In recent years, AI has achieved remarkable advances, but creating trustworthy AI-algorithms that are fair, explainable, and robust remains a challenge. This Meet-up will delve into how causal representation learning is helping to address these issues and shaping the future of AI-driven healthcare.
We are pleased to invite you to the upcoming CAIMed Meet-up on 29.11.2024 at the L3S Research Center in Hannover. The Meet-up will focus on "Trustworthy AI, Causality and Deep Learning for Medicine", exploring the intersection of AI technologies and causal models in healthcare.
This event will feature a series of presentations from researchers within the CAIMed consortium, covering topics like AI in genomics, cancer prediction, and digital pathology.
Main Topics:
- Causal Representation Learning and Foundation Models
- RESIST: Remapping EIT signals using an implicit spatially-aware transformer
- AI-based Digital Pathology in Oncology and Cancer Screening
We look forward to inspiring presentations and networking opportunities.
Please register in advance to confirm your participation.
Speakers
Prof. Dr. techn.
Wolfgang Nejdl
Prof. Dr.
Marius Lindauer
Dr. Michelle Tang
Azlaan Mustafa Samad, M.Sc.
Johanna Schrader, M.Sc.
Julian Laue, M.Sc.
Dominik Becker, M.Sc.
Prof. Dr. Niels Grabe
Felipe Miranda Ruiz, M.Sc
