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Prof. Dr. Thomas Bartz-Beielstein

Dr. rer. nat.
Fakultät für Informatik und Ingenieurwissenschaften

Institut für Data Science, Engineering, and Analytics (IDE+A)

Prof. Dr. Thomas Bartz-Beielstein

Campus Gummersbach
Steinmüllerallee 1
51643 Gummersbach
Raum 1.519 Postanschrift


  • Telefon+49 2261-8196-6391

Sprechstunden

Dienstag, 11.00 bis 12.00 Uhr
Campus Gummersbach, Raum R 1.519
Steinmüllerallee 6

Funktionen

  • InstitutsdirektorIn
  • LaborleiterIn
  • ProdekanIn
  • Mitglied der Ständigen Kommission für Forschung und Wissenstransfer
  • Beauftragter für den Studienfonds Oberberg
  • Sprecher des Forschungsschwerpunkts Computational Intelligence plus (CIplus)
  • Mitglied der Ständigen Kommission zur Förderung des wissenschaftlichen Nachwuchses
  • Gründungsmitglied der Fachgruppe Digitalisierung in Wirtschaft und Gesellschaft des Graduierteninstituts NRW

Aufgabenbereiche

  • Promotionsprogramm IDE+A
  • Promotionskolloquium IDE+A

Lehrgebiete

  • Angewandte Mathematik Simulation und Optimierung IDE+A
  • Computational Intelligence Evolutionäre Algorithmen IDE+A

