Simone Surace
Co-Founder And Partner at Flock Labs AG
Switzerland
Summary
🤩
Rockstar🎓
Top SchoolSimone Surace is a Swiss co-founder and partner with seven years of experience bridging advanced academic research and applied machine learning. With a PhD and postdoctoral work in time series, Gaussian processes, and nonlinear stochastic filtering, he brings deep expertise in probabilistic modeling and particle filters to product-focused ML roles. At Artificialy and in academia he translated theory into practice, and his contributions to the well-regarded JuliaStats/Distributions.jl—implementing analytical KL divergences with attention to numerical stability—highlight his commitment to robust, reproducible tooling. Now leading Flock Labs AG, he combines research rigor with startup execution, unusually fluent at both deriving inference formulas and shipping production-ready code.
7 years of coding experience
12 years of employment as a software developer
Bachelor of Science, Bachelor of Science at University of BernDoctor of Philosophy - PhD, Doctor of Philosophy - PhD at Universität BernSummer School, Summer School at Princeton University
Github Skills (6)
statistics10
probability-distribution10
distributions10
data-science10
julia10
testing10
Programming languages (7)
Github contributions (5)
JuliaStats/Distributions.jl
Apr 2022 - Aug 2022
A Julia package for probability distributions and associated functions.
Role in this project:
Data Scientist
Data ScientistContributions:21 reviews, 6 commits, 8 PRs in 3 months
Contributions summary:Simone primarily contributed to adding analytical formulas for calculating the Kullback-Leibler (KL) divergence between various probability distributions. These contributions involved implementing and testing KL divergence calculations for Laplace, Chi, Chisq, LogNormal, LogitNormal, NormalCanon, Binomial, NegativeBinomial, and Geometric distributions. The user's work frequently included improvements in code efficiency and numerical stability. Additionally, they added and updated test cases to validate the accuracy of the implemented formulas.
julia-packagedistributionsstatisticsdata-scienceprobability-distributions
Theoretical-Neuroscience-Group/SynapticFilter.jl
Jun 2021 - Jul 2021
A high-performance Julia package for the synaptic filter
Contributions:108 commits, 15 PRs, 72 pushes in 10 days
julia-packagejulia-languageperformancejuliasynaptic
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