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Dr. Maria Kalweit (Hügle)

mariakalweit.jpg

 

Postdoc

Institut für Informatik
Albert-Ludwigs-Universität
Freiburg Georges-Koehler-Allee 201, Room 00-019
79110 Freiburg im Breisgau

E-mail:  Email Maria

 

 

 

Preprints

  • Mansour Alyahyay, Gabriel Kalweit, Maria Kalweit, Golan Karvat, Julian Ammer, Artur Schneider, Ahmed Adzemovic, Andreas Vlachos, Joschka Boedecker and Ilka Diester. Mechanisms of Premotor-Motor Cortex Interactions during Goal Directed Behavior. 2023. biorxiv
  • Jens Rahnfeld, Mehdi Naouar, Gabriel Kalweit, Joschka Boedecker, Estelle Dubruc and Maria Kalweit. A Comparative Study of Explainability Methods for Whole Slide Classification of Lymph Node Metastases using Vision Transformers. 2024. medrxiv
  • Yannick Vogt, Mehdi Naouar, Maria Kalweit, Cornelius Miething, Justus Duyster, Joschka Boedecker and Gabriel Kalweit. BetterBodies: Reinforcement Learning guided Diffusion for Antibody Sequence Design. arxiv

Publications

2024

  • Marieke Wesselkamp, Niklas Moser, Maria Kalweit, Joschka Boedecker, Carsten F. Dormann. Process-informed neural networks: a hybrid modelling approach to improve predictive performance and inference of neural networks in ecology and beyond. Accepted at Ecology Letters.
  • Paul Schmidt-Barbo, Gabriel Kalweit, Mehdi Naouar, Lisa Paschold, Edith Willscher, Christoph Schultheiss, Bruno Markl, Stefan Dirnhofer, Alexandar Tzankov, Mascha Binder und Maria Kalweit. Detection of disease-specific signatures in B cell repertoires of lymphomas using machine learning. In PLOS Computational Biology.
  • Maria Kalweit and Gabriel Kalweit. Warum wir neu lernen müssen, mit Maschinen zu sprechen – eine Momentaufnahme der Generativen KI im Januar 2024. In Ordnung der Wissenschaft. web
  • Gabriel Kalweit, Anusha Klett, Mehdi Naouar, Jens Rahnfeld, Yannick Vogt, Diana Laura Infante Ramirez, Rebecca Berger, Jesus Duque Afonso, Tanja Nicole Hartmann, Marie Follo, Michael Luebbert, Roland Mertelsmann, Evelyn Ullrich, Joschka Boedecker and Maria Kalweit. Unsupervised Feature Extraction from a Foundation Model Zoo for Cell Similarity Search in Oncological Microscopy Across Devices. Accepted at the ICML 2024 Workshop on Foundation Models in the Wild.
  • Hao Zhu, Brice De La Crompe, Gabriel Kalweit, Artur Schneider, Maria Kalweit, Ilka Diester and Joschka Boedecker. Multi-intention Inverse Q-learning for Interpretable Behavior Representation. TMLR, 2024. web

 

2023

  • Maria Kalweit, Andrea Burden, Joschka Boedecker, Thomas Hügle and Theresa Burkard. Patient groups in Rheumatoid arthritis identified by deep learning respond differently to biologic or targeted synthetic DMARDs. PLoS Computational Biology, 2023. web
  • Gabriel Kalweit, Maria Kalweit, Ignacio Mastroleo, Joschka Bödecker und Roland Mertelsmann. Künstliche Intelligenz in der Krebstherapie. Ordnung der Wissenschaft, 2022. web
  • Mehdi Naouar, Gabriel Kalweit, Ignacio Mastroleo, Philipp Poxleitner, Marc Metzger, Joschka Boedecker and Maria Kalweit. Robust Tumor Detection from Coarse Annotations via Multi-Magnification Ensembles. Poster at Digital Oncology, Hannover 2023. arxiv
  • Mehdi Naouar, Gabriel Kalweit, Anusha Klett, Yannick Vogt, Paula Silvestrini, Diana Infante, Roland Mertelsmann, Joschka Boedecker and Maria Kalweit. CellMixer: Annotation-free Semantic Cell Segmentation of Heterogeneous Cell Populations. NeurIPS 2023 Workshop on Medical Imaging. arxiv
  • Yannick Vogt, Mehdi Naouar, Maria Kalweit, Cornelius Miething, Justus Duyster, Roland Mertelsmann, Gabriel Kalweit and Joschka Boedecker. Stable Online and Offline Reinforcement Learning for Antibody CDRH3 Design. NeurIPS 2023 Workshop on Machine Learning in Structural Biology. arxiv

2022

  • Maria Kalweit, Gabriel Kalweit, Moritz Werling and Joschka Boedecker. Deep Surrogate Q-Learning for Autonomous Driving. ICRA 2022.
  • Gabriel Kalweit, Maria Kalweit, Joschka Boedecker. Robust and Data-efficient Q-learning by Composite Value-estimation. TMLR 2022.
  • Thomas Hügle, Leo Caratsch, Matteo Caorsi, Jules Maglione, Alexandre Dumusc, Diana Dan, Marc Blanchard, Gabriel Kalweit and Maria Kalweit. Automated Recognition and Monitoring of Dorsal Finger Folds by a Convolutional Neural Network as a Potential Digital Biomarker for Joint Swelling in Patients with Rheumatoid Arthritis. Digital Biomarkers, 2022.

