Collaborative Research Institute Intelligent Oncology

Collaborative Research Institute
Intelligent Oncology

Harness the power of modern Artificial Intelligence techniques for the fight against cancer.

We strive to create an open and creative research environment at the Intersection of Translational Oncology and Machine Learning for talents all across the globe at the heart of Freiburg, Germany.

Collaborative Research

Multidisciplinary offices and laboratories, regular project leader meetings, international state-of-the-art conferences

Research Core Facilities

The institute has three core areas: Wet Labs, AI and Philosophy

Experimental Research

Interaction of AI experts, clinical and experimental scientists in joint wet labs

The potential of AI to Control Cancer

Current Projects

PD Dr. Florian Scherer

Liquid Biopsy

Ultra-sensitive genotyping of circulating tumor DNA for noninvasive classification of brain cancers

Prof. Dr. Tanja Hartmann

Cell Migration

Development of a machine learning approach for leukemia cell-microenvironment interactions

CRIION

Prof. Dr. Rainer Claus

AI@AML

Using artificial intelligence to decipher and manipulate cellular growth patterns in acute myeloid leukemia

Prof. Dr. Mascha Binder

IMMUSIGN

Using machine learning and a living immune repository to detect disease-specific and anti-tumor immune signatures

ChemoAI

PROF. DR. MAXIMILIANO S. PEREZ

ChemoAI

AI-Enhanced Lab-on-a-Chip and real-time imaging for personalized drug selection in cancer treatment

Dr. Cornelius Miething

Antibody Design

Automated Antibody Design for Targeted Cellular Immunotherapy of Anaplastic Thyroid Cancer

Current Projects

  • W1 TT: CRIION Professur für Bioinformatik: Künstliche Intelligenz für die Onkologie-Forschung
    Start: Frühjahr 2025

  • W1: CRIION Professur für Liquid Biopsy — Neue Methoden der Probenaufbereitung
    Start: Frühjahr 2025
  • Artificial Intelligence for non-invasive brain cancer classification based on ctDNA mutational profiles, Freiburg
  • IMMUSIGN-Using machine learning and a living immune repository to detect disease-specific and anti-tumor immune signatures, Basel
  • AI-compatible platform for automated therapeutic target discovery to overcome acquired drug resistance in leukemia, Freiburg
  • Using artificial intelligence to decipher and manipulate cellular growth patterns in acute myeloid leukemia (AI@AML), Augsburg
  • Use of 3D Holotomographic Microscopy on Living Cells as a Novel Source of Data for Deep Learning Analysis, Freiburg
  • Development of artificial intelligence-driven tools based on cytomorphological analysis for diagnostic and outcome prediction of patients with acute hematological diseases, Freiburg

  • Microscopy based evaluation of drug response profiles in NPM1c acute myeloid leukemia, Zürich

  • DeepPanOme – Deep learning-driven adaptive dynamic therapy for PDAC based on the secreted metabolome, Furtwangen

  • AI?Sign: Artificial Intelligence Enabled Signature Detection in Multi?Analyte Liquid Biopsy Data, Freiburg

Completed Projects

  • Prof. Dr. Robert Huber

    AMLAMO

    Automated Machine Learning-Assisted Media Optimization,
    München

  • Prof. Dr. Joschka Bödecker / Prof. Dr. Marc Metzger

    Personalized Medicine

    Artificial intelligence augmented intraoperative real time histology,
    Freiburg

