EVENTS

Prof. Dr. Heike Zinsmeister, Institut für Germanistik

Unter dem Motto „KI, wie geht das?“ bieten wir für alle Interessierten eine Einführung in die Funktionsweise von Large Language Models (LLMs) wie ChatGPT und Co. Anschließend werden wir UHHGPT gemeinsam ausprobieren und den Einsatz anhand von konkreten Szenarien für die geisteswissenschaftliche Lehre, das Studium und die Forschung erkunden. Technische Vorkenntnisse sind nicht notwendig, bitte bringen Sie Ihren eigenen Laptop mit.

Anmeldung an: digitale.gw@uni-hamburg.de

Institutions

• UHH

Recent advances in Generative AI have given rise to strong emotions among the general public, including excitement, fear, wonder, and disbelief. To be sure, the emergence of Large Language Models (LLMs) marks a significant milestone in the history of AI. But are systems like ChatGPT and Gemini actually intelligent, and are we at the threshold of so-called Artificial General Intelligence (AGI)? This session provides an overview of how LLM-based systems work, where they excel, and where they fall short, with a special emphasis on opportunities for the complementary strengths of humans and machines.

Session Objectives:

By the end of the session, participants will be able to:

• Explain the probabilistic nature of Large Language Models (LLMs) to demystify how they generate responses.
• Differentiate between the capabilities of current Generative AI and the “magical thinking” often associated with Artificial General Intelligence (AGI).
• Identify the operational limitations of AI systems to determine where human intervention and oversight are essential.
• Map complementary strengths of humans and machines to optimize collaboration in their own workflows.

Institutions

• AI for Good

Weather forecasting is critical for a range of human activities including transportation, agriculture, industry, as well as the safety of the general public. Over the last two years, machine learning models have shown that they have the potential to transform the complex weather prediction pipeline, but current approaches still rely on numerical weather prediction (NWP) systems, limiting forecast speed and accuracy. In this talk, some of the background on these developments will be given. A new generation of machine learning model will then be introduced which can replace the entire operational NWP pipeline. Aardvark Weather, an end-to-end data-driven weather prediction system, ingests raw observations and outputs global gridded forecasts and local station forecasts. Further, it can be optimised end-to-end to maximise performance over quantities of interest. It will be shown that the system outperforms an operational NWP baseline for multiple variables and lead times for gridded and station forecasts. Finally, the talk will end by discussing how these ideas might develop over the next few years, including their application to multiple parts of the Earth system on multiple time-scales, and their potential impact on climate modelling.

Institutions

• AI for Good

Das KI-Interface HAWKI von der Hochschule für angewandte Wissenschaft und Kunst Hildesheim/Holzminden/Göttingen (HAWK) zeigt, wie Open-Source-KI-Technologie im Bildungsbereich praktisch und datenschutzkonform eingesetzt werden kann. So bauen beispielsweise UHHGPT der Universität Hamburg und der Chatbot "TUKI" der TU Hamburg auf HAWKI auf und stehen dort allen Mitgliedern der Universität zu Verfügung. Die HfMT Hamburg verfügt über einen eigenen Chatbot "Frag Wolfgang", der auf ChatGPT-4 Turbo beruht.

In dieser 30-minütigen Online-Schulung lernen Sie das KI-Interface HAWKI kurz kennen und erhalten einen praxisnahen Einblick in die Anwendung und Einsatzmöglichkeiten im Hochschulkontext. 

Dabei werden sowohl Chancen als auch Herausforderungen aufgezeigt, um einen praxisnahen Umgang mit HAWKI zu ermöglichen. 

Vorkenntnisse werden nicht benötigt.

Institutions

• UHH

In Adobe Premiere Pro gibt es mittlerweile verschiedene KI-Tools, die die Postproduktion unterstützen und erleichtern sollen. In 30 Minuten geben wir einen Überblick über den aktuellen Stand der Möglichkeiten, die es bereits gibt und die vielleicht bald hinzukommen.

Wir werfen einen Blick darauf, wie die KI-Tools funktionieren und wie sie in den eigenen Workflow integriert werden können. 
Grundkenntnisse in Adobe Premiere Pro sind nicht erforderlich, aber hilfreich.

Alex Derr from the Software Engineering Institute at Carnegie Mellon University will join us at the HiRSE Seminar Series to talk about “MLTE: A process and tool for test and evaluation of machine learning models”

Abstract:
Test and Evaluation (T&E) of ML models largely focuses on model performance (e.g., accuracy) and often does not consider system aspects, which leads to models that fail in production. We will present MLTE, a semi-automated process and tool that enables negotiation, specification, and testing of ML model functional and non-functional requirements. A Negotiation Card records results of stakeholder discussions, which drive model development decisions and relevant test cases. MLTE automates test case execution and stores results that can be shared with stakeholders to provide evidence of testing that guides future iterations and system-level decisions.

