CAIMed Meet-up AI Powered Approaches in Infection Research
CAIMed Meet-up: AI Powered Approaches in Infection Research
We are pleased to invite you to the upcoming CAIMed Meet-up on January 30 2025, from 1:00 p.m. to 5:00 p.m. PM at TWINCORE, Zentrum für Experimentelle und Klinische Infektionsforschung GmbH. The meet-up will focus on "AI Powered Approaches in Infection Research",
Agenda
1:00 p.m. – 1:10 p.m. Welcome & Introduction (Prof. Dr. Yang Li, CAIMed, CiiM)
1:10 p.m. – 1:40 p.m. Session 1: AI systems for integrative Multi-Omics Data (Prof. Dr. Tim Beißbarth, University Medical Center Göttingen)
1:40 p.m. – 2:10 p.m. Session 2: Defense against respiratory pathogens (Dr.-Ing. Geraldine Nouailles, Charité - Universitätsmedizin Berlin)
2:10 p.m. – 2:40 p.m. Session 3: Machine learning applications to bacterial genomics, from essential genes to antimicrobial resistance (Prof. Dr. Marco Galardini, Twincore, MHH)
2:40 p.m. – 3:00 p.m. Coffee Break
3:00 p.m. – 4:20 p.m. Session 4: cutting-edge tocology powered by AI in infection research (CAIMed, Junior Research Group on AI & Bioinformatics)
1. From big data to immunological insights, Dr. Saumya Kumar
2. AI and gene regulatory network analysis: a practical introduction, Dr.-Ing. Jalil Nourisa
3. Spatial transcriptomics reveals abnormal immune and cell-matrix remodeling programs in MTB granuloma formation, Dr. Xun Jiang
4. AI powered segmentation and deconvolution in Spatial transcriptomics data analysisa, Yuesi Xi, M.Sc.
4:20 p.m. – 5:00 p.m. Reception & Networking
CAIMed is funded by the Ministry of Science and Culture of Lower Saxony with funds from the program zukunft.niedersachsen of the VolkswagenStiftung
Ticket(s)
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.