Conference Agenda
Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).
Please note that all times are shown in the time zone of the conference. The current conference time is: 24th Apr 2026, 04:59:28pm CEST
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Agenda Overview |
Mon08June
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Helmholtz Munich Campus
Foyer
Mensa
No specific location / location unknown
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WS 1 (1/4) - Data Parallelism: How to Train Deep Learning Models on Multiple GPUs
9:00am - 11:00am
Track 1
Location: Track 1
Brief Description and Outline:
Modern deep learning challenges leverage increasingly larger datasets and more complex models. As a result, significant computational power is required to train models effectively and efficiently. Learning to distribute data across multiple GPUs during deep learning mo...
Modern deep learning challenges leverage increasingly larger datasets and more complex models. As a result, significant computational power is required to train models effectively and efficiently. Learning to distribute data across multiple GPUs during deep learning mo...
WS 1 (2/4) - Data Parallelism: How to Train Deep Learning Models on Multiple GPUs
11:15am - 1:15pm
Track 1
Location: Track 1
Brief Description and Outline:
Modern deep learning challenges leverage increasingly larger datasets and more complex models. As a result, significant computational power is required to train models effectively and efficiently. Learning to distribute data across multiple GPUs during deep learning mo...
Modern deep learning challenges leverage increasingly larger datasets and more complex models. As a result, significant computational power is required to train models effectively and efficiently. Learning to distribute data across multiple GPUs during deep learning mo...
WS 1 (3/4) - Data Parallelism: How to Train Deep Learning Models on Multiple GPUs
2:15pm - 4:15pm
Track 1
Location: Track 1
Brief Description and Outline:
Modern deep learning challenges leverage increasingly larger datasets and more complex models. As a result, significant computational power is required to train models effectively and efficiently. Learning to distribute data across multiple GPUs during deep learning mo...
Modern deep learning challenges leverage increasingly larger datasets and more complex models. As a result, significant computational power is required to train models effectively and efficiently. Learning to distribute data across multiple GPUs during deep learning mo...
WS 1 (4/4) - Data Parallelism: How to Train Deep Learning Models on Multiple GPUs
4:30pm - 6:30pm
Track 1
Location: Track 1
Brief Description and Outline:
Modern deep learning challenges leverage increasingly larger datasets and more complex models. As a result, significant computational power is required to train models effectively and efficiently. Learning to distribute data across multiple GPUs during deep learning mo...
Modern deep learning challenges leverage increasingly larger datasets and more complex models. As a result, significant computational power is required to train models effectively and efficiently. Learning to distribute data across multiple GPUs during deep learning mo...
WS 2a (1/2) - Building Agentic ML Tools for Science: What Works and What Doesn’t
9:00am - 11:00am
Track 2
Location: Track 2
Brief Description and Outline:
Large language models and agentic AI systems are increasingly being adopted as tools in scientific workflows —from literature review and data analysis to experimental design and code generation.
Yet building effective agentic tools for research remains as much craft as...
Large language models and agentic AI systems are increasingly being adopted as tools in scientific workflows —from literature review and data analysis to experimental design and code generation.
Yet building effective agentic tools for research remains as much craft as...
WS 2a (2/2) - Building Agentic ML Tools for Science: What Works and What Doesn’t
11:15am - 1:15pm
Track 2
Location: Track 2
Brief Description and Outline:
Large language models and agentic AI systems are increasingly being adopted as tools in scientific workflows —from literature review and data analysis to experimental design and code generation.
Yet building effective agentic tools for research remains as much craft as...
Large language models and agentic AI systems are increasingly being adopted as tools in scientific workflows —from literature review and data analysis to experimental design and code generation.
Yet building effective agentic tools for research remains as much craft as...
WS 2b (1/2) - Open Challenges in Simulation-Based Inference
2:15pm - 4:15pm
Track 2
Location: Track 2
Brief Description and Outline:
Simulation-Based Inference (SBI) is rapidly emerging as a powerful paradigm for scientific discovery, enabling parameter estimation, uncertainty quantification, and model selection in complex systems. However, significant challenges remain in translating SBI’s potentia...
Simulation-Based Inference (SBI) is rapidly emerging as a powerful paradigm for scientific discovery, enabling parameter estimation, uncertainty quantification, and model selection in complex systems. However, significant challenges remain in translating SBI’s potentia...
