Amir Sani

AI & Automation

London, England, United Kingdom
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Summary

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Senior
🎓
Top School
Amir Sani is an experienced AI and automation strategist with 11 years blending academic rigor and product-focused deployment across private markets, finance, and complex systems. He holds a PhD in Machine Learning and has translated advanced agent-based modeling, surrogate ML, and calibration techniques from research at institutions like Oxford, Imperial and Scuola Superiore Sant'Anna into production analytics and fund intelligence at Techstars, 13books Capital and EY. Today he advises VCs, family offices and private companies while leading AI & Automation at I2ntelligence and R&D at AdapData, specializing in scalable data pipelines, surrogate-based sampling, and human-in-the-loop model design. Notably, his background spans both high-frequency market microstructure optimization and large-scale scraping/ETL architectures, enabling pragmatic bridges between cutting-edge research and commercial value creation.
code11 years of coding experience
job4 years of employment as a software developer
bookAustralian National University
bookUniversity College London
bookCertificate Law, Certificate Law at University of San Diego School of Law
bookClarkson School Coursework, Clarkson School Coursework at Clarkson University
bookUniversity of California, San Diego
bookDoctor of Philosophy (Ph.D.) Machine Learning, Doctor of Philosophy (Ph.D.) Machine Learning at INRIA & University of Lille 1
languagesFrench, Spanish, Italian, Persian, English
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Stackoverflow

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Github Skills (149)

quantitative10
flask10
react10
data-engineering9
data-analytics9
data-viz9
superset9
transfer-learning9
data-visualization9
trading9
topological-data-analysis9
python9
pitch9
audio-effect9
noise9

Programming languages (7)

TypeScriptJavaC++CHTMLJupyter NotebookPython

Github contributions (5)

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amirsani/fintech_news

Jul 2020 - Jul 2020

Contributions:3 PRs, 255 pushes, 3 branches in 26 days
amirsani/pySharpeRratio

Feb 2017 - Dec 2019

A moment-free estimator of the Sharpe (signal-to-noise) ratio.
Contributions:2 releases, 35 commits, 1 PR in 2 years 10 months
signalaudio-processingsignal-to-noisetradingratio
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