Forschungsgebiete

  • Künstliche Intelligenz (Artificial Intelligence)
  • Optimierung und Simulation
  • Chandrasekaran, Sowmya; Bartz-Beielstein, Thomas (2023): A Robust Statistical Framework for the Analysis of the Performances of Stochastic Optimization Algorithms Using the Principles of Severity. In: Applications of Evolutionary Computation: 26th European Conference, EvoApplications 2023, Held as Part of EvoStar 2023, Brno, Czech Republic, April 12–14, 2023, Proceedings. 26th International Conference on Applications of Evolutionary Computation, EvoApplications 2023, held as part of EvoStar 2023; Brno,Czech; 12.04.-14.04.2023., S. 426 - 441.
  • Vodopija, Aljoša; Stork, Jörg; Bartz-Beielstein, Thomas; Filipič, Bogdan (2022): Elevator Group Control as a Constrained Multiobjective Optimization Problem. In: Applied Soft Computing : The Official Journal of the World Federation on Soft Computing (WFSC). Vol. 115. (peer-reviewed/Open Access)
  • Rehbach, Frederik; Zaefferer, Martin; Fischbach, Andreas; Rudolph, Gunter; Bartz-Beielstein, Thomas (2022): Benchmark-Driven Configuration of a Parallel Model-Based Optimization Algorithm. In: IEEE Transactions on Evolutionary Computation., S. 1 - 14. (peer-reviewed)
  • Rebolledo, Margarita; Zeeuwe, Daan; Bartz-Beielstein, Thomas; Eiben, Agoston Endre (2022): Co-Optimizing for Task Performance and Energy Efficiency in Evolvable Robots. In: Engineering Applications of Artificial Intelligence : The International Journal of Real-Time Automation. Vol. 113. (peer-reviewed/Open Access)
  • Bartz, Eva; Bartz-Beielstein, Thomas; Zaefferer, Martin; Mersmann, Olaf (Hrsg.) (2022): Hyperparameter Tuning for Machine and Deep Learning with R : A Practical Guide. Singapore: Springer Nature. (Open Access)
  • Bartz-Beielstein, Thomas; Mersmann, Olaf; Chandrasekaran, Sowmya (2022): Ranking and Result Aggregation. In: Bartz, Eva; Bartz-Beielstein, Thomas; Zaefferer, Martin; Mersmann, Olaf (Hrsg.): Hyperparameter Tuning for Machine and Deep Learning with R : A Practical Guide. Singapore: Springer Nature, S. 121 - 161. (peer-reviewed/Open Access)
  • Bartz-Beielstein, Thomas; Zaefferer, Martin (2022): Hyperparameter Tuning Approaches. In: Bartz, Eva; Bartz-Beielstein, Thomas; Zaefferer, Martin; Mersmann, Olaf (Hrsg.): Hyperparameter Tuning for Machine and Deep Learning with R : A Practical Guide. Singapore: Springer Nature, S. 71 - 119. (peer-reviewed/Open Access)
  • Bartz-Beielstein, Thomas; Zaefferer, Martin (2022): Models. In: Bartz, Eva; Bartz-Beielstein, Thomas; Zaefferer, Martin; Mersmann, Olaf (Hrsg.): Hyperparameter Tuning for Machine and Deep Learning with R : A Practical Guide. Singapore: Springer Nature, S. 27 - 69. (peer-reviewed/Open Access)
  • Bartz-Beielstein, Thomas; Zaefferer, Martin; Mersmann, Olaf (2022): Tuning : Methodology. In: Bartz, Eva; Bartz-Beielstein, Thomas; Zaefferer, Martin; Mersmann, Olaf (Hrsg.): Hyperparameter Tuning for Machine and Deep Learning with R : A Practical Guide. Singapore: Springer Nature, S. 7 - 26. (peer-reviewed/Open Access)
  • Bartz-Beielstein, Thomas; Chandrasekaran, Sowmya; Rehbach, Frederik (2022): Case Study III: Tuning of Deep Neural Networks. In: Bartz, Eva; Bartz-Beielstein, Thomas; Zaefferer, Martin; Mersmann, Olaf (Hrsg.): Hyperparameter Tuning for Machine and Deep Learning with R : A Practical Guide. Singapore: Springer Nature, S. 235 - 269. (peer-reviewed/Open Access)
  • Bartz-Beielstein, Thomas; Chandrasekaran, Sowmya; Rehbach, Frederik (2022): Case Study II : Tuning of Gradient Boosting (xgboost). In: Bartz, Eva; Bartz-Beielstein, Thomas; Zaefferer, Martin; Mersmann, Olaf (Hrsg.): Hyperparameter Tuning for Machine and Deep Learning with R : A Practical Guide. Singapore: Springer Nature, S. 221 - 234. (peer-reviewed/Open Access)
  • Bartz-Beielstein, Thomas; Chandrasekaran, Sowmya; Rehbach, Frederik; Zaefferer, Martin (2022): Case Study I: Tuning Random Forest (Ranger). In: Bartz, Eva; Bartz-Beielstein, Thomas; Zaefferer, Martin; Mersmann, Olaf (Hrsg.): Hyperparameter Tuning for Machine and Deep Learning with R : A Practical Guide. Singapore: Springer Nature, S. 187 - 220. (peer-reviewed/Open Access)
  • Bartz-Beielstein, Thomas (2022): Hyperparameter Tuning and Optimization Applications. In: Bartz, Eva; Bartz-Beielstein, Thomas; Zaefferer, Martin; Mersmann, Olaf (Hrsg.): Hyperparameter Tuning for Machine and Deep Learning with R : A Practical Guide. Singapore: Springer Nature, S. 165 - 175. (peer-reviewed/Open Access)