The announcement and connection details are posted here:

• HiRSE-internal HiRSE Mattermorst channel,
• HIFIS Mattermost channel,
• Helmholtz Open Science Mattermost channel,
• FZJ-internal #rse Rocket.Chat channel,
• de-RSE mailing list and de-RSE Mattermost channel,
• Helmholtz Open Science Pro Mailinglist,
• RSE mailing lists of the HiRSE partners (if any).

If you are unable to join via one of these channels please email hirse@fz-juelich.de.

Institutions

• Helmholtz Platform for Research Software Engineering - Preparatory Study

Jeffrey Ding (George Washington University): Reputation Collectives: How International Industry Associations Influence China's Safety Standards in High-Risk Technologies

Artificial intelligence is rapidly transforming societies, economies, and political systems worldwide, and China is emerging as a central actor in shaping the governance of these technologies. This lecture series explores the multiple dimensions of AI governance in China, from state regulation and the role of AI in public administration to societal engagement with AI technologies.

The lectures highlight how China’s AI ambitions intersect with broader global trends and geopolitical tensions. The rise of generative AI has intensified the U.S.–China technological and strategic competition, introducing new complexities to the traditional security dilemma. At the same time, Chinese efforts to regulate and promote AI domestically reflect broader concerns over economic competitiveness, social stability, and regime security. The BCCN lecture series shed light on how AI is reshaping power relations, technological competition, and everyday life.

Join us online and in person for six lectures featuring leading scholars, including: Jinghan Zeng (City University of Hong Kong), Hui Zhou and Genia Kostka (Freie Universität Berlin) and Angela Huyue Zhang (USC Gould School of Law), Eddie Yang (Purdue University), David Yang (Harvard University) and Jeffrey Ding (George Washington University).

Hosted by the Berlin Contemporary China Network (BCCN), the China Competence Training Center (CCTC) and SCRIPTS, the 2025/26 winter term lecture series is conceptualized by Prof. Dr. Genia Kostka and Anton Bogs from Freie Universität Berlin.

Registration here

Institutions

• Institut für Asien- und Afrikawissenschaften, Humboldt-Universität zu Berlin 

Wie sieht die Zukunft der Videoproduktion aus?

Diese Online-Schulung gibt Ihnen einen Überblick über die neuesten Anwendungen von künstlicher Intelligenz in der Videoproduktion.

Es wird gezeigt, wie KI-Tools die Art und Weise verändern, wie Videos erstellt, bearbeitet und optimiert werden.

Mittlerweile ist es sogar mit Hilfe von KI-Tools möglich, kurze Bewegtbildsequenzen aus Bildern und Text-to-Video-Prompts zu generieren.

Wie könnte nun ein zukünftiger Produktionsworkflow mit Hilfe von KI-Tools aussehen?

In dieser Schulung wird anhand von Beispielen gezeigt, wie generative KI die Videoproduktion verändert.

Despite the global expansion of mobile and internet networks, critical connectivity gaps persist – particularly in areas most vulnerable to natural hazards and other emergencies. Reaching these populations with timely early warnings remains a pressing challenge for achieving the UN Early Warnings for All (EW4All) initiative.

Approximately 97.9% of the world’s population is covered by mobile network technology, gaps remain, leaving millions without reliable access to life-saving communications.

To address this challenge, the Telecommunication Development Bureau (BDT) of the International Telecommunication Union (ITU), in partnership with Microsoft AI for Good Lab, Planet Labs and the Institute of Health Metrics and Evaluation (IHME) at the University of Washington, has developed the Early Warning Connectivity Map (EWCM). This geospatial tool integrates connectivity and coverage datasets with high-resolution population density and hazard exposure datasets to produce granular, subnational maps that identify connectivity ‘coldspots’.

The EWCM helps ICT regulators and national stakeholders to visualize where connectivity investments or alternative communication solutions – such as radio or satellite – are needed to ensure access to early warnings. This session will showcase the EWCM using a case study from Liberia, illustrating its value for strengthening early warning systems nationally. Learn more

Institutions

• AI for Good

In DaVinci Resolve gibt es verschiedene KI-Tools, die die Postproduktion erleichtern sollen.

In 30 Minuten erhalten Sie einen Überblick über den aktuellen Stand der Möglichkeiten, die es bereits gibt und die vielleicht bald hinzukommen. Wir schauen uns an, wie die Tools funktionieren und wie sie in den eigenen Workflow integriert werden können.

