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Niki van Stein
Assistant professor
- Name
- Dr. N. van Stein
- Telephone
- +31 71 527 2727
- n.van.stein@liacs.leidenuniv.nl
- ORCID iD
- 0000-0002-0013-7969
Niki van Stein is a researcher in the Natural Computing Group of LIACS and manager of the applied data science lab. She received her PhD in Computer Science from Leiden University in 2018. Niki's research interest are in automated machine learning, global (Bayesian) optimization and neural architecture search.
Niki van Stein is a researcher in the Natural Computing Group of LIACS and manager of the applied data science lab. She received her PhD in Computer Science from Leiden University in 2018. Niki's research interest are in automated machine learning, global (Bayesian) optimization and neural architecture search.
Next to her research, Niki has founded several software solution-oriented companies such as Van Stein & Groentjes – Custom software development, and Smartnotation – the smart meeting minutes application.
Assistant professor
- Science
- Leiden Inst of Advanced Computer Science
- Winter R. de, Milatz B., Blank J., Stein N. van, Bäck T.H.W. & Deb K. (2024), Parallel multi-objective optimization for expensive and inexpensive objectives and constraints, Swarm and Evolutionary Computation 86: 101508.
- Long X.F., Vermetten D.L., Stein N. van & Kononova A.V. (2023), BBOB instance analysis: landscape properties and algorithm performance across problem instances. Correia J., Smith S. & Qaddoura R. (Eds.), Applications of evolutionary computation. International Conference on the Applications of Evolutionary Computation (Part of EvoStar) 12 April 2023 - 14 April 2023. Lecture Notes in Computer Science no. 13989. Cham: Springer. 380-395.
- Stein N. van, Vermetten D.L., Caraffini F. & Kononova A.V. (2023), Deep BIAS: detecting structural bias using explainable AI, GECCO '23 companion: proceedings of the companion conference on genetic and evolutionary computation. GECCO '23 Companion: Companion Conference on Genetic and Evolutionary Computation 15 July 2023 - 19 July 2023. New York, U.S.A.: Association for Computing Machinery. 455-458.
- Thomson S.L., Stein N. van, Berg D. van den & Leeuwen C. van (2023), The opaque nature of intelligence and the pursuit of explainable AI. Stein N. van, Marcelloni F., Lam H.K., Cottrell M. & Filipe J. (Eds.), Proceedings of the 15th International Joint Conference on Computational Intelligence. 15th International Conference on Neural Computation Theory and Applications 13 November 2023 - 15 November 2023: SciTePress . 555-564.
- Stein. N. van, Winter R. de, Bäck T.H.W. & Kononova A. V. (2023), AI for expensive optimization problems in industry, 2023 IEEE Conference on Artificial Intelligence (CAI). 2023 IEEE Conference on Artificial Intelligence 5 June 2023 - 6 June 2023: IEEE. 251-254.
- Lamers C.H.C.B., Vidal R., Belbachir N., Stein N. van, Bäck T.H.W. & Giampouras P. (2023), Clustering-based domain-incremental learning , Conference Proceedings 2023 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW). 2023 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW) 2 October 2023 - 6 October 2023: IEEE Computer Society. 3376-3384.
- Back T.H.W., Kononova A.V., Stein N. van, Wang H., Antonov K., Kalkreuth R.T., Nobel J.P. de, Vermetten D., Winter R. de & Ye F. (2023), Evolutionary algorithms for parameter optimization: thirty years later, Evolutionary Computation 31(2): 81-122.
- Zeiser A., Özcan B., Kracke C., Stein N. van & Bäck T.H.W. (2023), A data-centric approach to anomaly detection in layer-based additive manufacturing, at - Automatisierungstechnik 71(1): 81-89.
- Zeiser A., Özcan B., Stein N. van & Bäck T.H.W. (2023), Evaluation of deep unsupervised anomaly detection methods with a data-centric approach for on-line inspection, Computers in Industry 146: 103852.