  • Zaefferer, Martin; Mersmann, Olaf; Bartz-Beielstein, Thomas (2022): Global Study : Influence of Tuning. In: Bartz, Eva; Bartz-Beielstein, Thomas; Zaefferer, Martin; Mersmann, Olaf (Hrsg.): Hyperparameter Tuning for Machine and Deep Learning with R : A Practical Guide. Singapore: Springer Nature, S. 283 - 301. (peer-reviewed/Open Access)
  • Strohschein, Jan; Fischbach, Andreas; Bunte, Andreas; Faeskorn-Woyke, Heide; Moriz, Natalia; Bartz-Beielstein, Thomas (2021): Cognitive Capabilities for the CAAI in Cyber-Physical Production Systems. In: The International Journal of Advanced Manufacturing Technology. Vol. 115, S. 3513 - 3532. (peer-reviewed/Open Access)
  • Bartz-Beielstein, Thomas; Rehbach, Frederik; Rebolledo, Margarita (2021): Tuning Algorithms for Stochastic Black-Box Optimization : State of the Art and Future Perspectives. In: Pardalos, Panos M.; Rasskazova, Varvara; Vrahatis, Michael N. (Hrsg.): Black Box Optimization, Machine Learning, and No-Free Lunch Theorems. Cham: Springer (Springer Optimization and Its Applications), S. 67 - 108.
  • Stork, Jörg; Wenzel, Philip; Landwein, Severin; Algorri, Maria Elena; Zaefferer, Martin; Kusch, Wolfgang; Staubach, Martin; Bartz-Beielstein, Thomas; Köhn, Hartmut; Dejager, Hermann; Wolf, Christian (2021): Underwater Acoustic Networks for Security Risk Assessment in Public Drinking Water Reservoirs. In: De.arXiv.org., S. 1 - 24. (Open Access)
  • Gentile, Lorenzo; Greco, Cristian; Minisci, Edmondo; Bartz-Beielstein, Thomas; Vasile, Massimiliano (2021): Stochastic Satellite Tracking with Constrained Budget via Structured-Chromosome Genetic Algorithms. In: Optimization and Engineering : International Multidisciplinary Journal to Promote Optimization Theory & Applications in Engineering Sciences. (peer-reviewed/Open Access)
  • Bartz, Eva; Zaefferer, Martin; Mersmann, Olaf; Bartz-Beielstein, Thomas (2021): Experimental Investigation and Evaluation of Model-Based Hyperparameter Optimization. (Open Access)
  • Bartz-Beielstein, Thomas; Dröscher, Marcel; Gür, Alpar; Hinterleitner, Alexander; Mersmann, Olaf; Peeva, Dessislava; Reese, Lennard; Rehbach, Nicolas; Rehbach, Frederik; Sen, Amrita; Subbotin, Aleksandr; Zaefferer, Martin (2021): Resource Planning for Hospitals under Special Consideration of the COVID-19 Pandemic: Optimization and Sensitivity Analysis. (Open Access)
  • Bartz-Beielstein, Thomas; Dröscher, Marcel; Gür, Alpar; Hinterleitner, Alexander; Lawton, Tom; Mersmann, Olaf; Peeva, Dessislava; Reese, Lennard; Rehbach, Frederik; Rehbach, Nicolas; Sen, Amrita; Subbotin, Aleksandr; Zaefferer, Martin (2021): Optimization and Adaptation of a Resource Planning Tool for Hospitals Under Special Consideration of the COVID-19 Pandemic. 2021 IEEE Congress on Evolutionary Computation, CEC 2021 - Proceedings. Piscataway, NJ: Institute of Electrical and Electronics Engineers Inc., S. 728 - 735. (peer-reviewed)
  • Rebolledo, Margarita; Eiben, Agoston Endre; Bartz-Beielstein, Thomas (2021): Bayesian Networks for Mood Prediction Using Unobtrusive Ecological Momentary Assessments. In: Castillo, Pedro A.; Laredo, Juan Luis Jiménez (Hrsg.): Applications of Evolutionary Computation : 24th International Conference, EvoApplications 2021, Held as Part of EvoStar 2021, Virtual Event, April 7–9, 2021, Proceedings. Cham: Springer (Lecture Notes in Computer Science), S. 373 - 387. (peer-reviewed)
  • Rebolledo, Margarita; Zeeuwe, Daan; Bartz-Beielstein, Thomas; Eiben, Agoston Endre (2021): Impact of Energy Efficiency on the Morphology and Behaviour of Evolved Robots. In: Chicano, Francisco; Krawiec, Krzysztof (Hrsg.): GECCO '21 : Genetic and Evolutionary Computation Conference. New York: Association for Computing Machinery, S. 109 - 110. (peer-reviewed/Open Access)
  • Bartz-Beielstein, Thomas; Dröscher, Marcel; Gür, Alpar; Hinterleitner, Alexander; Mersmann, Olaf; Peeva, Dessislava Todorova; Reese, Lennard; Rehbach, Nicolas Alexander; Rehbach, Frederik; Sen, Amrita; Subbotin, Aleksandr; Zaefferer, Martin (2021): Resource Planning for Hospitals Under Special Consideration of the COVID-19 Pandemic : Optimization and Sensitivity Analysis. In: Chicano, Francisco; Krawiec, Krzysztof (Hrsg.): GECCO '21 : Genetic and Evolutionary Computation Conference. New York: Association for Computing Machinery, S. 293 - 294. (Open Access)
