Lecture Series: Medical Information Sciences
General information
?
?
The future of medical research and healthcare is personalized, digitized, and data-driven. The provision, analysis, and interpretation of this data rely on interdisciplinary collaborations. Thus, the foundations for future medical progress are laid at the interface of medicine and computer science.
?
The field of research and studies Medical Information Sciences has?been?established?as a response?to?this?development,?introducing a guest lecture?series?of?the same name in the winter semester of 2022/2023. It adresses current?questions from science and provides insights into corresponding areas of industry.
?
?
?
The MIS lecture series will take place this winter semester on Thursdays at 4:00 pm at the Faculty of Applied Computer Science in Lecture Hall N2045.??
?
A shared electronic calendar for the MIS lecture series can be found at the following link: https://bioinf-nextcloud.informatik.uni-augsburg.de/apps/calendar/p/ppNc2sNPDMFBGKoG?(You can access the registration link via the three dots to the left of the calendar name.)
?
Additionally, the events will be live-streamed. If you are interested in attending the live-stream, we kindly ask you to register by sending an informal email to office.bioinf@informatik.uni-augsburg.de?on time.?
?
The lectures aim at an interested professional audience and will be held in English.
?
More information about the speakers and their lectures are available on this website or via the official MIS newsletter, which you can register for at the bottom of this webpage.
?
?
In addition, prior to each lecture, we offer an opportunity?to?discuss individual scientific?questions, topics or cooperation opportunites with?the?speaker. If you are interested, please register in advance by sending a short message to office.bioinf@informatik.uni-augsburg.de.
?
Below, you find the schedule for the summer semester 2026?with further information on each single lecture:
?
schedule for the summer semester 2026
Location: Lecture hall N2045 (Faculty of Applied Computer Science)
?
Abstract
Mechanistic modeling provides a quantitative framework to connect molecular properties, ocular physiology, and clinical outcomes. The eye represents a uniquely accessible system in which key processes - such as diffusion, anatomical barriers, and fluid turnover - can be integrated into ODE-based models to describe drug distribution and elimination. These principles explain central observations such as ocular half-life and its translation across species, by linking molecular size and eye geometry to pharmacokinetics.
A major opportunity arises from combining such models with increasingly rich longitudinal data of drug effect. High-frequency measurements from emerging technologies such as home optical coherence tomography (OCT) capture disease dynamics at an unprecedented temporal resolution. Integrating these data with pharmacokinetic/pharmacodynamic (PK/PD) models enables a more precise characterization of treatment response and has been shown to improve the efficiency of clinical studies by reducing required sample sizes while maintaining statistical power.
Together, these approaches illustrate how mechanistic understanding can be translated into predictive capability - making it possible to infer otherwise inaccessible processes within the eye and to guide therapeutic development. At the same time, important open questions remain, including a deeper understanding of tissue-level distribution and variability in response, offering opportunities for collaborative research at the interface of modeling, data science, and experimental biology.
?
Speaker:?
?
Biography
Dr. Bernhard Steiert is Head of Clinical Pharmacometrics at Roche Pharma Research and Early Development (pRED), Pharmaceutical Sciences, at the Roche Innovation Center Basel, Switzerland. He leads a team of pharmacometricians across therapeutic areas, focusing on the application of modeling and simulation to inform drug development and decision-making.
He obtained his PhD in theoretical physics from the University of Freiburg in 2017, working on modeling and simulation of biological processes. He joined Roche that same year and has since contributed to projects in the preclinical and clinical space in several disease areas, and particularly within ophthalmology. In this context, he also serves as Clinical Pharmacologist, supporting dose selection and development strategy.
His work centers on mechanistic and data-driven approaches, including ODE-based modeling, digital biomarkers, and innovative study designs. He has pioneered the use of high-frequency patient data, such as home OCT, and to the development of novel modeling concepts for clinical decision-making. His interests further include AI-based methods, such as neural ODEs, and questions of model identifiability.
Dr. Steiert collaborates with academic partners and has supervised students and early-career researchers at the interface of biology and modeling.
Location: Lecture hall N2045 (Faculty of Applied Computer Science)
?
Abstract
?
?
Speaker:? Prof. Dr. Chi Wang Ip
?
Biography
?
Location: Lecture hall N2045 (Faculty of Applied Computer Science)
?
Abstract
?
?
Speaker:?
?
Biography
?
Location: Lecture hall N2045 (Faculty of Applied Computer Science)
?
Abstract
?
?
Speaker:? Dr. Mohammad Farid Azampour
?
Biography
?
Location: Lecture hall N2045 (Faculty of Applied Computer Science)
?
