Academic Education
- Master of Arts Philosophy, University of Münster
- Master of Arts Philosophy of Science, University of Münster
- PhD Computer Science, University of Münster
- Master of Science Chemistry, University of Münster
- Bachelor of Science Physics, University of Münster
- Bachelor of Science Chemistry, University of Münster
Publications
- Becker, M., Drees, D., Brückerhoff-Plückelmann, F., Schuck, C., Pernice, W., & Risse, B. (). Activation Functions in Non-Negative Neural Networks. doi: 10.1109/ACCESS.2025.3622408.
- Homberg, S. K.R., Modlich, M. L., Becker, M., Menke, J., Morris, G. M., Risse, B., & Koch, O. (). Interpreting Graph Neural Networks with Myerson Values for Cheminformatics Approaches. in Walter, S., Marcello, S., Ausra, S., Igor, V. T., Alessandro, E. P., Viktor, J., & Yoshua, B. (ed.), Artificial Neural Networks and Machine Learning - ICANN 2025 International Workshops and Special Sessions: Vol. 5. Artificial Neural Networks and Machine Learning. ICANN 2025 International Workshops and Special Sessions (pp. 232–234). Springer Nature. doi: 10.1007/978-3-032-04552-2.
- Becker, M., Altrock, F., & Risse, B. (). Momentum-SAM: Sharpness Aware Minimization without Computational Overhead. in Belgrave, D., Zhang, C., Montoya, L., Lin, H.-T., Pascanu, R., Koniusz, P., Ghassemi, M., & Chen, N. (ed.), Advances in Neural Information Processing Systems 39 (NeurIPS 2025) (pp. 1–8). Neural Information Processing Systems Foundation, Inc. (NeurIPS).
- Becker, M., Butz, M., Lemli, D., Schuck, C., & Risse, B. (). Learning Proposal Distributions in Simulated Annealing via Template Networks: A Case Study in Nanophotonic Inverse Design. in Antonacopoulos, A., Chaudhuri, S., Chellappa, R., Liu, C.-L., Bhattacharya, S., & Pal, U. (ed.), 27th International Conference ICPR 2024: Vol. 27. Pattern Recognition (pp. 188–202). Springer. doi: 10.1007/978-3-031-78186-5_13.
- Tertilt, H., Mensing, J., Becker, M., van der Wiel, W. G., Bobbert, P. A., & Heuer, A. (). Critical nonlinear aspects of hopping transport for reconfigurable logic in disordered dopant networks. Physical Review Applied, 22 (2). doi: 10.1103/PhysRevApplied.22.024063.
- Schulte, L., Butz, M., Becker, M., Risse, B., & Schuck, C. (). Accelerating Finite-Difference Frequency-Domain Simulations for Inverse Design Problems in Nanophotonics using Deep Learning. Journal of the Optical Society of America B, 41 (4), 1039–1046. doi: 10.1364/JOSAB.506159.
- Brückerhoff-Plückelmann, F., Borras, H., Klein, B., Varri, A., Becker, M., Dijkstra, J., Brückerhoff, M., Wright, CD., Salinga, M., Bhaskaran, H., Risse, B., Fröning, H., & Pernice, W. (). Probabilistic photonic computing with chaotic light. Nature Communications, 15 (1), 10445–10445. doi: 10.1038/s41467-024-54931-6.
- Becker, M., & Risse, B. (). Learned Random Label Predictions as a Neural Network Complexity Metric. Workshop on Scientific Methods for Understanding Deep Learning @NeurIPS , Vancouver.
- Wendland, D., Becker, M., Brückerhoff-Plückelmann, F., Bente, I., Busch, K., Risse, B., & Pernice, WH. (). Coherent dimension reduction with integrated photonic circuits exploiting tailored disorder. Journal of the Optical Society of America B, 40 (3), B35–B40.