  • Stork, Jörg; Zaefferer, Martin; Eisler, Nils; Tichelmann, Patrick; Bartz-Beielstein, Thomas; Eiben, Agoston Endre (2021): Behavior-Based Neuroevolutionary Training in Reinforcement Learning. In: Chicano, Francisco; Krawiec, Krzysztof (Hrsg.): GECCO '21 : Genetic and Evolutionary Computation Conference. New York: Association for Computing Machinery, S. 1753 - 1761. (Open Access)
  • Fischbach, Andreas; Strohschein, Jan; Bunte, Andreas; Stork, Jörg; Faeskorn-Woyke, Heide; Moriz, Natalia; Bartz-Beielstein, Thomas (2020): CAAI - A Cognitive Architecture to Introduce Artificial Intelligence in Cyber-Physical Production Systems. (Open Access)
  • Bartz, Eva; Zaefferer, Martin; Katagiri, Takeshi; Bartz-Beielstein, Thomas (2020): Architektur und Transport: Seillose, lineare Aufzüge und Künstliche Intelligenz. In: Transforming Cities : Urbane Systeme im Wandel. Vol. 2, S. 10 - 12.
  • Rehbach, Frederik; Zaefferer, Martin; Naujoks, Boris; Bartz-Beielstein, Thomas (2020): Expected Improvement versus Predicted Value in Surrogate-Based Optimization. (Open Access)
  • Rebolledo Coy, Margarita Alejandra; Stoean, Ruxandra; Eiben, A. E.; Bartz-Beielstein, Thomas (2020): Hybrid Variable Selection and Support Vector Regression for Gas Sensor Optimization. In: Filipič, Bogdan; Minisci, Edmondo; Vasile, Massimiliano (Hrsg.): Bioinspired Optimization Methods and Their Applications : Proceedings. Cham: Springer International Publishing (Lecture Notes in Computer Science), S. 281 - 293. (peer-reviewed)
  • Stork, Jörg; Eiben, A. E.; Bartz-Beielstein, Thomas (2020): A New Taxonomy of Global Optimization Algorithms. In: Natural Computing., S. 1 - 24. (Open Access)
  • Stork, Jörg; Zaefferer, Martin; Bartz-Beielstein, Thomas; Eiben, A. E. (2020): Understanding the Behavior of Reinforcement Learning Agents. In: Filipič, Bogdan; Minisci, Edmondo; Vasile, Massimiliano (Hrsg.): Bioinspired Optimization Methods and Their Applications : Proceedings. Cham: Springer International Publishing (Lecture Notes in Computer Science), S. 148 - 160. (peer-reviewed/Open Access)
  • Bartz-Beielstein, Thomas; Zaefferer, Martin (2020): Big Data is often just Bad Data. In: Digital Xchange 2020; Bergisches Rheinland, Germany; 06.06.2020.
  • Peetz, Tom; Vogt, Sebastian; Zaefferer, Martin; Bartz-Beielstein, Thomas (2020): Simulation of an Elevator Group Control Using Generative Adversarial Networks and Related AI Tools. (Open Access)
  • Rebolledo Coy, Margarita Alejandra; Chandrasekaran, Sowmya; Bartz-Beielstein, Thomas (2020): Technical Report: Flushing Strategies in Drinking Water Systems. (Open Access)
  • Chandrasekaran, Sowmya; Rebolledo Coy, Margarita Alejandra; Bartz-Beielstein, Thomas (2020): EventDetectR-An Open-Source Event Detection System. (Open Access)
  • Fischbach, Andreas; Strohschein, Jan; Bunte, Andreas; Stork, Jörg; Faeskorn-Woyke, Heide; Moriz, Natalia; Bartz-Beielstein, Thomas (2020): CAAI : A Cognitive Architecture to Introduce Artificial Intelligence in Cyber-physical Production Systems. In: The International Journal of Advanced Manufacturing Technology. Vol. 111, S. 609 - 626. (peer-reviewed/Open Access)
  • Rehbach, Frederik; Gentile, Lorenzo; Bartz-Beielstein, Thomas (2020): Variable Reduction for Surrogate-Based Optimization. GECCO '20 : Proceedings of the 2020 Genetic and Evolutionary Computation Conference. New York: Association for Computing Machinery (GECCO '20), S. 1177 - 1185.
  • Rehbach, Frederik; Zaefferer, Martin; Naujoks, Boris; Bartz-Beielstein, Thomas (2020): Expected Improvement versus Predicted Value in Surrogate-Based Optimization. GECCO '20 : Proceedings of the 2020 Genetic and Evolutionary Computation Conference. New York: Association for Computing Machinery (GECCO '20), S. 868 - 876. (peer-reviewed/Open Access)
  • Rebolledo Coy, Margarita Alejandra; Rehbach, Frederik; Eiben, Agoston Endre; Bartz-Beielstein, Thomas (2020): Parallelized Bayesian Optimization for Expensive Robot Controller Evolution. In: Bäck, Thomas; Preuss, Mike; Deutz, André; Wang, Hao; Doerr, Carola; Emmerich, Michael; Trautmann, Heike (Hrsg.): Parallel Problem Solving from Nature - PPSN XVI : Proceedings, Part I. Cham: Springer (Lecture Notes in Computer Science), S. 243 - 256.
  • Rebolledo Coy, Margarita Alejandra; Rehbach, Frederik; Eiben, Agoston Endre; Bartz-Beielstein, Thomas (2020): Parallelized Bayesian Optimization for Problems with Expensive Evaluation Functions. GECCO '20 : Proceedings of the 2020 Genetic and Evolutionary Computation Conference. New York: Association for Computing Machinery (GECCO '20), S. 231 - 232.