- Stein N. van, Long F., Frenzel M., Krause P., Gitterle M. & Bäck T.H.W. (2023), DoE2Vec: deep-learning based features for exploratory landscape analysis, Proceedings of the Companion Conference on Genetic and Evolutionary Computation. GECCO '23 Companion: Companion Conference on Genetic and Evolutionary Computation 15 July 2023 - 19 July 2023. New York: Association for Computing Machinery. 515-518.
- Long F.X., Vermetten D, Kononova A.V., Kalkreuth R, Yang K., Bäck T.H.W. & Stein N. van (2023), Challenges of ELA-guided function evolution using genetic programming. Stein N. van, Marcelloni F., Lam H.K., Cottrell M. & Filipe J. (Eds.), Proceedings of the 15th international joint conference on computational intelligence ECTA. 15th International Joint Conference on Computational Intelligence - ECTA 13 November 2023 - 15 November 2023 no. 1. Portugal: SciTePress. 119-130.
- Antonov K., Kononova A.V., Bäck T.H.W. & Stein N. van (2023), Curing ill-conditionality via representation-agnostic distance-driven perturbations, Proceedings of the 17th ACM/SIGEVO conference on foundations of genetic algorithms. FOGA '23: Foundations of Genetic Algorithms XVII 30 August 2023 - 1 September 2023. New York, NY, USA: Association for Computing Machinery. 15–26.
- Huang Q., Bäck T.H.W. & Stein N. van (2023), Application of functional kernel hypothesis testing for channel selection in time series classification, 2023 IEEE Conference on Artificial Intelligence (CAI). 2023 IEEE Conference on Artificial Intelligence 5 June 2023 - 6 June 2023: IEEE Computer Society. 245-247.
- Antonov K., Botari T., Tukker T., Bäck T.H.W., Stein N. van & Kononova A.V. (2023), New solutions to Cooke triplet problem via analysis of attraction basins. Kress B.C. & Czarske J.W. (Eds.), Proceedings SPIE 12624, Digital Optical Technologies 2023. SPIE Digital Optical Technologies 2023 25 June 2023 - 29 June 2023: SPIE. 126240T.
- Lamers C.H.C.B., Vidal R., Belbachir N., Stein N. van, Bäck T.H.W. & Paris G. (2023), Clustering-based domain-incremental learning, Proceedings of the IEEE/CVF international conference on computer vision (ICCV) workshops. 2023 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW) 2 October 2023 - 6 October 2023: IEEE Computer Society. 3384-3392.
- Rooij L. van, Winter R. de, Kononova A.V. & Stein N. van (2022), Explainable AI for ship design analysis with AIS and static ship data. Vladimir N., Malencia S & Senjanovic. I. (Eds.), International Symposium on Practical Design of Ships and Other Floating Structures: PRADS 2022 Proceedings. 15th International Symposium on Practical design of ships and other floating structures 9 October 2022 - 13 October 2022. Zagreb, Croatia: Faculty of Mechanical Engineering and Naval Architecture. 1521-1535.
- Huang Q., Winter R. de, Stein N. van, Bäck T.H.W. & Kononova A.V. (2022), Multi-surrogate assisted efficient global optimization for discrete problems. Ishibuchi H., Kwoh C.K., Tan A.H., Srinivasan D, Miao C., Trivedi A. & Crockett K. (Eds.), 2022 IEEE Symposium Series on Computational Intelligence (SSCI). 2022 IEEE Symposium Series on Computational Intelligence (SSCI) 4 December 2022 - 7 December 2022: IEEE. 1650-1658.
- Vermetten D.L., Stein B. van, Kononova A.V. & Caraffini F. (2022), Analysis of structural bias in differential evolution configurations. In: Kumar B.V., Oliva D. & Suganthan P.N (Eds.), Differential evolution: from theory to practice. Studies in Computational Intelligence. Singapore: Springer. 1-22.
- De Jesus de Araujo Rios T., Stein B. van, Bäck T.H.W., Sendhoff B. & Menzel S. (2022), Multi-task shape optimization using a 3D point cloud autoencoder as unified representation, IEEE Transactions on Evolutionary Computation 26(2): 206-217.
