Selbstfahrende Autos, immer ausgefeiltere Roboter und autonome Raumfahrzeuge wie beispielsweise planetare Erkundungsfahrzeuge sind allesamt Beispiele für hochkomplexe Systeme, die durch fortschrittliche Computersteuerung geregelt werden. Ihre wachsenden Fähigkeiten hängen von immer feiner abgestimmten Berechnungen und einer zunehmend präzisen Zeitsteuerung ab. Dennoch bleibt das Timing eine kritische Schwachstelle. Selbst geringfügige Abweichungen bei der Synchronisation von Rechenprozessen können sich durch ein System ausbreiten und in sicherheitskritischen Anwendungen zu schwerwiegenden oder sogar katastrophalen Ausfällen führen.

Die vom ERC geförderte Forschung wird dabei über die bloße theoretische Überprüfung, zum Beispiel die Einhaltung einer bestimmten Geschwindigkeit oder eines bestimmten Abstandes zu anderen Fahrzeugen, hinausgehen. „Wir möchten auch sicherstellen, dass diese Garantien bei der Implementierung der Systeme trotz der zeitlichen Schwankungen, die während der Ausführung unvermeidlich auftreten, weiterhin gültig bleiben“, erklärt Martina Maggio.

„Selbst die fortschrittlichsten computergesteuerten Systeme können anfällig für zeitbezogene Fehler sein“, so die Informatik-Professorin. „Der Mars-Hubschrauber Ingenuity beispielsweise erlebte gefährliche Schwingungen, die durch Fehlausrichtungen von Zeitstempeln verursacht wurden, und stieß später auf ein weiteres Synchronisationsproblem. Diese Vorfälle zeigen, dass Timing-Fehler keine seltenen Ausnahmefälle sind, sondern eine grundlegende Herausforderung bei der Entwicklung und dem Betrieb komplexer autonomer Systeme darstellen.“ Bei einem Vorfall war der Hubschrauber gezwungen, eine Notlandung durchzuführen, nachdem eine Bildverarbeitungsaufgabe nicht mehr mit anderen Bordberechnungen synchron war. Trotz dieser Rückschläge wurde „Ingenuity“ letztendlich zu einem bemerkenswerten Erfolg.

Martina Maggios Forschung konzentriert sich darauf, genau solche Ausfälle in softwaregesteuerten technischen Systemen zu verhindern – von autonomen Fahrzeugen über Industrieroboter bis hin zu Raumfahrzeugen. Dies ist besonders wichtig bei Anwendungen, bei denen das richtige Timing ebenso wichtig ist wie die korrekte Funktionalität: Wenn der Zeitpunkt kritischer Ereignisse nicht garantiert werden kann, reichen die Folgen von Leistungseinbußen bis hin zu katastrophalen Systemausfällen.

Um diese Forschung auf höchstem internationalem Niveau voranzutreiben, wurde Martina Maggio mit einem Advanced Grant des Europäischen Forschungsrats (ERC) ausgezeichnet. Seit ihrem Eintritt an die Universität des Saarlandes als Professorin für Informatik im Jahr 2020 hat sich Maggio als führende Expertin an der Schnittstelle zwischen Regelungstechnik und Echtzeitsystemen etabliert. Das vom ERC geförderte Projekt mit dem Titel SCARF (Scalable CPS Analysis of Robustness to Failures) wird 2027 beginnen und fünf Jahre dauern.

Weitere Informationen: 
Prof. Dr. Martina Maggio
E-Mail: maggio(at)cs.uni-saarland.de  

Whether it is online banking, email, video streaming, global cloud platforms, or large-scale AI infrastructures – planetary-scale distributed systems form the backbone of many societal-scale applications. We take for granted the continuous availability of these services, even though outages can cause widespread disruption. Yet today, developers do not have principled approaches to provision, analyze, or prove performance or resilience properties of such systems. Currently, developers test for such properties using expensive but inadequate workload testing, and availability outages continue to be a problem for users.

