Mario Beraha
Tenure Track Assistant Professor (RTT) at Università degli Studi di Milano-Bicocca
Milan, Lombardy, Italy
Summary
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Senior🎓
Top SchoolMario Beraha is a tenure-track assistant professor and researcher based in Milan with a decade of experience at the intersection of machine learning and Bayesian nonparametrics. He has transitioned from industry roles building AI‑driven chatbots and scalable microservices to academic positions at Politecnico di Milano, Università di Torino, and now Università degli Studi di Milano‑Bicocca, blending practical engineering with theoretical research. His PhD work and subsequent scholarship focus on probabilistic models that bring principled uncertainty quantification to modern ML problems. Comfortable with both deep learning methods (LSTMs, CNNs, GANs) and probabilistic theory, he bridges data science tooling and rigorous statistical modeling. Outside academia he has hands-on experience shipping distributed systems, NoSQL backends, and asynchronous services—an uncommon combination that tightens the loop between research ideas and deployable AI.
10 years of coding experience
6 years of employment as a software developer
Maturità Scientifica PNI, Liceo Scientifico PNI, 93/100, Maturità Scientifica PNI, Liceo Scientifico PNI, 93/100 at Liceo Scientifico Leonardo da VinciMaster Degree, Mathematical Engineering-Applied Statistics, 110 / 110 cum Laude, Master Degree, Mathematical Engineering-Applied Statistics, 110 / 110 cum Laude at Politecnico di MilanoSummer program in Public Speaking, Summer Program in Finance, Best of the class (Public Speaking), Summer program in Public Speaking, Summer Program in Finance, Best of the class (Public Speaking) at Amherst CollegeWinter School, Uncertainty Quantification, Winter School, Uncertainty Quantification at USI Università della Svizzera italiana
Italian, English, French
Stackoverflow
499reputation
69kreached
2answers
37questions
Github Skills (109)
mixture10
markdown10
protocol-buffers10
protobuf10
serialization10
rpc10
bayesian10
gitpod10
jekyll10
marshalling9
variance9
websocket-client9
slack-bot9
python9
data-interchange9
Programming languages (8)
Github contributions (5)
bayesmix-dev/pybmix
Dec 2020 - Nov 2022
Contributions:38 reviews, 13 PRs, 110 pushes in 1 year 11 months
bayesmix-dev/math
Nov 2021 - Apr 2023
The Stan Math Library is a C++ template library for automatic differentiation of any order using forward, reverse, and mixed modes. It includes a range of built-in functions for probabilistic modeling, linear algebra, and equation solving.
Contributions:1 review, 1 PR, 3 pushes in 1 year 5 months
automatic-differentiationprobabilistic-modelingmodestemplate-libraryroot-finding
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