Frank Sommer

Frank Sommer is a Humboldt fellow (Feodor Lynen scholarship for Postdocs) at Vienna University of Technology since June 2024. He is affiliated with the Institute of Logic and Computation, where he conducts research in theoretical computer science and algorithms. Previously, he held postdoc positions at Friedrich Schiller University Jena (May 2023-May 2024) and Philipps University Marburg (November 2022-May 2023).

Dr. Sommer earned his PhD in Mathematics from Philipps-University Marburg (2017-2022), following a Master's degree (2015-2017) and Bachelor's degree (2012-2015), both in Mathematics from Friedrich Schiller University Jena.

His research focuses on parameterized algorithms, algorithm engineering, and graph algorithms, with applications to hard problems in Data Science and Machine Learning. He has made significant contributions to the theoretical foundations of graph problems, particularly in network analysis, community detection, and subgraph optimization. His methodology combines theoretical analysis with practical implementation, emphasizing both computational complexity and real-world applicability.

Dr. Sommer's publication record shows a strong emphasis on parameterized complexity, kernelization techniques, and practical algorithm implementations. His work spans from theoretical foundations to practical applications in network analysis, machine learning, and data science, with particular expertise in graph-theoretic problems and their computational aspects.

Scientific Awards:

• Humboldt fellow (Feodor Lynen scholarship for Postdocs)

Dr. Sommer collaborates extensively with researchers including Christian Komusiewicz, Niels Grüttemeier, and Tomohiro Koana. His work is supported by the Humboldt Foundation and has been published in top-tier computer science venues including Algorithmica, Journal of Graph Algorithms and Applications, and proceedings of major conferences like ESA and ISAAC.

He is part of the Algorithms and Complexity Group within the Institute of Logic and Computation at TU Vienna, contributing to research on fundamental algorithmic problems with applications across various domains. His current research explores the intersection of theoretical computer science with practical challenges in data science and machine learning.