Jonathan Geuter

AI Research Intern at MBZUAI (Mohamed bin Zayed University of Artificial Intelligence)

United States
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Summary

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Jonathan Geuter is a PhD student in Applied Mathematics at Harvard and an AI research intern at MBZUAI’s Institute of Foundation Models, bringing five years of research and engineering experience across academic and industry settings. His work sits at the intersection of optimal transport, generative modeling, and statistical machine learning, with hands-on experience training foundational language embedding models during an internship at Jina AI. Jonathan has a strong theoretical foundation from TU Berlin and practical research exposure from Zuse Institute Berlin and UC Berkeley, and he’s comfortable moving between proofs, Python-based teaching, and model training pipelines. Colleagues describe him as someone who pairs mathematical rigor with a practical bent for scalable ML systems—often exploring how principled transport methods can improve generative models.
code5 years of coding experience
job2 years of employment as a software developer
bookBachelor of Science - BS, Mathematics, Bachelor of Science - BS, Mathematics at University of California, Berkeley
bookCross-Registered Student, Cross-Registered Student at Massachusetts Institute of Technology
bookDoctor of Philosophy - PhD, Doctor of Philosophy - PhD at Harvard University
bookMaster of Science - MS, Mathematics, Master of Science - MS, Mathematics at Technische Universität Berlin
languagesEnglish, German, French, Italian, Chinese, Spanish
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Github Skills (30)

julia10
optimization10
openai-clip9
pytorch9
amd9
llm9
inference9
llama9
metric-learning9
few-shot-learning9
openai9
siamese-network9
transfer-learning9
gpt9
cuda9

Programming languages (3)

JuliaHTMLPython

Github contributions (5)

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j-geuter/SinkhornNNHybrid

Sep 2022 - Jan 2023

Initializing the Sinkhorn Algorithm using a Neural Network
Contributions:286 commits, 2 PRs, 240 pushes in 4 months
neural-network
j-geuter/FrankWolfe.jl

Jun 2021 - Nov 2022

Julia implementation for various Frank-Wolfe and Conditional Gradient variants
Contributions:2 PRs, 132 pushes, 28 branches in 1 year 4 months
frank-wolfeconditionalfrankjuliagradient
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