Medical Data Science
| Lecturer: | Prof. Dr. Harald Binder |
| Start: | Wednesday, April 22, 2026 |
| End: | Wednesday, July 22, 2026 |
| Time: | 10:15 - 11:45 |
| Venue: | Lecture Hall IMBI, Stefan-Meier-Str. 26, 1st upper floor |
| VLVZ: | 07LE23S-Sem-8-Bi |
| Planing meeting: | Wednesday, Feb 04, 2026, 10:15-11:15 |
Content:
To answer complex biomedical questions, a broad spectrum of data analysis and modeling tools is required, ranging from classical statistical models to recent generative artificial intelligence approaches, such as large language models (LLMs). The idea of taking a broad perspective, allowing for the bringing together of the best aspects of many different approaches, is often summarized under the term “Medical Data Science.” A selection of approaches will be covered by the presenters in the seminar, which will be based on recently published original research, closely connected to the research of the Small Data Lab at the IMBI. The specific theme of the seminar for a semester is presented at the planning meeting, allowing participants to pick from the list of corresponding papers for presentation.
Requirements:
Participants should have a background in probability theory and mathematical statistics.
Remark:
A presentation in the seminar can be the basis for a subsequent Bachelor or Master’s thesis.
| Date | Presenter | Topic |
| 22.04.2026 | Jule Fritz | Language Models Represent Space and Time (2024),W. Gurnee and M. Tegmark, arxiv.org/abs/2310.02207 |
| 29.04.2026 | Iven-Stig Hiesener | The Geometry of Truth: Emergent Linear Structure in Large Language Model Representations of True/False Datasets (2024), S. Marks and M. Tegmark, arxiv.org/abs/2310.06824 |
| 06.05.2026 | Lucie Kutt | Locating and editing factual associations in GPT (2022) Meng et al. arxiv.org/abs/2202.05262 |
| 13.05.2026 | Ishant Srivastava | Insights into ordinal embedding algorithms: a systematic evaluation (2023), L. C. Vankadara, M. Lohaus, S. Haghiri, F. U. Wahab, and U. von Luxburg, jmlr.org/papers/v24/21-1170.html |
| 20.05.2026 | Richard Drohmann | Towards Monosemanticity: Decomposing Language Models With Dictionary Learning T. Bricken, A. Templeton, J. Batson, B. Chen, A. Jermyn, transformer-circuits.pub/2023/monosemantic-features |
| 03.06.2026 | Simon Reiser | Circuit Tracing: Revealing Computational Graphs in Language Models (2025), Part 1: A model for the LLM acitvity Ameisen et al., transformer-circuits.pub/2025/attribution-graphs/methods.html |
| 17.06.2026 | Aanisah R. Q. Bakry | Circuit Tracing: Revealing Computational Graphs in Language Models (2025), Part 2, use cases Ameisen et al., transformer-circuits.pub/2025/attribution-graphs/methods.html |
| 01.07.2026 (still needs to be confirmed) | Renaldo Pradipta Rizaham | Combining Hierachical VAEs with LLMs for clinically meaningful timeline summarisation in social media (2024), J. Song, J. Chim, A. Tsakalidis, J. Ive, D. Atzil-Slonim, M. Liakata, arxiv.org/abs/2401.16240 |
| 08.07.2026 | Leixian Wang | MedualTime: A Dual-Adapter Language Model for Medical Time Series-Text Multimodal Learning (2025), J. Ye , W. Zhang, Z. Li, J. Li, M. Zhao, F. Tsung, arxiv.org/pdf/2406.06620 |
| 15.07.2026 | Sabine Kronberger | ProMedTS: A Self-Supervised, Prompt-Guided Multimodal Approach for Integrating Medical Text and Time Series (2025), S. Niu, J. Ma, H. Lin, L. Bai, Z. Wang, W. Bi, Y. Xu, G. Li, and X. Yang, arxiv.org/pdf/2502.13509 |
| 22.07.2026 | Savannah Lane | TWIN-GPT: Digital Twins for Clinical Trials via Large Language Model (2024), Y. Wang, T. Fu, Y. Xu, Z. Ma, H. Xu, Y. Lu, B. Du, H. Gao, J. Wu, Link arxiv.org/abs/2404.01273 |
Please, register by email for the planning meeting: bemb.imbi.sek@list.uniklinik-freiburg.de
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