  • Bartz-Beielstein, Thomas; Bartz, Eva; Rehbach, Frederik; Mersmann, Olaf (2020): Optimization of High-dimensional Simulation Models Using Synthetic Data. (Open Access)
  • Bartz, Eva; Bartz-Beielstein, Thomas; Rehbach, Frederik; Mersmann, Olaf; Mühlenhaus, Ralf; Schmallenbach, Ralf; Leisner, Sarah; Hahn, Nikola; Ortlieb, Friedhelm; Elvermann, Kaija (2020): Einsatz künstlicher Intelligenz in der Bedarfsplanung im Gesundheitswesen, hier in der Bedarfsplanung von Intensivbetten im Pandemiefall. Abstractbuch zum 20. Kongress der Deutschen Interdisziplinären Vereinigung für Intensiv- und Notfallmedizin e.V. Wissen schafft Vertrauen. Berlin: DIVI e.V., S. 99 - 100. (Open Access)
  • Strohschein, Jan; Fischbach, Andreas; Bunte, Andreas; Faeskorn-Woyke, Heide; Moriz, Natalia; Bartz-Beielstein, Thomas (2020): Cognitive Capabilities for the CAAI in Cyber-Physical Production Systems. (Open Access)
  • Bartz-Beielstein, Thomas; Doerr, Carola; van der Berg, Daan; Bossek, Jakob; Chandrasekaran, Sowmya; Eftimov, Tome; Fischbach, Andreas; Kerschke, Pascal; Lopez-Ibanez, Manuel; Malan, Katherine M.; Moore, Jason H.; Naujoks, Boris; Orzechowski, Patryk; Volz, Vanessa; Wagner, Markus; Weise, Thomas (2020): Benchmarking in Optimization : Best Practice and Open Issues. (Open Access)
  • Fischbach, Andreas; Bartz-Beielstein, Thomas (2020): Improving the Reliability of Test Functions Generators. In: Applied Soft Computing : The Official Journal of the World Federation on Soft Computing (WFSC). Vol. 92. (peer-reviewed)
  • Gentile, Lorenzo; Bartz-Beielstein, Thomas; Zaefferer, Martin (2020): Sequential Parameter Optimization for Mixed-Discrete Problems. In: Vasile, Massimiliano (Hrsg.): Optimization Under Uncertainty with Applications to Aerospace Engineering. Cham: Springer, S. 333 - 355.
  • Bartz-Beielstein, Thomas; Rehbach, Frederik; Mersmann, Olaf; Bartz, Eva (2020): Hospital Capacity Planning Using Discrete Event Simulation Under Special Consideration of the COVID-19 Pandemic. (Open Access)
  • Rebolledo Coy, Margarita Alejandra; Chandrasekaran, Sowmya; Bartz-Beielstein, Thomas (2020): Sensor Placement for Contamination Detection in Water Distribution Systems. (Open Access)
  • Gentile, Lorenzo; Filippi, Gianluca; Minisci, Edmondo; Bartz-Beielstein, Thomas; Vasile, Massimiliano (2020): Preliminary Spacecraft Design by Means of Structured-Chromosome Genetic Algorithms. 2020 IEEE Congress on Evolutionary Computation (CEC). IEEE, S. 2107 - 2114. (Open Access)
  • Gentile, Lorenzo; Morales, Elisa; Quagliarella, Domenico; Minisci, Edmondo; Bartz-Beielstein, Thomas; Tognaccini, Renato (2020): High-Lift Devices Topology Optimisation using Structured-Chromosome Genetic Algorithm. 2020 IEEE Congress on Evolutionary Computation (CEC). IEEE, S. 1366 - 1374. (Open Access)
  • Bartz-Beielstein, Thomas; Doerr, Carola; Bossek, Jakob; Chandrasekaran, Sowmya; Eftimov, Tome; Fischbach, Andreas; Kerschke, Pascal; Lopez-Ibanez, Manuel; Malan, Katherine M.; Moore, Jason H.; Naujoks, Boris; Orzechowski, Patryk; Volz, Vanessa; Wagner, Markus; Weise, Thomas (2020): Benchmarking in Optimization : Best Practice and Open Issues. Köln: Technische Hochschule Köln (2/2020). (peer-reviewed/Open Access)
  • Fischbach, Andreas; Strohschein, Jan; Bunte, Andreas; Stork, Jörg; Faeskorn-Woyke, Heide; Moriz, Natalia; Bartz-Beielstein, Thomas (2020): CAAI - A Cognitive Architecture to Introduce Artificial Intelligence in Cyber-Physical Production Systems(1/2020). (Open Access)
  • Rebolledo Coy, Margarita Alejandra; Chandrasekaran, Sowmya; Bartz-Beielstein, Thomas (2020): Technical Report: Flushing Strategies in Drinking Water Systems. Köln: Technische Hochschule Köln (11/2020). (peer-reviewed/Open Access)
  • Rehbach, Frederik; Gentile, Lorenzo; Bartz-Beielstein, Thomas (2020): Feature Selection for Surrogate Model-Based Optimization. Köln: Technische Hochschule Köln (03/2020). (peer-reviewed/Open Access)
  • Rehbach, Frederik; Zaefferer, Martin; Naujoks, Boris; Bartz-Beielstein, Thomas (2020): Expected Improvement versus Predicted Value in Surrogate-Based Optimization. Köln: Technische Hochschule Köln (4/2020). (peer-reviewed/Open Access)
  • Rehbach, Frederik; Gentile, Lorenzo; Bartz-Beielstein, Thomas (2020): Variable Reduction for Surrogate-Based Optimization. Köln: Technische Hochschule Köln (5/2020). (peer-reviewed/Open Access)
  • Rebolledo Coy, Margarita Alejandra; Chandrasekaran, Sowmya; Bartz-Beielstein, Thomas (2020): Sensor Placement for Contamination Detection in Water Distribution Systems. Köln: Technische Hochschule Köln (10/2020). (peer-reviewed/Open Access)