- Hanse G., Winter R. de, Stein B. van & Bäck T.H.W. (2022), Optimally weighted ensembles for efficient multi-objective optimization. Nicosia G., Ojha V., Malfa E. La, Malfa G. La, Jansen G., Pardalos P.M., Giuffrida G. & Umeton R. (Eds.), Machine Learning, Optimization, and Data Science. LOD 2021. International Conference on Machine Learning, Optimization, and Data Science LOD 2021 4 October 2021 - 8 October 2021 no. 13163. Cham: Springer. 144-156.
- Kefalas M., Santiago Rojo J. de, Apostolidis A., Herik D. van den, Stein B. van & Bäck T.H.W. (2022), Explainable artificial intelligence for exhaust gas temperature of turbofan engines, Journal of Aerospace Information Systems 19(6): 447-454.
- Winter R. de, Bronkhorst P., Stein B. van & Bäck T.H.W. (2022), Constrained multi-objective optimization with a limited budget of function evaluations, Memetic Computing 14: 151-174.
- Winter R. de, Stein B. van & Bäck T.H.W. (2022), Multi-point acquisition function for constraint parallel efficient multi-objective optimization. Fieldsend E.J. (Ed.), GECCO '22: Proceedings of the genetic and evolutionary computation conference. GECCO '22: Genetic and Evolutionary Computation Conference 9 July 2022 - 13 July 2022. New York: Association for Computing Machinery . 511-519.
- Vermetten D.L., Caraffini F., Stein B. van & Kononova A.V. (2022), Using structural bias to analyse the behaviour of modular CMA-ES. Fieldsend J.E. (Ed.), GECCO '22: Proceedings of the genetic and evolutionary computation conference companion. GECCO '22: Genetic and Evolutionary Computation Conference 9 July 2022 - 13 July 2022. Boston: ACM. 1674-1682.
- Stein B. van, Raponi E., Sadeghi Z., Bouman N., Ham R.C.H.J. van & Bäck T.H.W. (2022), A comparison of global sensitivity analysis methods for explainable AI with an application in genomic prediction, IEEE Access 10: 103364-103381.
- Long F.X., Stein B. van, Frenzel M., Krause P., Gitterle M. & Bäck T.H.W. (2022), Learning the characteristics of engineering optimization problems with applications in automotive crash. Fieldsend J.E. (Ed.), GECCO '22: Proceedings of the genetic and evolutionary computation conference. GECCO '22: Genetic and Evolutionary Computation Conference 9 July 2022 - 13 July 2022: ACM. 1227-1236.
- Kefalas M., Stein B. van, Baratchi M., Apostolidis A. & Bäck T.H.W. (2022), End-to-end pipeline for uncertainty quantification and remaining useful life estimation: an application on aircraft engines. In: Do P. (Ed.) Proceedings of the European conference of the PHM Society 2022 . PHM Society European Conference no. 7: PHM Society. 245-260.
- Stein B. van & Raponi E. (2022), GSAreport: easy to use global sensitivity reporting, Journal of Open Source Software 7(78): 4721.
- Winter R. de, Stein B. van & Bäck T.H.W. (2021), SAMO-COBRA: a fast surrogate assisted constrained multi-objective optimization algorithm. Ishibuchi H., Zhang Q., Cheng R., Li K., Li H., Wang H. & Zhou A. (Eds.), Evolutionary Multi-Criterion Optimization. 11th International Conference on Evolutionary Multi-Criterion Optimization 28 March 2021 - 31 March 2021 no. 12654. Cham: Springer Nature Switzerland AG 2021. 270-282.
- Winter R. de, Stein B. van & Bäck T.H.W. (2021), Ship design performance and cost optimization with machine learning. Bertram V. (Ed.), COMPIT'21. 20th Conference on Computer and IT Applications in the Maritime Industries 8 August 2021 - 9 August 2021 no. 20. Mülheim : Hamburg University of Technology. 185-196.
- Ponse K., Kononova A.V., Loleyt M. & Stein B. van (2021), Using machine learning to detect rotational and local reflectional symmetries in 2D images, 2021 IEEE Symposium Series on Computational Intelligence (SSCI) Proceedings. IEEE Symposium Series on Computational Intelligence (SSCI 2021) 5 December 2021 - 7 December 2021. Orlando, Florida: IEEE. 01-08.
