Michael Savastio
Data Scientist
Village of Port Jefferson, New York, United States
Summary
👤
Senior🎓
Top SchoolMichael Savastio is a data scientist with a PhD in theoretical high energy physics and 11 years of experience translating complex research-grade mathematics into production-grade optimization and machine learning systems. At FreeWheel he designs and maintains large-scale mixed-integer and conic optimization pipelines, drawing on deep implementation experience in Julia, Fortran and C++ to deliver highly optimized solutions that map directly to client business constraints. His academic work at Cornell and Brookhaven combined statistical inference, metaheuristic search and large-scale data analysis with custom C++/ROOT tooling for particle physics, and he continues to bridge research and engineering as an active open-source contributor. Notably, he has contributed to the widely used JuliaData/DataFrames.jl project, improving core DataFrame behaviors and compatibility—evidence of his focus on robust low-level data infrastructure. Based in Port Jefferson, NY, he pursues diverse technical hobbies from neural networks to relativistic hydrodynamics, blending curiosity-driven research with pragmatic production delivery.
11 years of coding experience
7 years of employment as a software developer
Doctor of Philosophy (Ph.D.), High Energy Physics, 3.9/4.3, Doctor of Philosophy (Ph.D.), High Energy Physics, 3.9/4.3 at Cornell UniversityBachelor's Degree, Physics, 3.9/4.0, Bachelor's Degree, Physics, 3.9/4.0 at Stony Brook University
English
Github Skills (11)
datatables10
dataframes10
debug10
datatable10
tabular10
dataframe10
julia10
testing9
data-set8
data-model8
user-data8
Programming languages (20)
Github contributions (5)
JuliaData/DataFrames.jl
Oct 2017 - Aug 2018
In-memory tabular data in Julia
Role in this project:
Back-end Developer / Data Engineer
Back-end Developer / Data EngineerContributions:8 commits, 15 PRs, 117 comments in 10 months
Contributions summary:Michael primarily contributed to the `dataframes.jl` repository, focused on fixing bugs and improving the DataFrame functionality. Their work includes addressing stack overflow issues related to type promotion, updating code for Julia 0.7 compatibility, and replacing deprecated STDIO calls. They also made changes to core DataFrame structures, including fixing type assertions and ensuring correct `nrow` and `ncol` return types, indicating a strong focus on the internal workings of the data structure.
memorydataframesdatatabular-datadata-frame
ExpandingMan/WeakRefStrings.jl
Nov 2017 - Mar 2022
a minimal String type for Julia that allows for efficient string representation and transfer
Contributions:1 push, 2 branches in 4 years 4 months
representationstringjulia
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