  • Chandrasekaran, Sowmya; Rebolledo Coy, Margarita Alejandra; Bartz-Beielstein, Thomas (2020): EventDetectR – An Open-Source Event Detection System. Köln: Technische Hochschule Köln (9/2020). (peer-reviewed/Open Access)
  • Friese, Martina; Bartz-Beielstein, Thomas; Bäck, Thomas; Naujoks, Boris; Emmerich, Michael (2019): Weighted Ensembles in Model-Based Global Optimization. In: Proceedings LeGo - 14th International Global Optimization Workshop. 14th International Global Optimization Workshop; Leiden, the Netherlands; 18.09.-21.09.2018. (peer-reviewed)
  • Rehbach, Frederik; Gentile, Lorenzo; Bartz-Beielstein, Thomas (2019): Feature Selection for Surrogate Model-Based Optimization. In: López-Ibáñez, Manuel (Hrsg.): GECCO' 19 : Proceedings of the Genetic and Evolutionary Computation Conference Companion. New York: Association for Computing Machinery, S. 399 - 400. (peer-reviewed)
  • Rehbach, Frederik; Gentile, Lorenzo; Bartz-Beielstein, Thomas (2019): Variablenreduktion für Surrogat-Modell basierte Optimierung. In: Hoffmann, Frank; Hüllermeier, Eyke; Mikut, Ralf (Hrsg.): Proceedings. 29. Workshop Computational Intelligence. Karlsruhe: KIT Scientific Publishing, S. 209 - 216. (peer-reviewed)
  • Zaefferer, Martin; Bartz-Beielstein, Thomas; Rudolph, Günter (2019): An Empirical Approach for Probing the Definiteness of Kernels. In: Soft Computing : A Fusion of Foundations, Methodologies and Applications. Vol. 23, S. 10939 - 10952. (peer-reviewed)
  • Stork, Jörg; Zaefferer, Martin; Bartz-Beielstein, Thomas (2019): Improving NeuroEvolution Efficiency by Surrogate Model-Based Optimization with Phenotypic Distance Kernels. In: Kaufmann, Paul; Castillo, Pedro A. (Hrsg.): Applications of Evolutionary Computation : 22nd International Conference, EvoApplications 2019. Cham: Springer, S. 504 - 519. (peer-reviewed/Open Access)
  • Stork, Jörg; Zaefferer, Martin; Rehbach, Frederik; Gentile, Lorenzo; Bartz-Beielstein, Thomas (2019): Surrogate Models for Enhancing the Efficiency of Neuroevolution in Reinforcement Learning. In: López-Ibáñez, Manuel (Hrsg.): GECCO' 19 : Proceedings of the Genetic and Evolutionary Computation Conference Companion. New York: Association for Computing Machinery, S. 934 - 942. (peer-reviewed/Open Access)
  • Stork, Jörg; Friese, Martina; Zaefferer, Martin; Bartz-Beielstein, Thomas; Fischbach, Andreas; Breiderhoff, Beate; Naujoks, Boris; Tušar, Tea (2019): Open Issues in Surrogate-Assisted Optimization. In: Bartz-Beielstein, Thomas; Filipič, Bogdan; Korošec, Peter; Talbi, El-Ghazali (Hrsg.): High-Performance Simulation-Based Optimization. Cham: Springer, S. 225 - 244. (peer-reviewed)
  • Gentile, Lorenzo; Greco, Cristian; Minisci, Edmondo; Bartz-Beielstein, Thomas; Vasile, Massimiliano (2019): An Optimization Approach for Designing Optimal Tracking Campaigns for Low-resources Deep-space Missions. In: 70th International Astronautical Congress; Washington, D.C; 21.10.2019-25.10.2019. (peer-reviewed)
  • Bunte, Andreas; Fischbach, Andreas; Strohschein, Jan; Bartz-Beielstein, Thomas; Faeskorn-Woyke, Heide; Niggemann, Oliver (2019): Evaluation of Cognitive Architectures for Cyber-Physical Production Systems. In: De.arXiv.org. (Open Access)
  • Stork, Jörg; Zaefferer, Martin; Bartz-Beielstein, Thomas; Eiben, Agoston Endre (2019): Surrogate Models for Enhancing the Efficiency of Neuroevolution in Reinforcement Learning. In: De.arXiv.org., S. 1 - 9. (peer-reviewed/Open Access)
  • Stork, Jörg; Zaefferer, Martin; Bartz-Beielstein, Thomas (2019): Improving NeuroEvolution Efficiency by Surrogate Model-based Optimization with Phenotypic Distance Kernels. In: De.arXiv.org., S. 1 - 16. (peer-reviewed/Open Access)
  • Bartz-Beielstein, Thomas (2019): Why We Need an AI-Resilient Society. In: De.arxiv.org. (Open Access)
  • Bartz-Beielstein, Thomas; Filipič, Bogdan; Korošec, Peter; Talbi, El-Ghazali (Hrsg.) (2019): High-Performance Simulation-Based Optimization. Cham: Springer.
  • Chugh, Tinkle; Rahat, Alma; Volz, Vanessa; Zaefferer, Martin (2019): Towards Better Integration of Surrogate Models and Optimizers. In: Bartz-Beielstein, Thomas; Filipič, Bogdan; Korošec, Peter; Talbi, El-Ghazali (Hrsg.): High-Performance Simulation-Based Optimization. Cham: Springer, S. 137 - 163.
  • Greco, Cristian; Gentile, Lorenzo; Vasile, Massimiliano; Minisci, Edmondo; Bartz-Beielstein, Thomas (2019): Robust Particle Filter for Space Objects Tracking under Severe Uncertainty. In: 2019 AAS/AIAA Astrodynamics Specialist Conference; Portland, Maine; 11.08.-15.08.2019. (peer-reviewed)
