Dr. Marisa Mohr

About Me

I am Mathematician, Teamlead and Head of Research & Development at inovex, working in the field of data, mathematical modelling or artificial intelligence. I am supporting girls and women in STEM, whereby the organisations European Women in Mathematics, CyberMentor and Initiative NAT are particularly important to me. I am co-organiser of the event series Women & Wine & Tech, taking place quarterly.

Publications

Here you find my blogposts as part of my work at inovex. Most of the following publications were written as part of my doctorate at the Institute of Information Systems at the University of Lübeck on the topic of "Time Series Representation Learning".

2023

  • Katharina Post, Marisa Mohr, Max Koeppel, Astrid Laubenheimer: Improving Multiclass Classification of Cardiac Arrhythmias with Photoplethysmography using an Ensemble Approach of Binary Classifiers, will be published in: Proceedings of the Collaborative European Research Conference 2023

2022

  • Marisa Mohr: Learning from Ups and Downs: Multivariate Ordinal Pattern Representations for Time Series, in: University of Lübeck, 2022, September, PhD thesis
  • Marisa Mohr, Karsten Keller: Aus den Auf- und Abwärtsbewegungen einer Zeitreihe lernen, in: Mitteilungen der Deutschen Mathematiker-Vereinigung, 2022, Vol.30, (1), p.25-29
  • Marisa Mohr: Unternehmensübergreifend Daten analysieren und gemeinsam Wissen generieren, in: Tobias Bux und Armin Lechler (Hrsg.): KOSMoS – Kollaborative Smart Contracting Plattform für digitale Wertschöpfungsnetze, VDI Verlag, 2022, S. 62–76.
  • Florian Wilhelm, Marisa Mohr, Lien Michiels: An Interpretable Model for Collaborative Filtering Using an Extended Latent Dirichlet Allocation Approach, in: The International FLAIRS Conference Proceedings, 2022, Vol.35
  • Marisa Mohr, Frederik Timm: Vom Datenaustausch mit der Konkurrenz profitieren, in: t3n Magazin Nr. 68 (Print), 2022

2021

  • Marisa Mohr, Ralf Möller: Ordering Principle Components of Multivariate Fractional Brownian Motion for Solving Inverse Problems, in: Proceedings of the Asia-Pacific Signal and Information Processing Association Annual Summit and Conference 2021 (APSIPA-ASC), 2021, IEEE
  • Finke, Nils, Möller, Ralf, Mohr, Marisa: Multivariate Ordinal Patterns for Symmetry Approximation in Dynamic Probabilistic Relational Models, in: AI 2021: Advances in Artificial Intelligence, 2022, Long, Guodong, Yu, Xinghuo, Wang, Sen (Ed.), Springer International Publishing, p.543-555
  • Nils Finke, Marisa Mohr: A Priori Approximation of Symmetries in Probabilistic Dynamic Relational Models, in: KI 2021: Advances in Artificial Intelligence, 2021, Stefan Edelkamp, Ralf Möller, Elmar Rueckert (Ed.), Springer International Publishing, Cham, p.309-323
  • Marisa Mohr, Ralf Möller: A Summary of Canonical Multivariate Permutation Entropies on Multivariate Fractional Brownian Motion, in: Advances in Science, Technology and Engineering Systems Journal, 2021, Vol.6, (5), p.107-124
  • Nils Finke, Marisa Mohr, Alexander Lontke, Marwin Zünfle, Samuel Kounev, Ralf Möller: Recommendations for Data-Driven Degradation Estimation with Case Studies from Manufacturing and Dry-Bulk Shipping, in: Research Challenges in Information Science - 15th International Conference, RCIS 2021, 2021, Samira Cherfi, Anna Perini, Selmin Nurcan (Ed.), Springer International Publishing, Lecture Notes in Business Information Processing, Vol.415, p.189-204
  • Marisa Mohr, Florian Wilhelm, Ralf Möller: On the Behaviour of Weighted Permutation Entropy on Fractional Brownian Motion in the Univariate and Multivariate Setting, in: The International FLAIRS Conference Proceedings, 2021, April, Vol.34
  • Marisa Mohr, Christian Becker, Ralf Möller, Matthias Richter: Towards Collaborative Predictive Maintenance Leveraging Private Cross-Company Data, in: INFORMATIK 2020, 2021, Ralf H. Reussner, Anne Koziolek, Robert Heinrich (Ed.), Gesellschaft für Informatik, Bonn, p.427-432
  • Tobias Bux, Jonas Groß, Constantin Lichti, Marisa Mohr: Projekt KOSMoS: Mit Blockchain transparent und firmenübergreifend warten, in: atp magazin 03/2021, Bd. 63, Nr.3, Vulkan-Verlag GmbH, 2021

2020

  • Christian Becker, Marisa Mohr: Federated Machine Learning: über Unternehmensgrenzen hinaus aus Produktionsdaten lernen, in: atp magazin 05/2020, Bd. 62, Nr.5, S.18-20, Vulkan-Verlag GmbH, 2020
  • Tobias Bux, Marisa Mohr: Blockchain-Lösungen für den produktionstechnischen Mittelstand, in: Prof. Dr.-Ing. Thomas Bauernhansl (Ed.): wt Werkstattstechnik online, Bd. 111, Nr. 4., S. 201-204, ISSN online: 1436-4980, VDI Fachmedien GmbH & Co., 2020
  • Marisa Mohr, Nils Finke, Ralf Möller: On the Behaviour of Permutation Entropy on Fractional Brownian Motion in a Multivariate Setting, in: Proceedings of the Asia-Pacific Signal and Information Processing Association Annual Summit and Conference 2020 (APSIPA-ASC), 2020, IEEE, p.189-196
  • Marisa Mohr, Florian Wilhelm, Mattis Hartwig, Ralf Möller, Karsten Keller: New Approaches in Ordinal Pattern Representations for Multivariate Time Series, in: Proceedings of the 33rd International Florida Artificial Intelligence Research Society Conference (FLAIRS-33), 2020, AAAI Press, North Miami Beach, Florida, USA, May 17-20, 2020, p.124-129
  • Mattis Hartwig, Marisa Mohr, Ralf Möller: Constructing Gaussian Processes for Probabilistic Graphical Models, in: Proceedings of the 33rd International Florida Artificial Intelligence Research Society Conference (FLAIRS-33), 2020, AAAI, North Miami Beach, Florida, USA, May 17-20, 2020, p.57-62
  • Lucas Baier, Marcel Hofmann, Niklas Kühl, Marisa Mohr, Gerhard Satzger: Handling Concept Drifts in Regression Problems – the Error Intersection Approach, in: Entwicklungen, Chancen und Herausforderungen der Digitalisierung: der 15. Internationalen Tagung Wirtschaftsinformatik, WI 2020, Potsdam, Germany, March 9-11, 2020. Zentrale Tracks, 2020, N. Gronau, M. Heine, H. Krasnova, K. Poustcchi (Ed.), GITO Verlag