13:00–13:15
Opening remarks and Welcome
Astrid Lambrecht

13:15–13:30
Helmholtz AI in 2024
Fabian Theis & Timo Dickscheid

13:30–14:15
Highlights of AI advances inspired by physics
Kyle Cranmer

The Helmholtz Representation Model for Climate Science (HClimRep)
Martin Schultz

SOL-AI A symbiotic modular foundation model for accelerating solar energy materials development
Stefan Kesselheim

3D-ABC: Towards Global 3D Above and Below Ground Carbon Stocks
Aldino Rizaldy; Peter Steinbach

The Human Radiome Project – Unlocking 3D Radiological Data Analysis with Next-Generation Foundation Models
Fabian Isensee

The HFMI Synergy Unit: Building bridges and creating synergy between foundation model projects
Dagmar Kainmüller

DynGFN: Towards Bayesian Inference of Gene Regulatory Networks with GFlowNets
Lazar Atanackovic

An explainability framework for convolutional neural networks supporting MRI evaluation and clinical decision-making in dementia research
Devesh Singh

Risk control based trustworthiness of deep learning models for remote sensing applications
Protim Bhattacharjee

A Kernel-based Framework for Uncertainty in Generative AI
Sebastian Gruber

Advancing Brain Disorder Identification through Transformer-Based Models and Explainable AI
Hanning Guo

How to Transform AI Prototypes into Functional Healthcare Applications for Diagnostic Assistance? (Update 2024)
Martin Dyrba

Towards mitigating biases in single-cell analysis
Theresa Willem

Ethical Perspectives on AI-Based Clinical Decision Support Systems after Cardiac Surgery
Kirsten Brukamp

From nuclear repository processes to illegally traded spiders: An insight into the use cases of the AI Lab at the Federal Environment Agency
Luisa Bornberg

AutoAI-Pandemics: Democratizing Machine Learning for Analysis, Study, and Control of Epidemics and Pandemics
Ulisses Rocha

Uncovering Inductive Biases in Material Text Representation for Improved Language Modeling
Nawaf Alampara

ClarifAI: User-Centred Explainable AI (XAI) Methods for Scientists
Yulia Grushetskaya

Federated Continual Learning Goes Online: a Realistic Framework for Collaborative Class-Incremental Tasks
Giuseppe Serra

Advancing functional genomics analysis with Bayesian modeling: Case studies in RNA decay and pathogen invasion models
Laura Jenniches

End-to-End Track Reconstruction using Graph Neural Networks at Belle II
Lea Reuter

Enhancing Quality Control in Sparsely Distributed Environmental Sensor Networks with Graph Neural Networks
Elżbieta Lasota

Graph Neural Networks for Disease Gene Identification: Unveiling Disease-Specific Networks through Link Prediction
Nikolay Shvetsov

Adaptative Local PCA for Curvature Estimation on Data Manifolds
Lydia Mezrag

The Human Gut Microbiome Observable Universe: Unravelling Its Fingerprints via Dense Deep Clustering
Jonas Kasmanas

OneProt: Unified Protein Embeddings
Erinc Merdivan