Andrew Rosemberg
Graduate Researcher
Atlanta, Georgia, United States
Summary
👤
Senior🎓
Top SchoolAndrew Rosemberg is a Machine Learning PhD candidate and visiting researcher who blends optimization, differentiable programming, and model-based reinforcement learning to tackle time-sensitive control problems in energy and robotics. With nine years of experience across national labs, industry research teams, and academic labs—including AI4OPT, Los Alamos, Invenia, and UC Berkeley—he focuses on fast optimization surrogates with feasibility guarantees for real-world systems. He contributes to open-source tooling in mathematical optimization (notably JuMP.jl), improving core modeling functionality and usability. Comfortable moving between theory and implementation, Andrew applies hardware-aware acceleration and data-driven methods to safety-critical control and renewable energy challenges.
9 years of coding experience
3 years of employment as a software developer
Diplôme d'ingénieur Ingénierie, Diplôme d'ingénieur Ingénierie at Centrale MéditerranéeDoctor of Philosophy - PhD Machine Learning and Optimization, Doctor of Philosophy - PhD Machine Learning and Optimization at Georgia Institute of TechnologyPontifical Catholic University of Rio de Janeiro
French, English, Portuguese, German
Github Skills (7)
linear-programming10
lang10
mathematical10
mathematical-programming10
modeling10
julia10
optimization10
Programming languages (5)
Github contributions (5)
jump-dev/JuMP.jl
Oct 2020 - Oct 2020
Modeling language for Mathematical Optimization (linear, mixed-integer, conic, semidefinite, nonlinear)
Role in this project:
Back-end Developer
Back-end DeveloperContributions:2 reviews, 6 commits, 1 PR in 1 day
Contributions summary:Andrew primarily contributed to the JuMP (Julia Modeling Language) project by enhancing core functionality. They focused on implementing and refining the `haskey` method for the `AbstractModel` type, adding documentation, and fixing style and typos. These changes indicate a focus on improving the usability and correctness of the JuMP library's core features.
mathematical-optimizationoptimizationjuliamodeling-languagelinear-programming
andrewrosemberg/OptimalBids.jl
Feb 2022 - Jan 2023
Package for identifying optimal bids.
Contributions:2 releases, 3 reviews, 87 commits in 11 months
optimalbids
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