  • Gentile, Lorenzo; Greco, Cristian; Minisci, Edmondo; Bartz-Beielstein, Thomas; Vasile, Massimiliano (2019): Structured-chromosome GA Optimisation for Satellite Tracking. In: López-Ibáñez, Manuel (Hrsg.): GECCO' 19 : Proceedings of the Genetic and Evolutionary Computation Conference Companion. New York: Association for Computing Machinery, S. 1955 - 1963. (peer-reviewed)
  • Bunte, Andreas; Fischbach, Andreas; Strohschein, Jan; Bartz-Beielstein, Thomas; Faeskorn-Woyke, Heide; Niggemann, Oliver (2019): Evaluation of Cognitive Architectures for Cyber-Physical Production Systems. 2019 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA 2019) : Proceedings. Piscataway: IEEE, S. 729 - 736. (peer-reviewed)
  • Greco, Cristian; Gentile, Lorenzo; Filippi, Gianluca; Minisci, Edmondo; Bartz-Beielstein, Thomas (2019): Autonomous Generation of Observation Schedules for Tracking Satellites with Structured-Chromosome GA Optimisation. 2019 IEEE Congress on Evolutionary Computation. Piscataway, NJ: IEEE, S. 497 - 505.
  • Schagen, André; Rehbach, Frederik; Bartz-Beielstein, Thomas (2018): Modellgestützter Evolutionärer Algorith­mus zur Optimierung von Gasverteilsystemen in Elektroabscheidern von Kohlekraftwerken. In: VGB powertech., S. 65 - 72.
  • Bartz-Beielstein, Thomas; Zaefferer, Martin; Pham, Quoc Cuong (2018): Optimization via Multimodel Simulation : A New Approach to Optimization of Cyclone Separator Geometries. In: Structural and Multidisciplinary Optimization : Research Journal. Vol. 58, S. 919 - 933. (peer-reviewed/Open Access)
  • Zaefferer, Martin; Bartz-Beielstein, Thomas; Rudolph, Günter (2018): An Empirical Approach for Probing the Definiteness of Kernels. In: Soft computing. Vol. 55, S. 154. (Open Access)
  • Stork, Jörg; Zaefferer, Martin; Bartz-Beielstein, Thomas (2018): Distance-based Kernels for Surrogate Model-based Neuroevolution. In: De.arxiv.org. (Open Access)
  • Bartz-Beielstein, Thomas; Filipič, Bogdan; Korošec, Peter; Melab, Nouredine; Naujoks, Boris; Talbi, El-Ghazali (2018): Potential Complex Optimisation Problems in Science and Industry. (Open Access)
  • Zaefferer, Martin; Stork, Jörg; Flasch, Oliver; Bartz-Beielstein, Thomas (2018): Linear Combination of Distance Measures for Surrogate Models in Genetic Programming. In: Auger, Anne; Fonseca, Carlos M.; Lourenço, Nuno (Hrsg.): Parallel Problem Solving from Nature – PPSN XV : 15th International Conference, Coimbra, Portugal, September 8–12, 2018, Proceedings, Part II. Springer International Publishing (Theoretical Computer Science and General Issues), S. 220 - 231. (peer-reviewed/Open Access)
  • Breiderhoff, Beate; Naujoks, Boris; Bartz-Beielstein, Thomas; Filipič, Bogdan (2018): Expensive Optimisation Exemplified by ECG Simulator Parameter Tuning. In: Proceedings of the 21st International Multiconference INFORMATION SOCIETY – IS 2018 : Volume D, Zbornik 21. mednarodne multikonference INFORMACIJSKA DRUŽBA - IS 2018 : Zvezek D. International Conference on High-Performance Optimization in Industry, HPOI 2018; Ljubljana, Slovenia; 08.10.-12.10.2018., S. 15 - 19. (peer-reviewed/Open Access)
  • Filipič, Bogdan; Bartz-Beielstein, Thomas (Hrsg.) (2018): Proceedings of the 21st International Multiconference INFORMATION SOCIETY – IS 2018 : Volume D, Zbornik 21. mednarodne multikonference INFORMACIJSKA DRUŽBA - IS 2018 : Zvezek D. (peer-reviewed/Open Access)
  • Rehbach, Frederik; Zaefferer, Martin; Stork, Jörg; Bartz-Beielstein, Thomas (2018): Comparison of Parallel Surrogate-Assisted Optimization Approaches. In: Takadama, Keiki; Aguirre, Hernan (Hrsg.): GECCO '18 : Proceeding of the Genetic and Evolutionary Computation Conference. New York, NY: ACM, S. 1348 - 1355. (peer-reviewed/Open Access)
  • Gentile, Lorenzo; Zaefferer, Martin; Giugliano, Dario; Chen, Haofeng; Bartz-Beielstein, Thomas (2018): Surrogate Assisted Optimization of Particle Reinforced Metal Matrix Composites. In: Takadama, Keiki; Aguirre, Hernan (Hrsg.): GECCO '18 : Proceeding of the Genetic and Evolutionary Computation Conference. New York, NY: ACM, S. 1238 - 1245. (peer-reviewed)
  • Rebolledo Coy, Margarita Alejandra; Bartz-Beielstein, Thomas (2018): Modelling Zero-inflated Rainfall Data through the Use of Gaussian Process and Bayesian Regression(5/2018). (peer-reviewed/Open Access)
