CURRICULUM VITAE
MAX PAGELS
I specialise in incremental & online maching learning, linear optimisation, signals analysis and backend architectures. I've worked for small startups, mid-size businesses, and Fortune 500 enterprises.
Education
MSc, Computer Science, University of Helsinki; major in software systems, extended minor in mathematics and statistics. Natively trilingual (Swedish, Finnish, English).
Military service
Finnish Defence Forces reservist.
Past clients
Veikkaus, Elisa, Sanoma Media, Wayfair, Hennes & Mauritz
Talks
Aalto University, Aalto Pro, Node School Helsinki, Junction Helsinki, Alma Talent, Helsinki Reinforcement Learning
Projects
Formative
Quantitative reasoning made simple (but not easy).
Select Papers
Improving the Delivery Cycle: A Multiple-Case Study of the Toolchains in Finnish Software Intensive Enterprises, IST, 2016
The Highways and Country Roads to Continuous Deployment, IEEE Software, 2015
A Behavior Marker tool for measurement of the Non-Technical Skills of Software Professionals: An Empirical Investigation, SEKE, 2015
Examining the Structure of Lean and Agile Values Among Software Developers, XP, 2014
Summary
Primary domain: online (incremental) machine learning systems -- algorithms that update model parameters per-observation in O(1) amortised time rather than requiring full batch retraining. Applied focus on contextual bandits, off-policy evaluation (IPS, DR, doubly-robust estimators), and reward estimation under partial feedback. Experience in causal estimation and author of Formative, a causal estimation library. Authored the Vowpal Wabbit off-policy evaluation tutorial in the official documentation.
Secondary domains: linear and mixed-integer optimisation (LP/MIP formulations for scheduling, routing and resource allocation), time-series and signals analysis (spectral methods, online anomaly detection), and distributed backend architectures for real-time inference (streaming ingestion, feature stores, sub-millisecond serving layers).
Public talks on contextual bandits, bandit algorithms, and cloud-native ML at Aalto University, Junction Helsinki and Helsinki Reinforcement Learning meetup.