CARS Domain-Wall Analysis in single-crystalline Lithium Niobate
S. Reitzig, F. Hempel, M. Rüsing, L.M. Eng, in: OSA Nonlinear Optics 2021, Optica Publishing Group, 2022.

Second-harmonic microscopy in optically confining nanostructures
Z.H. Amber, B. Kirbus, M. Rüsing, L.M. Eng, in: OSA Nonlinear Optics 2021, Optica Publishing Group, 2022.

Broadband Coherent Anti-Stokes Raman Scattering on Solid State Systems
F. Hempel, S. Reitzig, M. Rüsing, L.M. Eng, in: OSA Nonlinear Optics 2021, Optica Publishing Group, 2022.

HPO x ELA: Investigating Hyperparameter Optimization Landscapes by Means of Exploratory Landscape Analysis
L. Schneider, L. Schäpermeier, R.P. Prager, B. Bischl, H. Trautmann, P. Kerschke, in: G. Rudolph, A.V. Kononova, H. Aguirre, P. Kerschke, G. Ochoa, T. Tusar (Eds.), Parallel Problem Solving from Nature — PPSN XVII, Springer International Publishing, Cham, 2022, pp. 575–589.

A Collection of Deep Learning-based Feature-Free Approaches for Characterizing Single-Objective Continuous Fitness Landscapes
M.V. Seiler, R.P. Prager, P. Kerschke, H. Trautmann, in: Proceedings of the Genetic and Evolutionary Computation Conference, Association for Computing Machinery, New York, NY, USA, 2022, pp. 657–665.

Automated Algorithm Selection in Single-Objective Continuous Optimization: A Comparative Study of Deep Learning and Landscape Analysis Methods
R.P. Prager, M.V. Seiler, H. Trautmann, P. Kerschke, in: G. Rudolph, A.V. Kononova, H. Aguirre, P. Kerschke, G. Ochoa, T. Tusar (Eds.), Parallel Problem Solving from Nature — PPSN XVII, Springer International Publishing, Cham, 2022, pp. 3–17.

Artificial Social Media Campaign Creation for Benchmarking and Challenging Detection Approaches
J.S. Pohl, D. Assenmacher, M.V. Seiler, H. Trautmann, C. Grimme, in:  for the Advancement of Artificial Intelligence (AAAI) Association (Ed.), Workshop Proceedings of the 16$^th$ International Conference on Web and Social Media (ICWSM), AAAI Press, Palo Alto, CA, USA, 2022, pp. 1–10.

On the Potential of Automated Algorithm Configuration on Multi-Modal Multi-Objective Optimization Problems
J. Rook, H. Trautmann, J. Bossek, C. Grimme, in: J. Fieldsend, M. Wagner (Eds.), Proceedings of the Genetic and Evolutionary Computation Conference Companion, Association for Computing Machinery, New York, NY, USA, 2022, pp. 356–359–356–359.

Process-Oriented Stream Classification Pipeline: A Literature Review
L. Clever, J.S. Pohl, J. Bossek, P. Kerschke, H. Trautmann, Applied Sciences 12 (2022) 1–44.

The objective that freed me: a multi-objective local search approach for continuous single-objective optimization
P. Aspar, V. Steinhoff, L. Schäpermeier, P. Kerschke, H. Trautmann, C. Grimme, Natural Computing 1 (2022) 1–15.

BBE: Basin-Based Evaluation of Multimodal Multi-objective Optimization Problems
J. Heins, J. Rook, L. Schäpermeier, P. Kerschke, J. Bossek, H. Trautmann, in: G. Rudolph, A. Kononova, H. Aguirre, P. Kerschke, G. Ochoa, T. Tusar (Eds.), Parallel Problem Solving from Nature — PPSN XVII, Springer International Publishing, Cham, 2022, pp. 192–206.

Das Stützpunktsystem im paralympischen Leistungssport. Eine empirische Studie unter Berücksichtigung der Perspektive von Para-Athletinnen und -Athleten sowie des Stützpunktpersonals. 
S. Radtke, M.P. Freier, Das Stützpunktsystem im paralympischen Leistungssport. Eine empirische Studie unter Berücksichtigung der Perspektive von Para-Athletinnen und -Athleten sowie des Stützpunktpersonals. , Sportverlag Strauß, 2022.

Das Stützpunktsystem im paralympischen Leistungssport. Eine empirische Studie unter Berücksichtigung der Perspektive von Para-Athletinnen und -Athleten sowie des Stützpunktpersonals. 
S. Radtke, M.P. Freier, Das Stützpunktsystem im paralympischen Leistungssport. Eine empirische Studie unter Berücksichtigung der Perspektive von Para-Athletinnen und -Athleten sowie des Stützpunktpersonals. , Sportverlag Strauß, 2022.

 An approach to teaching data science in middle school
S. Podworny, Y. Fleischer, in: U.T. Jankvist, R. Elicer, A. Clark-Wilson, H.-G. Weigand, M. Thomson (Eds.), Proceedings of the 15th International Conference on Technology in Mathematics Teaching (ICTMT 15), Danish School of Education, Aarhus, Denmark, 2022, pp. 308–315.

 Teaching machine learning with decision trees in middle school using CODAP
Y. Fleischer, S. Podworny, in: U.T. Jankvist, R. Elicer, A. Clark-Wilson, H.-G. Weigand, M. Thomson (Eds.), Proceedings of the 15th International Conference on Technology in Mathematics Teaching (ICTMT 15), Danish School of Education, Aarhus, Denmark, 2022, pp. 280–281.

A PLACE FOR A DATA SCIENCE PROJECT IN SCHOOL: BETWEEN STATISTICS AND EPISTEMIC PROGRAMMING
S. PODWORNY, S. HÜSING, C. SCHULTE, STATISTICS EDUCATION RESEARCH JOURNAL 21 (2022).

Grade 6 Students’ Perception and Use of Data-Based Decision Trees
S. Podworny, Y. Fleischer, S. Hüsing, in: Bridging the Gap: Empowering and Educating Today’s Learners in Statistics. Proceedings of the Eleventh International Conference on Teaching Statistics, International Association for Statistical Education, 2022.

Jupyter Notebooks for Teaching, Learning, and Doing Data Science
Y. Fleischer, S. Hüsing, R. Biehler, S. Podworny, C. Schulte, in: Bridging the Gap: Empowering and Educating Today’s Learners in Statistics. Proceedings of the Eleventh International Conference on Teaching Statistics, International Association for Statistical Education, 2022.

An example of rich, real and multivariate survey data for use in school
S. Podworny, Y. Fleischer, D. Stroop, R. Biehler, in: 2022.

Vokabeln lernen im Schlaf? Statistische Testprozeduren verstehen
S. Podworny, mathematik lehren 232 (2022) 36–40.