Antonio Vergari
Reader (Associate Professor) In Machine Learning At The University Of Edinburgh
City of Edinburgh, Scotland, United Kingdom
Summary
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Senior🎓
Top SchoolAntonio Vergari is a Reader (Associate Professor) in Machine Learning at the University of Edinburgh with 15 years of experience building reliable probabilistic ML systems that blend rich symbolic reasoning with efficient deep learning inference. As PI of the APRIL lab he focuses on tractable probabilistic models and provable reliability in real-world settings, pushing NeSy (neuro-symbolic) approaches toward practical deployment. His background spans top research institutions (UCLA, Max Planck) and applied roles from clinical data management to generative design, reflecting a rare mix of theoretical depth and practical engineering. A top-graduated computer scientist from Università di Bari, he brings an interdisciplinary perspective and a taste for simplicity—selfie non multiplicanda praeter necessitatem—when designing scalable, interpretable ML.
15 years of coding experience
7 years of employment as a software developer
Master's degree, Computer Science, 110/110 cum laude and special commendation by the commission, Master's degree, Computer Science, 110/110 cum laude and special commendation by the commission at Università degli Studi di Bari
Github Skills (96)
probabilistic-programming10
mixture-model10
autoencoder10
sum10
spn10
distributions10
information-theory10
bayesian10
probabilistic-models10
sum-product10
probabilistic-graphical-models10
graphical-models9
ai9
python9
encoding9
Programming languages (8)
Github contributions (5)
arranger1044/MADE
Nov 2015 - Apr 2019
Contributions:59 pushes in 3 years 6 months
autoencodermachine-learningestimationmaskeddistribution
arranger1044/DEBD
Nov 2015 - Jul 2019
A collection of commonly used datasets as benchmarks for density estimation in MaLe
Contributions:15 commits, 2 PRs, 12 pushes in 3 years 8 months
density-estimation
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