Current Publications

2025

  • Künstliche Intelligenz in der Krebstherapie. Gabriel Kalweit, Maria Kalweit, Ignacio Mastroleo, Joschka Bödecker und Roland Mertelsmann. Künstliche Intelligenz in Forschung, Lehre und Hochschule, edited by Manfred Löwisch, Thomas Würtenberger, Max-Emanuel Geis and Dirk Heckmann, Duncker & Humblot, 2025, pp. 425-434.
  • Warum wir neu lernen müssen, mit Maschinen zu sprechen – eine Momentaufnahme der Generativen Künstlichen Intelligenz im Januar 2024. Maria Kalweit und Gabriel Kalweit. Künstliche Intelligenz in Forschung, Lehre und Hochschule, edited by Manfred Löwisch, Thomas Würtenberger, Max-Emanuel Geis and Dirk Heckmann, Duncker & Humblot, 2025, pp. 111-127.
  • Salvage: Shapley-distribution Approximation Learning Via Attribution Guided Exploration for Explainable Image Classification. Mehdi Naouar, Hanne Raum, Jens Rahnfeld, Yannick Vogt, Joschka Boedecker, Gabriel Kalweit and Maria Kalweit. International Conference on Learning Representations (ICLR) 2025 read more
  • Deficiency of adenosine deaminase 2 skews adaptive immune repertoires towards specific sets of T and B cell receptors.
    Schultheiß C*, Schmidt-Barbo P*, Paschold L, Esperanzate C, Behn A, Mikolajczyk R, Kasnter D, Aksentijevich I, Binder M.
    J Allergy Clin Immunol. 2025
  • Oligoclonality of TRBC1 and TRBC2 in T cell lymphomas as mechanism of primary resistance to TRBC-directed CAR T cell therapies. Thiele* B, Schmidt-Barbo* P, Schultheiss C, Willscher E, Weber T, Binder M.
    Nature Communications 2025 Article number: 1104 2025
  • T cell receptor architecture and clonal tiding provide insight into the transformation trajectory of peripheral T cell lymphomas.
  • Willscher E*, Schultheiß C*, Paschold L, Schümann FL, Schmidt-Barbo P, Thiele B, Bauer M, Wickenhauser C, Weber T, Binder M.
    Haematologica. 2024 Aug 29. doi: 10.3324/haematol.2024.285395.
  • A20 haploinsufficiency disturbs immune homeostasis and drives the transformation of lymphocytes with permissive antigen receptors. Schultheiß C, Paschold L, Mohebiany AM, Escher M, Kattimani YM, Müller M, Schmidt-Barbo P, Mensa-Vilaró A, Aróstegui JI, Boursier G, de Moreuil C, Hautala T, Willscher E, Jonas H, Chinchuluun N, Grosser B, Märkl B, Klapper W, Oommen PT, Gössling K, Hoffmann K, Tiegs G, Czernilofsky F, Dietrich S, Freeman A, Schwartz DM, Waisman A, Aksentijevich I, Binder B.
    Science Adv. 2024 Aug 23;10(34):eadl3975.

2024

  • Unsupervised Feature Extraction from a Foundation Model Zoo for Cell Similarity Search in Oncological Microscopy Across Devices. 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. ICML 2024. Workshop on Foundation Models in the Wild. Web
  • A Comparative Study of Explainability Methods for Whole Slide Classification of Lymph Node Metastases using Vision Transformers. Jens Rahnfeld, Mehdi Naouar, Gabriel Kalweit, Joschka Boedecker, Estelle Dubruc, Maria Kalweit. Preprint
  • Detection of disease-specific signatures in B cell repertoires of lymphomas using machine learning. Paul Schmidt-Barbo, Gabriel Kalweit, Mehdi Naouar, Lisa Paschold, Edith Willscher, Christoph Schultheiss, Bruno Markl, Stefan Dirnhofer, Alexandar Tzankov, Mascha Binder und Maria Kalweit. PLOS Computational Biology, 2024. Web
  • Warum wir neu lernen müssen, mit Maschinen zu sprechen – eine Momentaufnahme der Generativen KI im Januar 2024. Maria Kalweit und Gabriel Kalweit. Web

2023

  • CellMixer: Annotation-free Semantic Cell Segmentation of Heterogeneous Cell Populations. Mehdi Naouar, Gabriel Kalweit, Anusha Klett, Yannick Vogt, Paula Silvestrini, Diana Infante, Roland Mertelsmann, Joschka Boedecker and Maria Kalweit. NeurIPS 2023 Workshop on Medical Imaging.
  • Stable Online and Offline Reinforcement Learning for Antibody CDRH3 Design. Yannick Vogt, Mehdi Naouar, Maria Kalweit, Cornelius Miething, Justus Duyster, Roland Mertelsmann, Gabriel Kalweit and Joschka Boedecker. NeurIPS 2023 Workshop on Machine Learning in Structural Biology.
  • Selection of phage-displayed antibodies with high affinity and specificity by electrophoresis in microfluidic devices. Anahí Sanluis-Verdes; Ana Peñaherrera; José L. Torán; Anahí Sanluis-Verdes; María A. Noriega; Betiana Lerner; Maximiliano Pérez; José M. Casasnovas. Wiley Online Library – Electrophoresis. Web
  • Socrates in the Machine: The “House Ethicist” in AI for Healthcare. Luis García Valiña, PhD; Paola Buedo, MD, MA; Timothy Daly, PhD. Journal of Radiology Nursing. Web
  • Robust Tumor Detection from Coarse Annotations via Multi-Magnification Ensembles. Mehdi Naouar, Gabriel Kalweit, Ignacio Mastroleo, Philipp Poxleitner, Marc Metzger, Joschka Boedecker and Maria Kalweit. Digital Oncology Conference (Oral). Web

2022

  • Künstliche Intelligenz in der Krebstherapie. Gabriel Kalweit, Maria Kalweit, Ignacio Mastrolo, Joschka Bödecker, Roland Mertelsmann.
    Ordnung in der Wissenschaft (Ausgabe 17-22). Web