People

Who writes and reviews the entries.

The dictionary is written and edited in the Aalto Machine Learning Research Group at Aalto University, Finland. Biographies and portraits are those of the group's pages.

Alexander Jung

Author and editor

In the dictionary. Writes the entries: the definitions, the figures, the Python demos, and the revisions that follow each review pass.

Tenured Associate Professor in Machine Learning at the Department of Computer Science, Aalto University, and head of the Aalto Machine Learning Research Group. He obtained his Ph.D. (with sub auspiciis) in electrical engineering from the Technical University of Vienna in 2012, held postdoctoral positions at ETH Zurich and TU Vienna, and joined Aalto University in 2015. His research focuses on trustworthy federated learning, explainable AI, and scalable machine learning systems. He is the author of the textbooks Machine Learning: The Basics (Springer, 2022) and Federated Learning: From Theory to Practice (Springer, 2026).

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Konstantina Olioumtsevits

Editor

In the dictionary. Reviews the entries, sentence by sentence, across the whole dictionary. Many of the revisions recorded in the project history answer comments from this review.

Postdoctoral researcher in the Aalto Machine Learning Research Group, with a background in linguistics. She completed her Ph.D. at the Aristotle University of Thessaloniki, Greece, specializing in second language learning and teaching in populations with a migrant and refugee background. At Aalto she develops and translates the dictionary as a specialized reference, learning, and teaching resource, with the aim of making machine learning accessible and understandable.

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Ekkehard Schnoor

Editor

In the dictionary. Reviews selected entries, contributing review passes alongside the continuous review.

Postdoctoral researcher in the Aalto Machine Learning Research Group. He obtained his Ph.D. in mathematics from RWTH Aachen University under the supervision of Holger Rauhut, with a dissertation in statistical learning theory at the intersection of compressive sensing and deep learning, and was a member of the Explainable AI group at Fraunhofer HHI before joining Aalto. His research combines generalization and explainability in machine learning, from Rademacher complexity and random matrix theory to concept activation vectors and sparse autoencoders for large language models, using tools from high-dimensional probability.

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How a review comment becomes a revision — and which automated checks run over every entry — is described in how this book is built.

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