WS 2b (2/2) - Open Challenges in Simulation-Based Inference
4:30pm - 6:30pm
Track 2
Location: Track 2
Simulation-Based Inference (SBI) is rapidly emerging as a powerful paradigm for scientific discovery, enabling parameter estimation, uncertainty quantification, and model selection in complex systems. However, significant challenges remain in translating SBI’s potential into widespread practical app...
WS 3a - Reproducible Benchmarking and Multi-Omics Integration Using the Multiverse Framework
9:00am - 11:00am
Track 3
Location: Track 3
Brief Description and Outline:
This workshop will focus on standardized benchmarking and reproducible evaluation of multiomics integration methods in bioinformatics, using Multiverse as a unifying framework rather than as the sole focus. The session will begin with a 15-minute conceptual overview of...
This workshop will focus on standardized benchmarking and reproducible evaluation of multiomics integration methods in bioinformatics, using Multiverse as a unifying framework rather than as the sole focus. The session will begin with a 15-minute conceptual overview of...
WS 3b - Responsible AI in Industrial Production: Practices and Methods for Predictive Models
11:15am - 1:15pm
Track 3
Location: Track 3
Brief Description and Outline:
This workshop addresses how ethical, fairness-related, and sustainability considerations can be systematically embedded into industrial AI projects. While industrial AI systems increasingly rely on predictive models and uncertainty-aware decision support, ethical aspec...
This workshop addresses how ethical, fairness-related, and sustainability considerations can be systematically embedded into industrial AI projects. While industrial AI systems increasingly rely on predictive models and uncertainty-aware decision support, ethical aspec...
WS 3c (1/2) - Medical Foundation Models: From Pretraining to Clinical Impact (MedFM @ HAICON26)
2:15pm - 4:15pm
Track 3
Location: Track 3
Brief Description and Outline:
Foundation models are rapidly reshaping medical AI, enabling large‑scale representation learning across imaging, clinical text, biosignals, and multimodal health data. While recent advances demonstrate impressive performance across a wide range of downstream tasks, sig...
Foundation models are rapidly reshaping medical AI, enabling large‑scale representation learning across imaging, clinical text, biosignals, and multimodal health data. While recent advances demonstrate impressive performance across a wide range of downstream tasks, sig...
WS 3c (2/2) - Medical Foundation Models: From Pretraining to Clinical Impact (MedFM @ HAICON26)
4:30pm - 6:30pm
Track 3
Location: Track 3
Brief Description and Outline:
Foundation models are rapidly reshaping medical AI, enabling large‑scale representation learning across imaging, clinical text, biosignals, and multimodal health data. While recent advances demonstrate impressive performance across a wide range of downstream tasks, sig...
Foundation models are rapidly reshaping medical AI, enabling large‑scale representation learning across imaging, clinical text, biosignals, and multimodal health data. While recent advances demonstrate impressive performance across a wide range of downstream tasks, sig...
TT 4a (1/2) - From Prompts to AI Applications: A Hands-On Introduction to RAG and LLM Systems
9:00am - 11:00am
Track 4
Location: Track 4
Brief Description and Outline:
This 4-hour hands-on tutorial introduces practical methods for building Generative AI (Gen AI) applications using prompt engineering and Retrieval-Augmented Generation (RAG). The session moves from controlling large language model (LLM) behavior to grounding models in ...
This 4-hour hands-on tutorial introduces practical methods for building Generative AI (Gen AI) applications using prompt engineering and Retrieval-Augmented Generation (RAG). The session moves from controlling large language model (LLM) behavior to grounding models in ...
TT 4a (2/2) - From Prompts to AI Applications: A Hands-On Introduction to RAG and LLM Systems
11:15am - 1:15pm
Track 4
Location: Track 4
Brief Description and Outline:
This 4-hour hands-on tutorial introduces practical methods for building Generative AI (Gen AI) applications using prompt engineering and Retrieval-Augmented Generation (RAG). The session moves from controlling large language model (LLM) behavior to grounding models in ...
This 4-hour hands-on tutorial introduces practical methods for building Generative AI (Gen AI) applications using prompt engineering and Retrieval-Augmented Generation (RAG). The session moves from controlling large language model (LLM) behavior to grounding models in ...
TT 4b - A Practical Tour of PEFT & Co.
