Publications

Kusampudi, N.; Diehl, M.: Inverse design of dual-phase steel microstructures using generative machine learning model and Bayesian optimization. International Journal of Plasticity 171, 103776 (2023)

Saxena, A.; Polin, N.; Kusampudi, N.; Katnagallu, S.; Molina-Luna, L.; Gutfleisch, O.; Berkels, B.; Gault, B.; Neugebauer, J.; Freysoldt, C.: A Machine Learning Framework for Quantifying Chemical Segregation and Microstructural Features in Atom Probe Tomography Data. Microscopy and Microanalysis 29 (5), pp. 1658 - 1670 (2023)

Nascimento, A.; Roongta, S.; Diehl, M.; Beyerlein, I. J.: A machine learning model to predict yield surfaces from crystal plasticity simulations. International Journal of Plasticity 161, 103507 (2023)

Roters, F.; Diehl, M.; Eisenlohr, P.; Shanthraj, P.: DAMASK: the Düsseldorf Advanced MAterial Simulation Kit for studying multi-field crystal plasticity phenomena. Invited online seminar Harbin Institute of Technology, online , Shenzhen, China (2023)

Kusampudi, N.: Application of topological data analysis and sliding window embedding to analyze time series data from bird songs. Danish-Swedish summer school on TDA and spatial statistics, Aalborg, Sweden (2023)