Photo: Prof. Alexander Meyer, Head of the Institute for Artificial Intelligence in Medicine © DHZC | Sarah Paff
Alexander Meyer appointed Professor of Artificial Intelligence in Medicine
Berlin, November 13, 2025
Artificial intelligence (AI) will shape the healthcare of tomorrow. Even today, it plays an increasingly important role in many areas – from prevention and screening to diagnosis, therapy, and aftercare. Charité – Universitätsmedizin Berlin is now bringing these activities together in a newly founded institute – the Institute for Artificial Intelligence in Medicine (IKIM). Its aim is to reliably integrate AI solutions into healthcare, provide evidence-based proof of their benefits, and establish them in everyday clinical practice. The institute will be headed by Prof. Alexander Meyer, who will also hold the newly created professorship for AI in Medicine.
“In recent years, we have seen the challenges that AI projects face at the interface between research, clinical practice, and hospital operations. They often fail to achieve their goals – not because of poor algorithms, but because of a lack of structures, evidence, and trust,” says Prof. Alexander Meyer. “The IKIM is the answer to this: We bring data scientists directly into clinics, research and develop AI agents for routine use, and build a systematic evidence base for medical AI not only in the lab, but in real-world clinical settings. Our goal is measurably better care – this also means production-ready systems that relieve the burden on hospital staff and help patients,” emphasizes the institute director.
Prof. Heyo K. Kroemer, CEO of Charité, adds: “The transformative potential of artificial intelligence for the medicine of the future is enormous: Processes are being fundamentally redesigned, diagnoses accelerated, and therapies made more precise. With the new institute, we are sending a clear signal that technological innovations can be responsibly integrated into patient-centered care. This will allow us to ensure the highest quality of treatment and a sustainable healthcare infrastructure in the future.”
From basic research to patient care
The newly founded institute systematically integrates computer science with medicine and basic sciences, building on its already well-established collaboration with the Berlin Institute for the Foundations of Learning and Data (BIFOLD). Together, they develop new AI methods, adapt them to medical questions, and then implement them in clinical practice. Data scientists will become integral members of clinical teams—as commonplace as their colleagues in biochemistry and biology are today.
The IKIM’s key areas of focus are:
Application-oriented development: The institute researches and develops AI systems for patient care, hospital management, and medical research. The focus is on agent-based solutions for automating knowledge-based processes, as well as the development and testing of large AI models for intensive care and preventive medicine.
Evidence-based implementation: The introduction of AI applications in hospitals is scientifically supported by clinical trials. The IKIM assesses efficacy and safety, thereby creating the foundation for responsible use in patient care.
Explainable AI: The institute researches methods that make AI decisions comprehensible for physicians. This transparency is crucial for building trust in AI systems and simultaneously fulfills regulatory requirements.
Transfer and Teaching: A service unit advises researchers and clinicians on AI projects. The institute also provides impetus for new curricula and continuing education programs to firmly establish AI competencies in medical education and training, as well as in corporate training.
New Projects for the Medicine of the Future
In addition to leading the institute, Alexander Meyer will also assume the professorship for Artificial Intelligence in Medicine. He brings many years of experience in AI projects and has initiated important digitization projects at Charité and the German Heart Center of Charité (DHZC) in recent years: from systems for the real-time prediction of postoperative complications during intensive care monitoring to current projects on AI-supported medical documentation and the preventive use of health data while driving using AI. As Chief Medical Information Officer of the DHZC, he continues to drive forward the digital transformation, real-time analytics and operational excellence of the DHZC – including in the new building project.
Building on these experiences, Alexander Meyer is planning new projects to prepare Charité for the future of medicine. He and his team aim to develop an AI strategy for Charité and establish the necessary structures for the practical application of AI. A key element of this is the digital model hospital currently being developed at the DHZC (German Heart Center Berlin), which will serve as a testing ground for innovations.
BIFOLD-Charité Professorship for Machine Learning
Alexander Meyer is supported by Prof. Grégoire Montavon, who was recently appointed to the first BIFOLD-Charité Professorship for Machine Learning in Medicine. His research group, “Explainable Machine Learning in Medicine,” will be based at the IKIM (Institute for Clinical Informatics and Management). A particular focus of his research is the development of new approaches in the field of explainable AI that can be integrated into modern machine learning (ML) models for medical diagnostics and research.
The Institute for Artificial Intelligence in Medicine is supported by the Berlin Institute for the Foundations of Learning and Data at TU Berlin (BIFOLD), where Alexander Meyer has been a Principal Investigator since 2018. BIFOLD has collaborated successfully with Charité for many years – for example, on projects such as the application of AI in patient monitoring, pathology, data processing, and also within the framework of projects on so-called Explainable AI (XAI).
Other key funding providers are the German Heart Center Foundation and the Charité Foundation, which are financially supporting the newly established W3 professorship for AI in Medicine. The German Heart Center Foundation aims to pave the way for intelligent, data-driven patient care in the new DHZC building with its funding. The Charité Foundation is supporting the appointment through a recruiting grant.
Brief CV of Prof. Alexander Meyer
Alexander Meyer has been a W3 Professor of Artificial Intelligence in Medicine at Charité and the German Heart Center Berlin (DHZC) since May 1, 2025, and is the Founding Director of the Institute for Artificial Intelligence in Medicine (IKIM). As a scholarship recipient of the German National Academic Foundation, he studied medicine in Frankfurt am Main and conducted research at Rockefeller University in New York from 2010 to 2011. After receiving his doctorate in Leipzig in 2014, he joined the former German Heart Center Berlin (DHZB, now DHZC) in 2015, where he continues to work. As a participant in the BIH Clinician-Scientist Program, he combined his specialist training in cardiac surgery at the DHZC with AI research. Within the BIH Digital Health Accelerator, he developed AI-based medical technology, which he then brought into clinical application through a spin-off company. In 2020, he completed his habilitation in Berlin and was appointed to the W2 professorship “Clinical Applications of AI and Data Science” at Charité. Since 2023, he has been Chief Medical Information Officer (CMIO) at the DHZC, where he is strategically responsible for digital transformation and AI integration. He is a board-certified cardiac surgeon with additional qualifications in medical informatics at the DHZC.
Brief CV of Prof. Grégoire Montavon
Grégoire Montavon, Professor of Machine Learning in Medicine, is also part of the management team of the Institute for Artificial Intelligence at Charité. He received his Master’s degree in Communication Systems from the École Polytechnique Fédérale de Lausanne in 2009 and his PhD in Machine Learning from the Technical University of Berlin in 2013. For several years, he has been a visiting professor at the Free University of Berlin and head of a research group at BIFOLD. Together with his colleagues, he developed the Layer-Wise Relevance Propagation method, which explains the predictions of popular machine learning models such as deep neural networks.