2021

  • Branka Mirchevska, Maria Hügle, Gabriel Kalweit, Moritz Werling, Joschka Boedecker. Amortized Q-learning with Model-based Action Proposals for Autonomous Driving on Highways. Accepted at ICRA 2021. arxiv Video
  • Maria Hügle, Ulrich A Walker, Axel Finckh, Ruediger Mueller, Gabriel Kalweit, Almut Scherer, Joschka Boedecker, Thomas Hügle. Personalized Prediction of Disease Activity in Patients with Rheumatoid Arthritis Using an Adaptive Deep Neural Network. PLOS ONE. web medrxiv
  • Maria Kalweit, Gabriel Kalweit and Joschka Boedecker. AnyNets: Adaptive Deep Neural Networks for Medical Data with Missing Values. IJCAI 2021 Workshop on Artificial Intelligence for Function, Disability, and Health. web
  • Maria Kalweit, Gabriel Kalweit, Moritz Werling and Joschka Boedecker. Deep Surrogate Q-Learning for Autonomous Driving. IJCAI 2021 Workshop on Artificial Intelligence for Autonomous Driving. web video
  • Gabriel Kalweit, Maria Kalweit, Mansour Alyahyay, Zoe Jaeckel, Florian Steenbergen, Stefanie Hardung, Ilka Diester and Joschka Boedecker. NeuRL: Closed-form Inverse Reinforcement Learning for Neural Decoding.  ICML 2021 Workshop on Computational Biology. web
  • Gabriel Kalweit, Maria Huegle, Moritz Werling and Joschka Boedecker. Q-learning with Long-term Action-space Shaping to Model Complex Behavior for Autonomous Lane Changes. Accepted at IROS 2021.
  • Hügle T, Kalweit M. Artificial intelligence-supported treatment in rheumatology: Principles, current situation and perspectives. Zeitschrift fur Rheumatologie. 2021

 

2020

  • Gabriel Kalweit*, Maria Huegle*, Moritz Werling and Joschka Boedecker. Deep Inverse Q-learning with Constraints (Accepted at NeurIPS 2020). arxiv Video Project Page
  • Maria Huegle, Gabriel Kalweit, Moritz Werling and Joschka Boedecker. Dynamic Interaction-Aware Scene Understanding for Reinforcement Learning in Autonomous Driving. In Proc. of the IEEE International Conference on Robotics and Automation (ICRA, 2020). website arxiv Project Page
  • Maria Hügle, Gabriel Kalweit, Thomas Hügle and Joschka Boedecker. A Dynamic Deep Neural Network For Multimodal Clinical Data Analysis. AAAI 2020 Workshop on Health Intelligence. Explainable AI in Healthcare and Medicine. Studies in Computational Intelligence, Springer (2020). web arxiv Project Page
  • Maria Hügle, Patrick Omoumi, Jaap van Laar, Joschka Boedecker and Thomas Hügle. Applied Machine Learning and Artificial Intelligence in Rheumatology. Rheumatology Advances in Practice (2020). web

 

2019

  • Maria Huegle*, Gabriel Kalweit*, Branka Mirchevska, Moritz Werling and Joschka Boedecker. Dynamic Input for Deep Reinforcement Learning in Autonomous Driving (IROS 2019). arxiv Project Page
  • Maria Hügle, Joschka Boedecker and Thomas Hügle. Clinical Event-based Adaptive Deep Learning for the Prediction of Disease Progression in Rheumatoid Arthritis (Abstract and poster at Frontier of AI-Assisted Care Scientific Symposium, Stanford University, 2019).
  • Maria Hügle, Gabriel Kalweit, Moritz Werling, and Joschka Boedecker. Learning Dynamic Representations for Deep Reinforcement Learning in Autonomous Driving (Extended abstract at RSS 2019 Workshop on Scene and Situation Understanding for Autonomous Driving). extended abstract  poster
  • Gabriel Kalweit, Maria Huegle and Joschka Boedecker. Composite Q-Learning. Extended abstract at RSS 2019 Workshop on Combining Learning and Reasoning – Towards Human-Level Robot Intelligence. pdf

 

