Anton Begehr
Founder at KiloAgent
Dubai, Dubai, United Arab Emirates
Summary
👤
Senior🎓
Top SchoolAnton Begehr is a Dubai-based founder and freelance software engineer with nine years of experience building scalable web and mobile applications, data pipelines, and cloud deployments for startups and enterprise clients including Palantir. He moves quickly from prototype to production, having co-founded multiple ventures and independently shipped end-to-end products such as an early room-scanning system at autarc. Comfortable across full-stack web, iOS, and data engineering, Anton blends hands-on development with product instincts to deliver high-impact solutions for global clients. His academic background spans computer science and big data systems from Universität Passau, Freie Universität Berlin, and HSE, underpinning a strong foundation in systems and data. Notably, he pairs enterprise-grade experience from forward-deployed roles with the agility of a founder, able to lead projects solo or scale collaborative teams.
9 years of coding experience
7 years of employment as a software developer
Bachelor of Science - BS Computer Science, Bachelor of Science - BS Computer Science at Freie Universität BerlinMaster's degree Big Data Systems, Master's degree Big Data Systems at Higher School of EconomicsMaster of Science - MS Computer Science, Master of Science - MS Computer Science at Universität Passau
Stackoverflow
517reputation
146kreached
7answers
12questions
Github Skills (200)
twilio-api10
component-library10
google-maps10
mouse-events10
github-desktop10
browser10
voice10
skia10
audio-recorder10
firebase-database10
static-site-generator10
cordova10
css10
material-design10
firebase-storage10
Programming languages (26)
Github contributions (5)
abegehr/ComE_BGMM
Feb 2020 - May 2022
Implementation of the ComE algorithm using a Bayesian Gaussian mixture model and variational inference (BGMM+VI) for community embedding instead of a non-Bayesian Gaussian mixture model and expectation maximization (GMM+EM). The advantage of BGMM+VI over GMM+EM is that the hyper-parameter number of communities K acts as an upper bound and unused communities are discarded using the trade-off hyper-parameter weight concentration prior.
Contributions:21 PRs, 343 pushes, 25 branches in 2 years 3 months
bayesianexpectation-maximizationgaussian-mixture-modelsvariational-inference
abegehr/ML_compare_mixture_algs
Jun 2018 - Jun 2020
Contributions:24 commits, 18 pushes, 1 branch in 2 years
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