Grundkenntnisse in DaVinci Blackmagic Resolve sind nicht erforderlich, aber hilfreich.

Satellite remote sensing enables a wide range of downstream applications, including habitat mapping, carbon accounting, and strategies for conservation and sustainable land use. However, satellite time series are voluminous and often corrupted, making them challenging to use: the scientific community’s ability to extract actionable insights is often constrained by the scarcity of labelled training datasets and the computational burden of processing temporal data.

The presentation will introduce TESSERA (Time-series Embeddings of Surface Spectra for Earth Representation and Analysis), an open foundation model that preserves spectral-temporal signals in 128-dimensional latent representations at 10-meter resolution globally. The model uses self-supervised learning to summarise petabytes of Earth observation data. TESSERA is shown to be label-efficient and closely matches or outperforms state-of-the-art alternatives. By preserving temporal phenological signals that are typically lost in conventional approaches, TESSERA enables new insights into ecosystem dynamics, agricultural food systems, and environmental change detection. Moreover, the open-source implementation supports reproducibility and extensibility, while the privacy-preserving design allows researchers to maintain data sovereignty. To current knowledge, TESSERA is unprecedented in its ease of use, scale, and accuracy: no other foundation model provides analysis-ready outputs, is open, and delivers global, annual coverage at 10m resolution using only spectral-temporal features at pixel level.

This session is part of a two-session series, providing the theoretical introduction to TESSERA. The second session, a hands-on workshop, will be held on February 2nd, 2026.

Institutions

• AI for Good

David Y. Yang (Harvard University): Government as Venture Capitalists in AI

Artificial intelligence is rapidly transforming societies, economies, and political systems worldwide, and China is emerging as a central actor in shaping the governance of these technologies. This lecture series explores the multiple dimensions of AI governance in China, from state regulation and the role of AI in public administration to societal engagement with AI technologies.

The lectures highlight how China’s AI ambitions intersect with broader global trends and geopolitical tensions. The rise of generative AI has intensified the U.S.–China technological and strategic competition, introducing new complexities to the traditional security dilemma. At the same time, Chinese efforts to regulate and promote AI domestically reflect broader concerns over economic competitiveness, social stability, and regime security. The BCCN lecture series shed light on how AI is reshaping power relations, technological competition, and everyday life.

Join us online and in person for six lectures featuring leading scholars, including: Jinghan Zeng (City University of Hong Kong), Hui Zhou and Genia Kostka (Freie Universität Berlin) and Angela Huyue Zhang (USC Gould School of Law), Eddie Yang (Purdue University), David Yang (Harvard University) and Jeffrey Ding (George Washington University).

Hosted by the Berlin Contemporary China Network (BCCN), the China Competence Training Center (CCTC) and SCRIPTS, the 2025/26 winter term lecture series is conceptualized by Prof. Dr. Genia Kostka and Anton Bogs from Freie Universität Berlin.

Registration here

Institutions

• Institut für Asien- und Afrikawissenschaften, Humboldt-Universität zu Berlin 

Aus einfachen Text- oder Bildeingaben können mit dem browserbasierten AI-Tool RunwayML Videoclips generiert und mit Magic Tools nachbearbeitet werden.

In 30 Minuten lernen Sie einen beispielhaften Workflow zur Generierung von Videoclips aus Einzelbildern oder Textprompts kennen. Dabei werden Ihnen die einzelnen Arbeitsschritte in RunwayML gezeigt.

Diese Online-Schulung richtet sich an Einsteiger*innen und es werden keine Vorkenntnisse vorausgesetzt.

We are calling in all AI enthusiasts in Hamburg. Let's talk and exchange thoughts and ideas!

Meet other AI and tech enthusiasts at our well-established AI Meetup, bringing together the Hamburg AI scene for more than three years. Join us for the AI Mix & Mingle at Sofabar, where you can chat casually, exchange ideas, or discuss your AI projects. There are no presentations—the focus is on networking and open conversation.

While your registration is not mandatory, it is appreciated. You would make our reporting easier if you sign up on Eventbrite. But feel free to drop by spontaneously, too, to connect with us and others, build networks, and dive into interesting conversations about AI and beyond!

We are lookimg forward to seeing you there!
For any questions, comments, or feedback, please email us at: cm@aric-hamburg.de
More information on our website: [https://aric-hamburg.de/veranstaltungen/ai-mix-mingle

Institutions

• Artificial Intelligence Center Hamburg (ARIC) e.V.