- Butz, M., Leifhelm, A., Becker, M., Risse, B., & Schuck, C. (). A Universal Approach to Nanophotonic Inverse Design through Reinforcement Learning. in Group, O. P. (ed.), CLEO 2023, paper STh4G.3 (p. STh4G.3–STh4G.3). Optica. doi: 10.1364/CLEO_SI.2023.STh4G.3.
- Butz, M., Leifhelm, A., Becker, M., Risse, B., & Schuck, C. (). A Novel Approach to Nanophotonic Black-Box Optimization Through Reinforcement Learning. in DPG (ed.), Q 30 Nano-optics (p. 1–1). Deutsche Physikalische Gesellschaft.
- Brückerhoff-Plückelmann, F., Bente, I., Becker, M., Vollmar, N., Farmakidis, N., Lomonte, E., Lenzini, F., Wright, C. D., Bhaskaran, H., Salinga, M., Risse, B., & Pernice, W. HP. (). Event-driven adaptive optical neural network. Science advances, 9 (42), eadi9127. doi: 10.1126/sciadv.adi9127.
- Purk, M., Fujarski, M., Becker, M., Warnecke, T., & Varghese, J. (). Utilizing a tablet-based artificial intelligence system to assess movement disorders in a prospective study. Scientific Reports, 13 (1). doi: 10.1038/s41598-023-37388-3.
- Becker, M., Drees, D., Brückerhoff-Plückelmann, F., Schuck, C., Pernice, W., & Risse, B. (). Activation Functions in Non-Negative Neural Networks. Machine Learning and the Physical Sciences Workshop, NeurIPS, New Orleans.
- Becker, M., Riegelmeyer, J., Seyfried, M. D., Ravoo, B. J., Schuck, C., & Risse, B. (). Adaptive Photochemical Nonlinearities for Optical Neural Networks. Advanced Intelligent Systems, 5 (12). doi: 10.1002/aisy.202300229.
- Becker, M., Butz, M., Lemli, D., Schuck, C., & Risse, B. (). Combinatorial Optimization via Memory Metropolis: Template Networks for Proposal Distributions in Simulated Annealing applied to Nanophotonic Inverse Design. Neural Information Processing Systems (NeurIPS) Workshop on AI for Accelerated Materials Design (AI4Mat-2023), New Orleans.
- Riegelmeyer, J., Eich, A., Becker, M., Risse, B., & Schuck, C. (). Development of a nanophotonic nonlinear unit for optical artificial neural networks. in DPG (ed.), Q 31 Photonics I (pp. 8–9). Deutsche Physikalische Gesellschaft.
- Butz, M., Leifhelm, A., Becker, M., Risse, B., & Schuck, C. (). Inverse Design of Nanophotonic Devices based on Reinforcement Learning. in DPG (ed.), Q 38 Photonics II (p. 2–2). Deutsche Physikalische Gesellschaft.
- Tertilt, H., Bakker, J., Becker, M., de Wilde, B., Klanberg, I., Geurts, B. J., van der Wiel, W. G., Heuer, A., & Bobbert, P. A. (). Hopping-transport mechanism for reconfigurable logic in disordered dopant networks. Physical Review Applied, 17 (6), 064025. doi: 10.1103/PhysRevApplied.17.064025.
- Friedman, R., Khalid, S., Santamaría, CA., Arutyunova, E., Becker, M., Boyd, KJ., Christensen, M., Coimbra, JTS., Concilio, S., Daday, C., van, E. FJ., Fernandes, PA., Gräter, F., Hakobyan, D., Heuer, A., Karathanou, K., Keller, F., Lemieux, MJ., Marrink, SJ., May, ER., Mazumdar, A., Naftalin, R., Pickholz, M., Piotto, S., Pohl, P., Quinn, P., Ramos, MJ., Schiøtt, B., Sengupta, D., Sessa, L., Vanni, S., Zeppelin, T., Zoni, V., Bondar, A.-N., & Domene, C. (). Understanding Conformational Dynamics of Complex Lipid Mixtures Relevant to Biology. Journal of Membrane Biology, 251 (5), 609–631. doi: 10.1007/s00232-018-0050-y.