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The Machine Learning Group at RPTU (formerly 'TU Kaiserslautern') was established in 2017. The group currently comprises professors, postdocs, PhD students, administrative / technical support staff and student assistants. The group is interested in theory and algorithms of statistical machine learning (especially deep learning) and its applications. Our research covers a broad range of topics and applications, where we try to unify theoretically proven approaches (e.g., based on learning theory) with recent advances (e.g., in deep learning or reinforcement learning). Topics we have been working on include unsupervised deep learning (particularly, anomaly detection), multi-modal learning, extreme classification, adversarial learning, explainable AI, and applications of ML in the life sciences, mechanical and chemical process engineering, and text analysis. Members of the group have received various awards, including the Google Most Influential Papers Award, the ICML and NIPS Best Reviewer Awards, the ANDEA Test-of-time Award, and the Emmy-Noether Career Award (DFG). The group contributes the community with helpful service. Members of the group have been reviewing for more than 50 conferences and 30 journals. They have been serving as associate editors for journals (TPAMI, JMLR, TNNLS) and area chairs of conferences (NeurIPS, ICLR, AAAI, AISTATS, ECML, ECAI). The group is committed to improving the diversity, equity, and inclusion in the field of ML. This is evidenced by the high percentage of women in the group, on all levels of academic qualification.
