master of Science - MS, Scientific Computing at Technische Universität BerlinTU Delft
Github Skills (6)
simulation3
arweave1
creative-commons1
ethereum1
blockchain1
tagging1
Programming languages (2)
Github contributions (5)
deveringham/metalens_optimization
Jun 2022 - Jul 2022
Contributions:10 commits, 11 pushes, 1 branch in 1 month
deveringham/PhysicsSims
Jul 2018 - Jul 2019
Contributions:5 pushes, 1 branch in 1 year
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