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Our recent Meet-Ups have once again highlighted the importance of interdisciplinary collaboration, and we are pleased to continue this series with the upcoming CAIMed Meet-Up: Machine Learning beyond textual data.
This Meet-Up will explore the expanding role of artificial intelligence beyond text-based applications. The program will begin with the HAIMed workshop, a CAIMed “sharktank” experiment designed to foster creative problem-solving and teamwork among PhD students and participants. Following an introduction session, participants will engage in an intensive working phase across multiple rooms, developing and refining their ideas in a collaborative setting.
In addition, the Meet-Up will feature two invited keynote lectures providing insights into cutting-edge developments and applications of Mashine Learning beyond textual data. The outcomes of the HAIMed working phase will be presented in a dedicated session, offering an opportunity to showcase innovative concepts and approaches. The event will conclude with the announcement of the winning team and a farewell.
A light lunch and coffee break will provide space for discussion, networking, and exchange among participants throughout the day.
We are pleased to invite you to the upcoming CAIMed Meet-up on 24 June 2026 – 09:30 a.m. to 3:45 p.m. at Königlicher Pferdestall (LUH), Appelstraße 7, 30167 Hannover (maps link).
❗ Please note The workshop (HAIMed) will take place at Appelstraße 11A, whilst the Meet-Up itself will be held at the Königliche Pferdestall❗
CAIMed is funded by the Ministry of Science and Culture of Lower Saxony with funds from the program zukunft.niedersachsen of the VolkswagenStiftung.
CAIMed is the Lower Saxony research center for artificial intelligence and causal methods in medicine. We develop innovative methods for improved, personalized healthcare and contribute to the management of widespread diseases such as cancer, cardiovascular diseases and infections. The combination of excellent locations in Lower Saxony for methodical AI research, data-intensive medicine, medical informatics and basic medical research creates a unique flagship project for research into AI and personalized medicine.
CAIMed relies on the linking of research data, clinical data and patient care data as well as the use of artificial intelligence and causal methods. This enables prevention, diagnostics, therapy and monitoring of therapeutic success to become more effective and efficient and the individual needs of each person to be better identified and served.