DKRZ and UniHH are hosting the next 4.5 days '**Python Course for Geoscientist** s' as a virtual workshop from **02\. to 06. February 2026**. 
This course is offered to our DKRZ users and project partners and is particularly designed for **beginners** with little or no knowledge of Python. In each section of the course, participants can work interactively on the
tasks in order to better understand what they have learned.

Course content: Python core language, NumPy, Xarray, Matplotlib, Cartopy

\- **For those interested, we offer a short introduction to Linux and Jupyterhub on Monday, 02.02.26**
\- **The actual 4 days Python course then starts on Tuesday, 03.02.26**

This course will take place online via videoconference. Register now

Institutions

• DKRZ
• UHH

This is a global startup pitching session to find the most promising solutions using AI to address challenges in the healthcare sector. The competition is open to any innovative startups using artificial intelligence, machine learning, and advanced algorithms to improve the access and affordability of healthcare services around the world. It focuses on AI for global health improvement, making AI solutions accessible and impactful across diverse health systems, particularly in low-resource settings and through integration into existing healthcare systems.

Benefits for startups

The Winner of the session receives:     

• AI for Good Innovation Factory Grand Finale ticket at the AI for Good Global Summit 2026 
• Speaker Pass to attend the AI for Good Global Summit 2026 
• Startup pod at the AI for Good Global Summit 2026  
• Pitching opportunity in the Frontier Stage at the AI for Good Global Summit 2026 
• Exclusive access to the AI for Good Innovation Factory Startup Accelerator Programme 2026   
• Featured startup in the Innovation Factory Exhibition on the AI for Good Neural Network     
• Exclusive follow-up mentoring from judges after the session
• Exclusive access to AI for Good Innovation Factory Alumni Network
• Networking opportunities with the UN and other potential business partners 

Institutions

• AI for Good

Gastvortrag von Julia Katharina Saatkamp, Abteilungsleitung eLearning.Medien im Bielefelder IT-Servicezentrum (BITS) der Uni Bielefeld

Der BITS SPACE der Uni Bielefeld vereint verschiedene IT- und Medienservices des Bielefelder IT-Servicezentrums (BITS). Er bietet neben unterschiedlichen Medienräumen und Studios zu den Themen Podcast, Videoproduktion, XR und 3D-Druck auch moderne IT-Arbeitsplätze für Studierende sowie eine umfangreich ausgestattete Geräteausleihe. 
Der Beitrag liefert einen Einblick in die Konzeption des BITS SPACE als Servicebereich mit dem Anspruch zentrale IT- und Medieninfrastrukturen zukunftsorientiert, nachhaltig und bedarfsgerecht anzubieten. Wir möchten Sie einladen, nach dem Impulsvortrag mit uns in den Austausch zu treten.

We are calling in all AI enthusiasts in Hamburg. Let's talk and exchange thoughts and ideas!

Meet other AI and tech enthusiasts at our well-established AI Meetup, bringing together the Hamburg AI scene for more than three years. Join us for the AI Mix & Mingle at Sofabar, where you can chat casually, exchange ideas, or discuss your AI projects. There are no presentations—the focus is on networking and open conversation.

While your registration is not mandatory, it is appreciated. You would make our reporting easier if you sign up on Eventbrite. But feel free to drop by spontaneously, too, to connect with us and others, build networks, and dive into interesting conversations about AI and beyond!

We are lookimg forward to seeing you there!
For any questions, comments, or feedback, please email us at: cm@aric-hamburg.de
More information on our website: [https://aric-hamburg.de/veranstaltungen/ai-mix-mingle

Institutions

• Artificial Intelligence Center Hamburg (ARIC) e.V.

Cyber-physical systems are required to adapt to changing demands, often experience architectural changes over their lifetime, and generate a heterogeneous set of data. All of this leads to significant demands on monitoring and control software. This conference focuses on aspects of machine learning and related domains, such as predictive maintenance, self-optimization, fault diagnosis, re-planning, and reconfiguration. To build intelligent cyber-physical systems close cooperation between AI-research and industrial engineering is necessary. To facilitate such an exchange is the goal of this conference.

Register here: Registration

The 9th Machine Learning for Cyber Physical Systems (ML4CPS) conference offers researchers and users from various fields an exchange platform. The conference will take place March 2026, 19th till 20th at the Fraunhofer Forum in Berlin. Hosts are Fraunhofer IOSB, Helmut Schmidt University, Hamburg University of Technology, and the Chair of Production Engineering of E-Mobility Components (PEM) of RWTH Aachen.

In this year’s edition of the conference we also encourage submission of contributions from industry detailing scientific problems they encounter. To contribute, an extended abstract of a maximum of one page is required and must be submitted through the conference portal.