2:15pm - 4:15pm
Track 4
Location: Track 4
Brief Description and Outline:
Foundation models can be adapted in many ways, but it’s often unclear how these approaches differ beyond their descriptions. In this interactive workshop, we start from a fixed pretrained check-point and walk through several prominent adaptation strategies (linear prob...
Foundation models can be adapted in many ways, but it’s often unclear how these approaches differ beyond their descriptions. In this interactive workshop, we start from a fixed pretrained check-point and walk through several prominent adaptation strategies (linear prob...
TT 4c - Small and Locally Deployed VLMs under Evaluation: A Case Study of Image Captioning
4:30pm - 6:30pm
Track 4
Location: Track 4
Brief Description and Outline:
This tutorial sheds the light on the small and locally deployed large language models (LLMs) and vision language models (VLMs). It starts by deploying them on our local machines with the help of Ollama. This is followed by the implementation of API endpoints – using Py...
This tutorial sheds the light on the small and locally deployed large language models (LLMs) and vision language models (VLMs). It starts by deploying them on our local machines with the help of Ollama. This is followed by the implementation of API endpoints – using Py...
WS 5a - Translating Research Concepts into GDPR-Compliant Projects: A Six-Step Process and Three Cases for Hands-on Practice
9:00am - 11:00am
Track 5
Location: Track 5
Brief Description and Outline:
Designing GDPR-compliant projects is challenging for many researchers, resulting in long approval cycles, repeated changes to the project design and suboptimal technical setups. This hands-on workshop introduces a six-step process for translating research concepts into...
Designing GDPR-compliant projects is challenging for many researchers, resulting in long approval cycles, repeated changes to the project design and suboptimal technical setups. This hands-on workshop introduces a six-step process for translating research concepts into...
WS 5b - AI, Brussels and how to participate in decision-making and science policy
11:15am - 1:15pm
Track 5
Location: Track 5
Brief Description and Outline:
The goals are here dual:
1) Inform and engage on AI developments and initiatives at the EU level (e.g RAISE), from a strategical point of view:
Why were such developments/ initatives chosen?
How did they materialize?
How can we, scientists, influence this process...
The goals are here dual:
1) Inform and engage on AI developments and initiatives at the EU level (e.g RAISE), from a strategical point of view:
Why were such developments/ initatives chosen?
How did they materialize?
How can we, scientists, influence this process...
WS 5c - The Science of Successful AI Communication
2:15pm - 4:15pm
Track 5
Location: Track 5
Brief Description and Outline:
How AI research is communicated plays a central role in shaping how AI is understood, trusted, and governed. AI researchers therefore have a unique opportunity to actively contribute to how their work is perceived and discussed beyond the lab.
Engaging with journalist...
How AI research is communicated plays a central role in shaping how AI is understood, trusted, and governed. AI researchers therefore have a unique opportunity to actively contribute to how their work is perceived and discussed beyond the lab.
Engaging with journalist...
WS 5d - Introduction to Prototyping
4:30pm - 6:30pm
Track 5
Location: Track 5
Brief Description and Outline:
During this 2-hour interactive workshop participants will get an introduction to rapid prototyping. They will define an idea and explore what makes an idea work, followed by building a prototype and presenting it to the other participants.
Goals:
Participants will expl...
During this 2-hour interactive workshop participants will get an introduction to rapid prototyping. They will define an idea and explore what makes an idea work, followed by building a prototype and presenting it to the other participants.
Goals:
Participants will expl...
WS 6a - Powering Helmholtz AI: HAICORE Infrastructure & AI Platform at HZDR
9:00am - 11:00am
Track 6
Location: Track 6
Brief Description and Outline:
This workshop introduces the HAICORE HPC Cluster at HZDR, a high-performance computing resource available to Helmholtz AI projects. This session focuses on how researchers can effectively utilize our Open OnDemand web portal to run AI and data-intensive workloads and o...
This workshop introduces the HAICORE HPC Cluster at HZDR, a high-performance computing resource available to Helmholtz AI projects. This session focuses on how researchers can effectively utilize our Open OnDemand web portal to run AI and data-intensive workloads and o...
WS 6b - Novel Helmholtz Imaging Tools for AI image processing along the pipeline
11:15am - 1:15pm
Track 6
Location: Track 6
Brief Description and Outline:
Joint introduction (~12 min)
Ella Bahry and Deborah Schmidt will give a short overview of PixelPatrol, and Hans Werners and Philipp Heuser will introduce the Helmholtz Model Zoo. The two tools address opposite ends of the AI pipeline in scientific imaging: PixelPatrol ...