- Vermetten D.L., Stein B. van, Caraffini F., Minku L. & Kononova A.V. (2021), BIAS: a toolbox for benchmarking structural bias in the continuous domain. Institute of Electrical and Electronics Engineers (IEEE). [working paper].
- Stein B. van, Caraffini F. & Kononova A.V. (2021), Emergence of structural bias in differential evolution. Chicano F. (Ed.), Proceedings of the Genetic and Evolutionary Computation Conference Companion. GECCO '21: Genetic and Evolutionary Computation Conference 10 July 2021 - 14 July 2021: ACM. 1234-1242.
- Zeiser A.Z., Stein B van & Bäck T.H.W. (2021), Requirements towards optimizing analytics in industrial processes, Procedia Computer Science 184: 597-605.
- deJesus de Araujo Rios T., Stein B. van Wollstadt P., Bäck T.H.W., Sendhoff B. & Menzel S. (2021), Exploiting local geometric features in vehicle design optimization with 3D point cloud autoencoders. In: 2021 IEEE Congress on Evolutionary Computation (CEC).: IEEE. 514-521.
- Saha S., de Jesus de Araujo Rios T., Minku L.L., Stein B. van, Wollstadt P., Yao X., Bäck T.H.W., Sendhoff B. & Menzel S. (2021), Exploiting generative models for performance predictions of 3D car designs. IEEE Symposium Series on Computational Intelligence (SSCI 2021) 5 December 2021 - 7 December 2021: IEEE. 1-9.
- de Jesus de Araujo Rios T., Stein B. van, Bäck T.H.W., Sendhoff B. & Menzel S. (2021), Point2FFD: learning shape representations of simulation-ready 3D models for engineering design optimization, 2021 International Conference on 3D Vision (3DV). International Conference on 3D Vision (3DV) 1 December 2021 - 3 December 2021: IEEE. 1024-1033.
- Wang Y., Stein N. van, Bäck T.H.W. & Emmerich M.T.M. (2020), A tailored NSGA-III for multi-objective flexible job shop scheduling, 2020 IEEE Symposium Series on Computational Intelligence (SSCI). IEEE Symposium Series on Computational Intelligence (SSCI) 1 December 2020 - 4 December 2020: IEEE. 2746-2753.
- Stein N. van, Wang H. & Bäck T.H.W. (2020), Neural network design: learning from Neural Architecture Search, 2020 IEEE Symposium series on computational intelligence (SSCI). IEEE Symposium Series on Computational Intelligence (SSCI) 1 December 2020 - 4 December 2020: IEEE. 1341-1349.
- Rios T., Kong J., Stein B. van, Bäck T.H.W., Wollstadt P., Sendhoff B. & Menzel S. (2020), Back to meshes: optimal simulation-ready mesh prototypes for autoencoder-based 3D car point clouds, 2020 IEEE Symposium Series on Computational Intelligence (SSCI). IEEE Symposium Series on Computational Intelligence (SSCI) 1 December 2020 - 4 December 2020: IEEE. 942-949.
- Rios T., Stein B. van, Menzel S., Bäck T.H.W., Sendhoff B. & Wollstadt P. (2020), Feature visualization for 3d point cloud autoencoders, 2020 International Joint Conference on Neural Networks (IJCNN). 2020 International Joint Conference on Neural Networks (IJCNN) 19 July 2020 - 24 July 2020: IEEE. 1-9.
- Wang Y., Stein N. van, Bäck T.H.W. & Emmerich M.T.M. (2020), Improving NSGA-III for flexible job shop scheduling using automatic configuration, smart initialization and local search, GECCO '20: Proceedings of the 2020 genetic and evolutionary computation conference companion. Genetic and Evolutionary Computation Conference (GECCO 2020) 8 July 2020 - 12 July 2020. New York: ACM. 181-182.
- Stein B. van, Wang H., Kowalczyk W.J., Emmerich M.T.M. & Bäck T.H.W. (2019), Cluster-based Kriging approximation algorithms for complexity reduction, Applied Intelligence : .
