Ingo Scholtes
Professor at Julius-Maximilians-Universität Würzburg
Würzburg, Bavaria, Germany
Summary
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Senior🎓
Top SchoolIngo Scholtes is a Full Professor and chairing researcher in Machine Learning for Complex Networks at Julius-Maximilians-Universität Würzburg, combining 14 years of experience in machine learning, network science, and graph mining. His work bridges theory and empirical analysis, with foundational contributions on higher-order graph analytics for time series featured in Nature Physics. He has secured major competitive funding (including a CHF 1.5M SNSF professorship) and holds leadership roles in CAIDAS, ELLIS, and the German Informatics Society’s Computational Social Science section. Trained at ETH Zürich and summa cum laude PhD from Universität Trier, he blends rigorous mathematical grounding with practical graph-learning methods. Beyond academia, he follows empirical software engineering and maintains active engagement with the research community through editorial and organizational service.
14 years of coding experience
Dr.rer.nat., Informatik, summa cum laude, Dr.rer.nat., Informatik, summa cum laude at Universität TrierPostdoc, Postdoc at ETH Zürich
Github Skills (29)
network-analysis10
temporal10
data-mining10
graph10
graphical-models10
ranking10
science10
pypi10
computer-science10
react10
pytorch9
python9
machine-learning9
time-series9
modeling9
Programming languages (3)
Github contributions (5)
IngoScholtes/NETGen
Aug 2011 - Mar 2012
Contributions:58 commits in 7 months
IngoScholtes/pathpy
Feb 2017 - May 2020
pathpy is an OpenSource python package for the modeling and analysis of pathways and temporal networks using higher-order and multi-order graphical models
Contributions:7 releases, 86 commits, 6 PRs in 3 years 3 months
pythondatadata-mininggraph-analysistemporal-networks
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