Janek Thomas

1.5k total citations · 1 hit paper
15 papers, 606 citations indexed

About

Janek Thomas is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Information Systems. According to data from OpenAlex, Janek Thomas has authored 15 papers receiving a total of 606 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Artificial Intelligence, 6 papers in Computational Theory and Mathematics and 2 papers in Information Systems. Recurrent topics in Janek Thomas's work include Machine Learning and Data Classification (8 papers), Advanced Multi-Objective Optimization Algorithms (6 papers) and Metaheuristic Optimization Algorithms Research (2 papers). Janek Thomas is often cited by papers focused on Machine Learning and Data Classification (8 papers), Advanced Multi-Objective Optimization Algorithms (6 papers) and Metaheuristic Optimization Algorithms Research (2 papers). Janek Thomas collaborates with scholars based in Germany, United States and Netherlands. Janek Thomas's co-authors include Bernd Bischl, Stefan Coors, Martin Binder, Michel Lang, Tobias Pielok, Jakob Richter, Difan Deng, Marc Becker, Marius Lindauer and Theresa Ullmann and has published in prestigious journals such as IEEE Access, Statistics and Computing and Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery.

In The Last Decade

Janek Thomas

15 papers receiving 586 citations

Hit Papers

Hyperparameter optimization: Foundations, algorithms, bes... 2023 2026 2024 2025 2023 100 200 300
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Hyperparameter optimization: Foundations, algorithms, best practices, and open challenges
    2023 398 citations Bernd Bischl, Martin Binder et al. Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Janek Thomas Germany 7 205 60 50 40 39 15 606
Stefan Coors Germany 6 200 1.0× 56 0.9× 21 0.4× 37 0.9× 58 1.5× 7 739
Martin Binder Germany 5 190 0.9× 58 1.0× 15 0.3× 39 1.0× 60 1.5× 10 693
Yuchen Wu China 5 199 1.0× 82 1.4× 17 0.3× 35 0.9× 26 0.7× 12 664
Sergio González Spain 9 267 1.3× 87 1.4× 12 0.2× 28 0.7× 43 1.1× 15 618
Jianyu Wang China 12 109 0.5× 42 0.7× 28 0.6× 53 1.3× 14 0.4× 46 426
Mukta Paliwal India 6 219 1.1× 89 1.5× 15 0.3× 20 0.5× 48 1.2× 9 739
Usha A. Kumar India 6 236 1.2× 93 1.6× 16 0.3× 22 0.6× 56 1.4× 10 791
Kalpana Dahiya India 8 115 0.6× 47 0.8× 20 0.4× 26 0.7× 23 0.6× 28 588
José Antonio Gómez‐Ruiz Spain 12 174 0.8× 86 1.4× 17 0.3× 29 0.7× 41 1.1× 31 516
Varun Ojha United Kingdom 10 267 1.3× 100 1.7× 14 0.3× 19 0.5× 66 1.7× 50 785

Countries citing papers authored by Janek Thomas

Since Specialization
Citations

This map shows the geographic impact of Janek Thomas's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Janek Thomas with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Janek Thomas more than expected).

Fields of papers citing papers by Janek Thomas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Janek Thomas. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Janek Thomas. The network helps show where Janek Thomas may publish in the future.

Co-authorship network of co-authors of Janek Thomas

This figure shows the co-authorship network connecting the top 25 collaborators of Janek Thomas. A scholar is included among the top collaborators of Janek Thomas based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Janek Thomas. Janek Thomas is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

15 of 15 papers shown
1.
Pielok, Tobias, Florian Pfisterer, Stefan Coors, et al.. (2023). Multi-Objective Hyperparameter Optimization in Machine Learning—An Overview. Fraunhofer-Publica (Fraunhofer-Gesellschaft). 3(4). 1–50. 36 indexed citations
2.
Bischl, Bernd, Martin Binder, Michel Lang, et al.. (2023). Hyperparameter optimization: Foundations, algorithms, best practices, and open challenges. Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery. 13(2). 398 indexed citations breakdown →
3.
Bischl, Bernd, et al.. (2023). Multi-Objective Optimization of Performance and Interpretability of Tabular Supervised Machine Learning Models. Proceedings of the Genetic and Evolutionary Computation Conference. 538–547. 4 indexed citations
4.
Pargent, Florian, Florian Pfisterer, Janek Thomas, & Bernd Bischl. (2022). Regularized target encoding outperforms traditional methods in supervised machine learning with high cardinality features. Computational Statistics. 37(5). 2671–2692. 63 indexed citations
5.
Thomas, Janek, et al.. (2022). Structured Verification of Machine Learning Models in Industrial Settings. Big Data. 11(3). 181–198. 7 indexed citations
6.
Pfisterer, Florian, et al.. (2022). A collection of quality diversity optimization problems derived from hyperparameter optimization of machine learning models. Proceedings of the Genetic and Evolutionary Computation Conference Companion. 2136–2142. 2 indexed citations
7.
Gerostathopoulos, Ilias, František Plášil, Christian Prehofer, Janek Thomas, & Bernd Bischl. (2021). Automated Online Experiment-Driven Adaptation–Mechanics and Cost Aspects. IEEE Access. 9. 58079–58087. 3 indexed citations
8.
Thomas, Janek, et al.. (2021). Deep Semi-supervised Learning for Time Series Classification. 2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA). 422–428. 5 indexed citations
9.
Hofner, Benjamin, Andreas Mayr, Nora Fenske, Janek Thomas, & Matthias Schmid. (2021). Boosting Methods for 'GAMLSS' [R package gamboostLSS version 2.0-5]. 1 indexed citations
10.
Thomas, Janek. (2019). Gradient boosting in automatic machine learning: feature selection and hyperparameter optimization. Electronic Theses of LMU Munich (Ludwig-Maximilians-Universität München). 3 indexed citations
11.
Rijn, Jan N. van, Florian Pfisterer, Janek Thomas, et al.. (2018). Meta learning for defaults: symbolic defaults. Data Archiving and Networked Services (DANS). 2 indexed citations
12.
Thomas, Janek, et al.. (2018). compboost: Modular Framework for Component-Wise Boosting. The Journal of Open Source Software. 3(30). 967–967. 1 indexed citations
13.
Thomas, Janek, Tobias Hepp, Andreas Mayr, & Bernd Bischl. (2017). Probing for Sparse and Fast Variable Selection with Model-Based Boosting. Computational and Mathematical Methods in Medicine. 2017. 1–8. 22 indexed citations
14.
Thomas, Janek, Andreas Mayr, Bernd Bischl, et al.. (2017). Gradient boosting for distributional regression: faster tuning and improved variable selection via noncyclical updates. Statistics and Computing. 28(3). 673–687. 47 indexed citations
15.
Rietzler, Michael, Florian Geiselhart, Janek Thomas, & Enrico Rukzio. (2016). FusionKit. 73–84. 12 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Stefan Coors Breakdown of academic impact, for papers by Martin Binder Breakdown of academic impact, for papers by Yuchen Wu Breakdown of academic impact, for papers by Sergio González Breakdown of academic impact, for papers by Jianyu Wang Breakdown of academic impact, for papers by Mukta Paliwal Breakdown of academic impact, for papers by Usha A. Kumar Breakdown of academic impact, for papers by Kalpana Dahiya Breakdown of academic impact, for papers by José Antonio Gómez‐Ruiz Breakdown of academic impact, for papers by Varun Ojha
Rankless by CCL
2026