Joint introduction (~12 min)
Ella Bahry and Deborah Schmidt will give a short overview of PixelPatrol, and Hans Werners and Philipp Heuser will introduce the Helmholtz Model Zoo. The two tools address opposite ends of the AI pipeline in scientific imaging: PixelPatrol ...
TT 6c - Qubits all the way down: A Gentle Dive into Quantum Machine Learning Theory
2:15pm - 4:15pm
Track 6
Location: Track 6
Brief Description and Outline:
This tutorial aims to provide attendees with a foundational introduction to quantum computing and quantum machine learning (QML). It will address key challenges in QML, including data en- coding strategies, model trainability [1], the barren plateau phenomenon [2], opt...
This tutorial aims to provide attendees with a foundational introduction to quantum computing and quantum machine learning (QML). It will address key challenges in QML, including data en- coding strategies, model trainability [1], the barren plateau phenomenon [2], opt...
TT 6d - Coding the Quantum Machine Learning Future: A hands-on Tutorial
4:30pm - 6:30pm
Track 6
Location: Track 6
Brief Description and Outline:
This is a hands-on tutorial to create a hybrid quantum-classical QML workflow for training a Quantum Neural Network. We will first introduce different strategies on how to include quantum computers into machine learning workflows. Further, we will not only show how an ...
This is a hands-on tutorial to create a hybrid quantum-classical QML workflow for training a Quantum Neural Network. We will first introduce different strategies on how to include quantum computers into machine learning workflows. Further, we will not only show how an ...
Start at 10:00 WS 7a (1/2) - AI in environmental research
9:00am - 11:00am
Track 7
Location: Track 7
Brief Description and Outline:
While HFMI and Helmholtz AI provide active fora to discuss machine learning from a methodological perspective, and there are dedicated conferences on weather AI (e.g., MLESM) and remote sensing (e.g., ESA ML for EO), there are few opportunities to establish connections...
While HFMI and Helmholtz AI provide active fora to discuss machine learning from a methodological perspective, and there are dedicated conferences on weather AI (e.g., MLESM) and remote sensing (e.g., ESA ML for EO), there are few opportunities to establish connections...
WS 7a (2/2) - AI in environmental research
11:15am - 1:15pm
Track 7
Location: Track 7
Brief Description and Outline:
While HFMI and Helmholtz AI provide active fora to discuss machine learning from a methodological perspective, and there are dedicated conferences on weather AI (e.g., MLESM) and remote sensing (e.g., ESA ML for EO), there are few opportunities to establish connections...
While HFMI and Helmholtz AI provide active fora to discuss machine learning from a methodological perspective, and there are dedicated conferences on weather AI (e.g., MLESM) and remote sensing (e.g., ESA ML for EO), there are few opportunities to establish connections...
WS 7b (1/2) - Current status of the benchmarking field: lessons learned from the first half of the UNLOCK initiative
2:15pm - 4:15pm
Track 7
Location: Track 7
Brief Description and Outline:
In this session, we will explore the state of the art in the benchmarking field, showcasing the most useful tools and summarizing best practices for setting up benchmarks. The workshop program features invited talks by leading contributors in the benchmarking field, a ...
In this session, we will explore the state of the art in the benchmarking field, showcasing the most useful tools and summarizing best practices for setting up benchmarks. The workshop program features invited talks by leading contributors in the benchmarking field, a ...
WS 7b (2/2) - Current status of the benchmarking field: lessons learned from the first half of the UNLOCK initiative
4:30pm - 6:30pm
Track 7
Location: Track 7
Brief Description and Outline:
In this session, we will explore the state of the art in the benchmarking field, showcasing the most useful tools and summarizing best practices for setting up benchmarks. The workshop program features invited talks by leading contributors in the benchmarking field, a ...
In this session, we will explore the state of the art in the benchmarking field, showcasing the most useful tools and summarizing best practices for setting up benchmarks. The workshop program features invited talks by leading contributors in the benchmarking field, a ...
WS 8a (1/2) - Causal Inference and Causal AI for Complex Dynamic Systems in Medicine and Biology
9:00am - 11:00am
Track 8
Location: Track 8
Brief Description and Outline:
This workshop aims to actively discuss the role of concepts of causality in complex dynamic systems and how the application of these concepts can be challenging to address in medicine and biology.
