Michael Mahoney
Professor Adjunct at University of California, Berkeley
San Francisco Bay Area United States
Summary
👤
Senior🎓
Top SchoolMichael Mahoney is an applied algorithms and data science researcher with over two decades of academic and lab experience, currently serving as an adjunct professor at UC Berkeley and Senior Scientist leading Machine Learning and Analytics at Lawrence Berkeley National Laboratory. He specializes in algorithmic and statistical approaches to large-scale data analysis, with recent work on geometric approximation methods for understanding structure, community detection, and information dynamics in massive informatics graphs. His career spans top research institutions and industry labs—including ICSI, Stanford, Yahoo Research, and Amazon Scholar—bridging foundational theory with practical analysis of social and information networks. Trained as a physicist (Ph.D., Yale), he brings a quantitative, systems-oriented perspective that often uncovers geometric and dynamical structure not obvious from standard graph statistics.
10 years of coding experience
22 years of employment as a software developer
Ph.D. Physics, Ph.D. Physics at Yale University
Github Skills (5)
graph1
machine-learning1
science1
stat1
data-science1
Github contributions (5)
mahoneymw/sc-2015
Jul 2015 - Jul 2015
Contributions:9 pushes in 5 days
randomizedlinear-algebrarandomized-linear-algebralinearalgebra
data-8/stat89a
Jan 2016 - Jan 2016
Contributions:1 PR, 7 pushes in 8 days
matricessciencedata-sciencemachine-learningstat
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