Abstract
Biotechnology and drug research are facing increasingly complex challenges: diseases are becoming more individualized, drug development remains costly and slow, and the demand for sustainable solutions in medicine continues to grow. Generating new insights in this environment requires more than just data — it requires intelligent integration and interpretation. This talk presents a systematic AI-driven approach to understanding biological systems, based on a globally unique, deeply curated dataset that combines biological sequence data with rich semantic knowledge about entities and their relationships. By integrating large language models, knowledge graphs, and multi-modal data, we enable AI systems to uncover hidden biological patterns and generate actionable insights — often without extensive wet-lab experimentation. The lecture demonstrates how such data can be transformed into practical, explainable applications: from advanced sequence analysis and automated biomarker discovery to precise prediction of biological interactions and AI-supported drug repurposing and repositioning. The result is a new generation of AI tools that accelerates discovery, reduces costs, and supports more sustainable and personalized innovation in the life sciences.
?
Speaker:? Prof. Dr. Prof. h.c. Andreas Dengel
?
Biography
Andreas Dengel is a professor at the Department of Computer Science at the RPTU University of Kaiserslautern-Landau, an Executive Director of the German Research Center for Artificial Intelligence (DFKI) in Kaiserslautern, and head of the Smart Data & Knowledge Services research department at DFKI. Since 2009, he has also held a professorship (kyakuin) at the Department of Computer Science and Intelligent Systems at Osaka Metropolitan University. He has received many awards for his work and scientific achievements. In 2019, for example, he was selected by a jury on behalf of the German Federal Ministry of Education and Research (BMBF) as one of the most influential scientists in 50 years of AI history in Germany for his research in the field of document analysis. He is the recipient of the Order of Merit of Rhineland-Palatinate and was awarded the “Order of the Rising Sun, Gold Star” in 2021, Japan's oldest order, on behalf of His Majesty Emperor Naruhito. His recent research focuses on a wide-spectrum neuro-symbolic AI problems (https://scholar.google.de/citations?hl=de&user=p3YP0DMAAAAJ&view_op=list_works&sortby=pubdate)
?
Location: Lecture hall N2045 (Faculty of Applied Computer Science)
?
Abstract
?
?
Speaker:?
?
Biography
?
Location: Lecture hall N2045 (Faculty of Applied Computer Science)
?
Abstract
?
?
Speaker:?
?
Biography
?
Location: Lecture hall N2045 (Faculty of Applied Computer Science)
?
Abstract
Despite impressive performance in publications, many AI models fail when deployed in real-world settings. One important reason is poor or misleading validation. This talk explores common pitfalls in validating AI systems, especially the misuse of performance metrics, and shows how they can create false confidence. Practical recommendations will be offered to guide more robust and trustworthy validation practices, aimed at supporting the safe and effective integration of AI into real-world workflows.
?
Speaker:?
?
Biography
Dr. Annika Reinke is Deputy Head of Department of the Intelligent Medical Systems Division at the German Cancer Research Center (DKFZ), where she leads the Validation of Intelligent Systems group. Her research focuses on identifying and eliminating fundamental flaws in the validation of biomedical image analysis algorithms. Through her work, Dr. Reinke addresses societally and clinically relevant challenges in medical AI, aiming to improve the robustness, comparability, and real-world relevance of validation pipelines. She plays a leading role in the international community, serving as Secretary of the MICCAI Special Interest Group on Biomedical Challenges and as Chair of the MONAI Working Group on Evaluation and Benchmarking, among others. Her contributions have been recognized with several prestigious awards, including the Hector Foundation Award and the Richtzenhain Doctoral Prize.
Location: Lecture hall N2045 (Faculty of Applied Computer Science)
?
Abstract
?
?
Speaker: PD Dr. Matthias Grothe
?
Biography
?
Location: Lecture hall N2045 (Faculty of Applied Computer Science)
?
Abstract
?
?
Speaker:? Prof. Dr. Bj?rn Schuller
?
Biography
?
Location: Lecture hall N2045 (Faculty of Applied Computer Science)
?
Abstract
?
?
Speaker:?
?
Biography
?
Location: Lecture hall N2045 (Faculty of Applied Computer Science)
?
Abstract
?
?
Speaker:? Dr.-Ing. Miriam Goldammer
?
Biography
?
Subscription to the MIS newsletter
We appreciate your interest in the work of the Chair of Biomedical Informatics, Data Mining and Data Analytics!
?
Filling in the following registration form, you can request to receive regular updates on current information as well as notifications of events related to the MIS field of research.
?
?
Registration form
?
?
By subscribing to our media, you agree to the processing of your data for the purpose of delivering the selected media, as well as to the data protection policies of the University of Augsburg. The collected data is solely used for delivering the selected media and documenting your consent. There is no other processing of the data and no sharing of the data with third parties. You may revoke your subscription and consent to the storage of your data at any time without giving any reasons. Please send a simple email to office.bioinf@informatik.uni-augsburg.de for this purpose.