Institutions

• Fraunhofer IOSB
• Helmut-Schmidt-Universität Hamburg
• RWTH Aachen
• Hamburg University of Technology (TUHH)

We are calling in all AI enthusiasts in Hamburg. Let's talk and exchange thoughts and ideas!

Meet other AI and tech enthusiasts at our well-established AI Meetup, bringing together the Hamburg AI scene for more than three years. Join us for the AI Mix & Mingle at Sofabar, where you can chat casually, exchange ideas, or discuss your AI projects. There are no presentations—the focus is on networking and open conversation.

While your registration is not mandatory, it is appreciated. You would make our reporting easier if you sign up on Eventbrite. But feel free to drop by spontaneously, too, to connect with us and others, build networks, and dive into interesting conversations about AI and beyond!

We are lookimg forward to seeing you there!
For any questions, comments, or feedback, please email us at: cm@aric-hamburg.de
More information on our website: [https://aric-hamburg.de/veranstaltungen/ai-mix-mingle

Institutions

• Artificial Intelligence Center Hamburg (ARIC) e.V.

The International Conference on Computational Science is an annual conference that brings together researchers and scientists from mathematics and computer science as basic computing disciplines, as well as from other various application areas, who are pioneering computational methods in sciences such as physics, chemistry, life sciences, and engineering, as well as in arts and humanitarian fields, to discuss problems and solutions in the area, identify new issues, and shape future directions for research.

ICCS 2026 in Hamburg, Germany will be the twenty-sixth edition in this series of highly successful conferences.

The conference theme for this year is “At the Forefront of Science through Computation and Data”.

This conference will be a unique event focusing on recent developments in: scalable scientific algorithms; advanced software tools; computational grids; advanced numerical methods; and novel application areas. These innovative novel models, algorithms and tools drive new science through efficient application in areas such as physical systems, computational and systems biology, environmental systems, finance, and others.

The Hamburg Network for Artificial Intelligence and Law (NAIL) will host a conference on “AI, Finance & Law: Innovation, Integrity, and the Future of Markets” on 2–3 July 2026 in Hamburg, Germany, and invites paper submissions.

This in-person conference will seek to explore a broad range of regulatory issues in relation to, inter alia, the following aspects:

• How should financial markets law respond to the adoption of AI systems by financial institutions and intermediaries? What are the economic effects of AI-driven financial markets, and are there risks to market integrity, efficiency, and to market stability?
• What governance mechanisms ensure accountability, transparency, and auditability of AI in financial services? How can market supervisors and investors effectively monitor the integrity of new AI-driven market players?
• How does the EU AI Act interact with existing and upcoming financial regulatory frameworks? How does the AI Act and associated rules apply to financial-markets use-cases such as algorithmic trading, risk models, and credit scoring?
• How can regulators balance innovation, competition, and financial stability in regulating AI? What forms of legal experimentation (sandboxing, testbeds, proportionality tools) support safe AI adoption and ensure innovation? 
• What are cross-border challenges with regulating AI across the EU and globally? What can the EU learn from global regulatory models such as the US, UK, Singapore, China, and international standard setters?
• Twin Transformation: How can advances in AI be balanced with sustainable development and green finance?

The conference organizers invite papers from scholars, policymakers, and practitioners on each of these topics, and on any other topic of relevance to the conference theme. In particular, the organisers encourage the submission of papers that examine these topics from an interdisciplinary, international and/or comparative perspective.

Institutions

• Network for Artificial Intelligence and Law (NAIL)

This Dagstuhl Seminar seeks to ignite a focused dialogue on the strategic positioning and practical implementation of digital transformation in scientific research. Central to our discussion will be the role of Digital Centers or Hubs as flagship components of modern research infrastructure and the significance of Research Software Engineering (RSE) and Research Data Management (RDM) as essential enablers of their success.

The seminar's guiding question is: How can digital transformation be effectively embedded in the research landscape? Should it be steered centrally via comprehensive digital centers or emerge through decentralized, institution-driven initiatives? We will explore the strengths, limitations, and potential synergies of both models, with the goal of deriving actionable insights for sustainable digital infrastructure strategies.

Another focus is on the tension between disciplinary specificity and transdisciplinarity: Should digital competence centers closely align with specific research domains, or should they work across disciplines to foster collaboration and shared innovation? Understanding this balance is crucial for building effective, scalable digital ecosystems across institutions and research communities.

For more information please read here

Institutions

• Indiana University - Bloomington, US
• Universität Kiel, DE
• Universität Innsbruck, AT
• HCDS, Universität Hamburg, DE