Jarrett Revels
Chief Technology Officer at Beacon Biosignals
Boston, Massachusetts, United States
Summary
🤩
Rockstar🎓
Top SchoolJarrett Revels is a CTO and cofounder with 12 years of experience building high-performance scientific software and leading engineering teams at the intersection of biosignals and research computing. Based in Boston, he combines hands-on systems and compiler work—contributing performance-critical patches to the Julia language and foundational packages like ForwardDiff, JuMP, and BenchmarkTools—with strategic product leadership at Beacon Biosignals. His background at MIT includes developing JIT code-transformation tooling and large-scale benchmarking infrastructure that have shaped Julia’s performance ecosystem. He is fluent in optimization, automatic differentiation, and memory/performance tuning, and he brings a habit of turning deep compiler and numerical insights into practical, production-ready systems. Notably, his contributions to core Julia compiler and GC behavior reflect a rare blend of low-level engineering and applied scientific productization.
12 years of coding experience
6 years of employment as a software developer
B.Sc. in Physics and Computer Science (Double Major), B.Sc. in Physics and Computer Science (Double Major) at American University
Github Skills (31)
algorithm10
code-optimization10
algorithms10
benchmark10
type-inference10
benchmarking10
mathematical10
type-system10
calculus10
automatic-differentiation10
performance-optimization10
optimisation10
compiler-optimization10
numerical-optimization10
linear-programming10
Programming languages (7)
Github contributions (5)
JuliaCI/BenchmarkTools.jl
Feb 2016 - Mar 2019
A benchmarking framework for the Julia language
Role in this project:
Back-end Developer & Performance Engineer
Back-end Developer & Performance EngineerContributions:4 releases, 1 review, 150 commits in 3 years 1 month
Contributions summary:Jarrett primarily contributed to the development and improvement of the `BenchmarkTools.jl` package, which is a benchmarking framework for the Julia language. They focused on refactoring the code, including moving execute functions and updating the data structures. Furthermore, they added features such as support for parameter pre-tuning and better outlier trimming, which significantly enhanced the capabilities of the package. This involved performance optimization and streamlining the benchmarking workflow.
benchmarkingjulia-languagebenchmarkbenchmarksjulia
JuliaDiff/ForwardDiff.jl
Jul 2015 - Feb 2019
Forward Mode Automatic Differentiation for Julia
Role in this project:Back-end Developer
Back-end DeveloperContributions:27 releases, 421 commits, 238 PRs in 3 years 7 months
Contributions summary:Jarrett refactored the code base to use a new data structure, ``Dual``, replacing the existing ``GradientNumber`` and related types. They defined a new tagging mechanism and performed optimizations that were enabled by these changes. The user also added code to automatically define the math operations on the new structure using existing derivative definitions, which resulted in a new API.
calculusautomatic-differentiationdifferentiationforward-modejulia
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