Understanding cause–and–effect relationships rather than pure correlatio...
This workshop aims to actively discuss the role of concepts of causality in complex dynamic systems and how the application of these concepts can be challenging to address in medicine and biology.
Understanding cause–and–effect relationships rather than pure correlatio...
WS 8a (2/2) - Causal Inference and Causal AI for Complex Dynamic Systems in Medicine and Biology
11:15am - 1:15pm
Track 8
Location: Track 8
Brief Description and Outline:
This workshop aims to actively discuss the role of concepts of causality in complex dynamic systems and how the application of these concepts can be challenging to address in medicine and biology.
Understanding cause–and–effect relationships rather than pure correlatio...
This workshop aims to actively discuss the role of concepts of causality in complex dynamic systems and how the application of these concepts can be challenging to address in medicine and biology.
Understanding cause–and–effect relationships rather than pure correlatio...
TT 8b (1/2) - TwinWeaver: Generative Artificial Intelligence and Digital Twins for Longitudinal Modelling
2:15pm - 4:15pm
Track 8
Location: Track 8
Brief Description and Outline:
This workshop introduces TwinWeaver, a generative artificial intelligence framework for building digital twins of longitudinal systems. Participants will learn how generative models can move beyond static prediction toward dynamic trajectory simulation, counterfactual ...
This workshop introduces TwinWeaver, a generative artificial intelligence framework for building digital twins of longitudinal systems. Participants will learn how generative models can move beyond static prediction toward dynamic trajectory simulation, counterfactual ...
TT 8b (2/2) - TwinWeaver: Generative Artificial Intelligence and Digital Twins for Longitudinal Modelling (End at 17:30)
4:30pm - 6:30pm
Track 8
Location: Track 8
Brief Description and Outline:
This workshop introduces TwinWeaver, a generative artificial intelligence framework for building digital twins of longitudinal systems. Participants will learn how generative models can move beyond static prediction toward dynamic trajectory simulation, counterfactual ...
This workshop introduces TwinWeaver, a generative artificial intelligence framework for building digital twins of longitudinal systems. Participants will learn how generative models can move beyond static prediction toward dynamic trajectory simulation, counterfactual ...
TT 9a - Deep Learning with Bayesian Principles
9:00am - 11:00am
Track 9
Location: Track 9
Brief Description and Outline:
The tutorial covers both practical tools to obtain uncertainty estimates in deep learning, as well as a theoretical understanding of various deep learning phenomena through a Bayesian lens.
Outline:
Part 1 -- Foundations of Bayesian Principles for Deep Learning (30 mi...
The tutorial covers both practical tools to obtain uncertainty estimates in deep learning, as well as a theoretical understanding of various deep learning phenomena through a Bayesian lens.
Outline:
Part 1 -- Foundations of Bayesian Principles for Deep Learning (30 mi...
WS 9b - Curiosity, Exploration, and Meta-Reinforcement Learning: Learning What to Learn
11:15am - 1:15pm
Track 9
Location: Track 9
Brief Description and Outline:
Agentic AI is becoming ubiquitous, but how an agent learns to navigate an environment efficiently remains an open problem. This session traces the exploration problem from its classical formulation in reinforcement learning (where the tension between exploiting known r...
Agentic AI is becoming ubiquitous, but how an agent learns to navigate an environment efficiently remains an open problem. This session traces the exploration problem from its classical formulation in reinforcement learning (where the tension between exploiting known r...
TT 9c - Uncertainty Quantification for Neural Networks: Make your model predictions trustworthy
2:15pm - 4:15pm
Track 9
Location: Track 9
Brief Description and Outline:
In machine learning, the ability to make reliable predictions is paramount. Yet, standard ML models and pipelines provide only point predictions without accounting for model confidence (or the lack thereof). Uncertainty in model outputs, especially when faced with out-...
In machine learning, the ability to make reliable predictions is paramount. Yet, standard ML models and pipelines provide only point predictions without accounting for model confidence (or the lack thereof). Uncertainty in model outputs, especially when faced with out-...
Self-paid dinner in downtown Munich
7:30pm - 10:00pm
Dinner is planned from 19:30 and will take place at a restaurant or beer garden in downtown Munich. The organizer will make a reservation based on the number of participants who register for the dinner. The venue will be selected to ensure easy access by public transport. The exact location will be ...