  • Stork, Jörg; Bartz-Beielstein, Thomas (2018): Global Optimization Strategies : Analogies to Human Behavior(2/2018). (Open Access)
  • Stork, Jörg; Eiben, A. E.; Bartz-Beielstein, Thomas (2018): A New Taxonomy of Continuous Global Optimization Algorithms(4/2018). (Open Access)
  • Bartz-Beielstein, Thomas; Zaefferer, Martin; Pham, Quoc Cuong (2018): Optimization via Multimodel Simulation. Köln: Technische Hochschule Köln (1/2018). (peer-reviewed/Open Access)
  • Rehbach, Frederik; Zaefferer, Martin; Stork, Jörg; Bartz-Beielstein, Thomas (2018): Comparison of Parallel Surrogate-Assisted Optimization Approaches(7/2018). (peer-reviewed/Open Access)
  • Coy Rebolledo, Margarita Alejandra; Baez, Oscar Manuel; Bartz-Beielstein, Thomas; Ribbe, Lars (2017): Bias-Correction of Satellite Rainfall Estimates Through the Use of Metamodels using Gaussian Process and Bayesian Regression. A Case Study for the Imperial Basin (Chile). In: Hoffmann, Frank; Hüllermeier, E.; Mikut, Ralf (Hrsg.): Proceedings 27. Workshop Computational Intelligence, Dortmund, 23. - 24. November 2017. Karlsruhe: Kit Scientific Publishing, S. 261 - 277.
  • Bartz-Beielstein, Thomas; Moritz, Steffen; Strohschein, Jan; Winterberg, T.; Gross, Dimitri; Seger, Ralf (2017): Trinkwassersicherheit mit Predictive Analytics und Oracle. In: Business News., S. 18 - 23. (peer-reviewed)
  • Bartz-Beielstein, Thomas; Zaefferer, Martin (2017): Model-based Methods for Continuous and Discrete Global Optimization. In: Applied soft computing. Vol. 55, S. 154 - 167.
  • Krey, S.; Bartz-Beielstein, Thomas; Fu, Y.; Gorec, C. (2017): Structural Health Monitoring for Resource : Efficient Usage of Fibre-reinforced Plastic. In: Kestler, H.; Lausser, L.; Kraus, J.; Schmid, M.; Fürstberger, A. (Hrsg.): Statistical Computing 2017 : Abstracts der 49. Arbeitstagung der Arbeitsgruppen Statistical Computing (GMDS/IBS-DR), Klassifikation und Datenanalyse in den Biowissenschaften (GfKl) - 23.07.-25.07.2017, Schloss Reisensburg (Günzburg). Ulm: Universität Ulm, Univ., Fak. für Informatik, S. 9.
  • Moritz, Steffen; Bartz-Beielstein, Thomas (2017): imputeTS : Time Series Missing Value Imputation in R. In: The R Journal. Vol. 9, S. 207 - 218. (peer-reviewed)
  • Zaefferer, Martin; Fischbach, Andreas; Naujoks, Boris; Bartz-Beielstein, Thomas (2017): Simulation-based Test Functions for Optimization Algorithms. In: Bosman, Peter A. N. (Hrsg.): GECCO'17 : Proceedings of the 2017 Genetic and Evolutionary Computation Conference, Berlin 15.-19.07.2017. New York: Association for Computing Machinery, S. 905 - 912. (peer-reviewed)
  • Sardá-Espinosa, Alexis; Subbiah, Subanatarajan; Bartz-Beielstein, Thomas (2017): Conditional Inference Trees for Knowledge Extraction from Motor Health Condition Data. In: Engineering Applications of Artificial Intelligence : The International Journal of Real-Time Automation. Vol. 62, S. 26 - 37. (peer-reviewed)
  • Forschungspreis der TH Köln 2020
    Prof. Dr. Thomas Bartz-Beielstein, Professor für Angewandte Mathematik an der Fakultät für Informatik und Ingenieurwissenschaften erhält den mit 10.000 Euro dotierten Forschungspreis. Er forscht im Bereich der Computational Intelligence, einem Teilgebiet der Künstlichen Intelligenz. Sein Schwerpunkt sind evolutionäre Algorithmen zur Modellierung, Simulation und Optimierung von Prozessen, beispielweise in den Bereichen Industrie 4.0 und Big Data. Seit 2014 wurden von ihm zehn Forschungsprojekte mit hohem Praxisbezug durchgeführt, beispielsweise Projekte zur Trinkwasserversorgung und Datensouveränität sowie deren Auswirkungen auf die Gesellschaft. Bartz-Beielstein ist Mitbegründer und Mitglied des Forschungsschwerpunks Computational Intelligence plus sowie Direktor des interdisziplinärem Instituts für Data Science, Engineering, and Analytics, an dem aktuell 14 kooperative Promotionen durchgeführt werden. „Professor Bartz-Beielstein legt mit seiner Bewerbung für den ersten Forschungspreis der TH Köln die Messlatte hoch“, so die Jury in ihrer Begründung. „Seine beeindruckenden Forschungsleistungen im Bereich der Computational Intelligence manifestieren sich in ca. 50 Publikationen und hohen Drittmitteleinnahmen alleine innerhalb der letzten fünf Jahre. Sein Engagement für den wissenschaftlichen Nachwuchs, regelmäßige Gutachtertätigkeiten sowie maßgebliche Impulse zur Profilbildung der TH Köln weit über den Campus Gummersbach hinweg runden das Bild ab. Ein mehr als würdiger Kandidat.“
    Erster Tag der Forschung

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