2018

  • Maria Hügle, Simon Heller, Manuel Watter, Manuel Blum, Farrokh Manzouri, Matthias Dümpelmann, Andreas Schulze-Bonhage, Peter Woias, Joschka Boedecker. Early Seizure Detection with an Energy-Efficient Convolutional Neural Network on an Implantable Microcontroller (IJCNN 2018, won the "Best Paper Award"). web Project Page
  • Simon Heller, Maria Hügle, Iman Nematollahi, Farrokh Manzouri, Matthias Dümpelmann, Andreas Schulze-Bonhage, Joschka Boedecker, Peter Woias. Hardware Implementation of a Performance and Energy-Optimized Convolutional Neural Network for Seizure Detection (EMBC 2018). video

 

2016

  • Molteni P, Hügle T, Hügle M, Nüesch C, Mündermann A. Reduction in ulnar pressure distribution when walking with forearm crutches with a novel cuff design: Cross-sectional intervention study on the biomechanical efficacy of an ulnar recess (2016).

 

Patents

  • Maria Huegle, Gabriel Kalweit, Branka Mirchevska, Moritz Werling and Joschka Boedecker. (EP3730369A1) Selecting a Motion Action for an Automated Vehicle Considering a Variable Number of Other Road Users. web
  • Moritz Werling, Branka Mirchevska, Joschka Bödecker, Maria Hügle and Gabriel Kalweit. (10 2020 106 816.6) Steuerung eines automatisierten Kraftfahrzeugs. web
  • Moritz Werling, Gabriel Kalweit, Maria Hügle and Joschka Bödecker. (10 2020 121 150.3) Trainieren eines Reinforcement Learning Agenten zur Steuerung eines autonomen Systems. web
  • Joschka Bödecker, Maria Hügle, Gabriel Kalweit and Moritz Werling. (WO002022033746A1) Training a Reinforcement Learning Agent to Control an Autonomous System. web
  • Joschka Boedecker, Maria Huegle, Gabriel Kalweit, Moritz Werling. (US 2024/0037447 A1) Training a Reinforcement Learning Agent to Control an Autonomous System. web

 

Honors and Awards

  • Gips-Schüle-Nachwuchspreis in der Kategorie Technikwissenschaften, 2024
  • Wolfgang-Gentner-Nachwuchsförderpreis, Universität Freiburg, 2023
  • Best Paper Award, IJCNN 2018

Academic Activities

  • Volunteer: RSS 2019 web
  • Reviewer: NeurIPS, IROS, ICRA, L4DC 
  • GirlsDay Workshops
  • KITE mentoring

  • Role Model (Technik, Frauen, Freiburg), Vorbild der Technischen Fakultät

 

Teaching

  • WS 2024/2025 Seminar on Machine Learning in Health website
  • WS 2023/2024 Seminar on Machine Learning in Health website
  • WS 2020/2021 Reinforcement Learning website
  • WS 2019/2020 Reinforccement Learning website
  • SS 2019 Deep Learning Lab website
  • WS 2018/2019 Deep Learning Lab website
  • SS 2018 Hierarchical Reinforcement Learning Seminar website
  • WS 2017/2018 Deep Learning Lab website

 

Students (Co-)Supervised

  • Kerstin Ohler and Emmanuel Hofmann (Cell Tracking and Apoptosis Prediction, Master's project, together with Gabriel Kalweit)
  • Ralvi Isufaj (Early seizure detection with unsupervised learning, Master's Thesis)
  • Claas Bollen (Machine Learning for Disease Progression Prediction in Rheumatoid Arthritis, Master's Thesis)
  • Jan Günthor (Unsupervised and semi-supervised detection of underlying data structures in medical records, Master's Thesis)
  • Alex Rose (Optimising for Unsupervised Skill Discovery, Master's Thesis, together with Gabriel Kalweit)
  • Ahmed Abdelhadi, Sara Al-Rawi (Safe Reinforcement Learning with hybrid Action-spaces, Master's Project, together with Gabriel Kalweit)
  • Marieke Wesselkamp (Process-guided Transfer Learning with sparse Data, Master's Thesis)
  • Ashwin Raaghav (Behavioral modeling of Rats using Inverse Reinforcement Learning, Master's Project, together with Gabriel Kalweit)
  • Tanyu Tanev (Stable clustering and visualization of medical data, Master's Project)
  • Mehdi Naouar (Multi-magnification Classifier Ensemble for the Classification of Whole Slide Images, Master's Thesis, together with Gabriel Kalweit)
  • Jens Rahnfeld (Enhancing Interpretability of ViT Attention in Histopathology, Master's project, together with Gabriel Kalweit and Mehdi Naouar)
  • Matthias Eberle (Leveraging vision features from segment anything and DINOv2 for cell classifcation, together with Mehdi Naouar and Gabriel Kalweit)