- Stein B. van, Wang H. & Bäck T.H.W. (2019), Automatic Configuration of Deep Neural Networks with Parallel Efficient Global Optimization, 2019 International Joint Conference on Neural Networks (IJCNN). 2019 International Joint Conference on Neural Networks (IJCNN) 14 July 2019 - 19 July 2019. Budapest, Hungary, Hungary: IEEE. 1-7.
- Winter R. de, Stein B. van, Dijkman M. & Bäck T.H.W. (2019), Designing Ships Using Constrained Multi-objective Efficient Global Optimization. Nicosia G., Parda-los P., Giuffrida G., Umeton R. & Sciacca V. (Eds.), Machine Learning, Optimization, and Data Science LOD2018. The Fourth International Conference on Machine Learning, Optimization, and Data Science 13 September 2018 - 16 September 2018 no. 11331. Cham: Springer International Publishing. 191–203.
- Guo X., Stein B. van & Bäck T.H.W. (2019), A New Approach Towards the Combined Algorithm Selection and Hyper-parameter Optimization Problem, 2019 IEEE Symposium Series on Computational Intelligence (SSCI). 2019 IEEE Symposium Series on Computational Intelligence (SSCI) 6 December 2019 - 9 December 2019: IEEE. 2042-2049.
- Rios T., Sendhoff B., Menzel S., Bäck T.H.W. & Stein B. van (2019), On the Efficiency of a Point Cloud Autoencoder as a Geometric Representation for Shape Optimization, 2019 IEEE Symposium Series on Computational Intelligence (SSCI). 2019 IEEE Symposium Series on Computational Intelligence (SSCI) 6 December 2019 - 9 December 2019. Piscataway, New Jersey: Institute of Electrical and Electronics Engineers (IEEE). 791-798.
- Rios T., Wollstadt P., Stein B. van, Bäck T.H.W., Xu Z., Sendhoff B. & Menzel S. (2019), Scalability of Learning Tasks on 3D CAE Models Using Point Cloud Autoencoders, 2019 IEEE Symposium Series on Computational Intelligence (SSCI). 2019 IEEE Symposium Series on Computational Intelligence (SSCI) 6 December 2019 - 9 December 2019. Piscataway, New Jersey: Institute of Electrical and Electronics Engineers (IEEE). 1367-1374.
- Stein B. van (20 September 2018), Data driven modeling & optimization of industrial processes (Dissertatie. Leiden Institute of Advanced Computer Science (LIACS), Faculty of Science, Leiden University). Supervisor(s) and Co-supervisor(s): Bäck T.H.W., Kowalczyk W.J.
- Stein B. van, Wang H., Kowalczyk W.J. & Bäck T.H.W. (2018), A Novel Uncertainty Quantification Method for Efficient Global Optimization. Medina J., Ojeda-Aciego M., Verdegay J.L., Perfilieva I., Bouchon-Meunier B. & Yager R.R. (Eds.), Information Processing and Management of Uncertainty in Knowledge-Based Systems. Applications - 17th International Conference, IPMU 2018, Cádiz, Spain, June 11-15, 2018, Proceedings, Part III. IPMU 2018 : 17th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems 11 June 2018 - 15 June 2018 no. Communications in Computer and Information Science, volume 855. Cham: Springer. 480-491.
- Stein B. van, Wang H. & Bäck T.H.W. (2018), Automatic Configuration of Deep Neural Networks with EGO.
- Stein B. van, Leeuwen M. van & Bäck T. (2017), Local Subspace-Based Outlier Detection using Global Neighbourhoods, 2016 IEEE International Conference on Big Data (Big Data). : IEEE. 1136-1142.
- Stein B. van, Leeuwen M. van, Wang H., Purr S., Kreissl S., Meinhardt J. & Bäck T.H.W. (2017), Towards Data Driven Process Control in Manufacturing Car Body Parts, 2016 International Conference on Computational Science and Computational Intelligence CSCI. International Conference on Computational Science and Computational Intelligence (CSCI 2016) 15 December 2016 - 17 December 2016: IEEE CPS.
- Wang H., Stein B. van, Emmerich M.T.M. & Bäck T.H.W. (2017), Time complexity reduction in efficient global optimization using cluster kriging, GECCO '17 Proceedings of the Genetic and Evolutionary Computation Conference. Genetic and Evolutionary Computation Conference (GECCO 2017) 15 July 2017 - 19 July 2017. New York: ACM. 889-896.
- Rijn S.J. van, Wang H., Stein B. van & Bäck T.H.W. (2017), Algorithm configuration data mining for CMA evolution strategies, GECCO '17 Proceedings of the Genetic and Evolutionary Computation Conference. Genetic and Evolutionary Computation Conference (GECCO 2017) 15 July 2017 - 19 July 2017. New York: ACM. 737-744.
- Wang H., Stein B. van, Emmerich M.T.M. & Bäck T.H.W. (2017), A New Acquisition Function for Bayesian optimization based on the moment-generating function. Wang Hao, Stein B. van, Emmerich Michael T.M. & Bäck T.H.W. (Eds.), 2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC). 2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC) 5 October 2017 - 8 October 2017. Banff, AB, Canada: IEEE. 507-512.
- Spek T. van der, Stein B. van, Holst M. van der & Bäck T.H.W. (2017), A Multi-Method Simulation of a High-Frequency Bus Line, 2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITCS). IEEE 20th International Conference on Intelligent Transportation Systems 16 October 2017 - 19 October 2017: IEEE Xplore. 1-6.
- Stein B. van, Hao Wang, Kowalczyk W.J., Emmerich Michael T.M. & Bäck T.H.W. (2016), Fuzzy clustering for Optimally Weighted Cluster Kriging, 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). Fuzzy Systems, 2016 IEEE 24 June 2016 - 29 June 2016: IEEE. 978-1-5090-0627-4.
- Stein B. van, Kowalczyk W.J. & Bäck T.H.W. (2016), Analysis and Visualization of Missing Value Patterns. Carvalho J., Lesot M.J., Kaymak U., Vieira S., Bouchon-Meunier B. & Yager R. (Eds.), Information Processing and Management of Uncertainty in Knowledge-Based Systems. Information Processing and Management of Uncertainty in Knowledge-Based Systems 2016 20 June 2016 - 24 June 2016 no. 611. Switzerland: Springer International Publishing. 187-198.
- Stein B. van, Leeuwen M. van & Bäck T.H.W. (2016), Local Subspace-Based Outlier Detection using Global Neighbourhoods, 2016 IEEE International Conference on Big Data (Big Data). IEEE International Conference on Big Data 2016 5 December 2016 - 8 December 2016: IEEE Publishing.
- Stein B. van & Kowalczyk W.J. (2016), An Incremental Algorithm for Repairing Training Sets with Missing Values. Carvalho J.P., Lesot M., Kaymak U., Vieira S., Bouchon-Meunier B. & Yager R.R. (Eds.), Information Processing and Management of Uncertainty in Knowledge-Based Systems. Information Processing and Management of Uncertainty in Knowledge-Based Systems 2016 20 June 2016 - 24 June 2016 no. 611. Switzerland: Springer International Publishing. 175-186.
- Heiningen P. van, Stein B. van & Bäck T.H.W. (2016), A Framework for Evaluating Meta-models for Simulation-based Optimisation, 2016 IEEE Symposium Series on Computational Intelligence (SSCI). IEEE Symposium Series on Computational Intelligence (SSCI 2016) 6 December 2016 - 9 December 2016: IEEE.
- Stein B. van, Wang H., Kowalczyk W., Bäck T. & Emmerich M. (2015), Optimally Weighted Cluster Kriging for Big Data Regression. Fromont E., Bie T. de & Leeuwen M. van (Eds.), Advances in Intelligent Data Analysis XIV. 14th International Symposium, IDA 2015 22 October 2015 - 24 October 2015 no. LNCS 9385. Cham: Springer International Publishing. 310-321.
- Stein B. van, Emmerich Michael T.M. & Yang Z. (2013), Fitness Landscape Analysis of NK Landscapes and Vehicle Routing Problems by Expanded Barrier Trees, EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation IV. : Springer International Publishing. 75-89.
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