The now EU-funded project “Pascal: Formal Performance Analysis at Scale” addresses the major challenge of formally reasoning about (that is, mathematically describing and verifying) the performance and resilience of large-scale distributed systems. Its ultimate goal is to develop methodologies and tools that system developers can use to reason about implementations of their systems.

Rupak Majumdar has been a Scientific Director at the Max Planck Institute for Software Systems since 2010 and an Honorary Professor in the Department of Computer Science at the Rhineland-Palatinate University of Technology Kaiserslautern-Landau (RPTU). This is the second ERC grant he has received. In 2015, together with Michael Backes, Peter Druschel, and Gerhard Weikum, he was awarded an ERC Synergy Grant for the project ImPACT: Privacy, Accountability, Compliance, and Trust in Tomorrow’s Internet. The ERC Synergy Grant is the European Research Council’s most highly funded grant scheme.

More info from the ERC.

Derek Dreyer has set an exemplary standard of service within the PL community. Throughout the years, Derek has served in almost every possible role in our community, including General Chair of ICFP’19, Program Chair of POPL’24, and Associate Chair of OOPSLA’23 and PLDI’26. Since 2017, he is an Associate Editor of TOPLAS; since 2023, he is on the PACMPL advisory board; and since 2022, he is co-editor-in-chief of the Journal of Functional Programming, presently overseeing the transfer of the journal to Diamond Open Access. But Derek’s service work began much earlier. While still an assistant professor, he was moderator of the TYPES mailing list and volunteered to serve on the SIGPLAN Executive Committee (2012-15) as Awards Chair. In 2020, he helped safeguard the perception of programming languages research outside the field, when the CORE ranking committee threatened to demote the rankings of several major PL conferences. Derek has also been a prominent mentor for students, postdocs, and junior faculty. He chaired early editions of PLMW and co-founded the RTFM workshop on faculty mentoring (at PLDI’24 and POPL’26). He frequently speaks at such events, and is known for his widely-cited talks on speaking and writing skills: “How to Write Papers and Give Talks That People Can Follow”. Last but not least, Derek has written popular blog posts touching on the more “human” aspects of a career in research such as: accepting criticism, handling rejection, struggling to maintain a work-life balance, and impostor syndrome. In summary, Derek has served the community in many ways, always striving to promote the value and the quality of PL research, to help maintain cohesion in our community, and to empower junior researchers to conduct outstanding PL research.

The Distinguished Service Award is given by ACM SIGPLAN to recognize distinguished service contributions to the Programming Languages Community. The award recognizes contributions to ACM SIGPLAN, its conferences, publications, or its local activities. The award includes a prize of $2,500.

The report by the United Nations University (UNU) examines the environmental impacts of artificial intelligence, focusing primarily on generative AI models such as ChatGPT, Claude, and DeepSeek. Among other things, the study examines the resource requirements of data centers for training and operation, as well as the associated CO₂ emissions. As the use of generative AI increases, so does the computing capacity required for inference and training.

Prof. Maaß generally welcomes the debate but is critical of parts of the report. “The report makes a useful contribution by systematically compiling consumption figures for the first time and making them accessible to a broader audience,” he says. At the same time, he emphasizes: “The figures cited in the report are plausible in terms of their magnitude, but difficult to reproduce methodologically.”

Prof. Maaß generally welcomes the debate but is critical of parts of the report. “The report makes a useful contribution by systematically compiling consumption figures for the first time and making them accessible to a broader audience,” he says. At the same time, he emphasizes: “The figures cited in the report are plausible in terms of their magnitude, but difficult to reproduce methodologically.”

This is precisely where the ESCADE project, funded by the Federal Ministry for Economic Affairs and Climate Action, comes in. As part of this project, DFKI is researching energy- and cost-efficient approaches for operating AI applications in data centers. Using the EAVE demonstrator, energy consumption, CO₂ emissions, and operating costs of different model, hardware, and location configurations are made comparable.

In doing so, ESCADE addresses key transparency and decision-making issues that are also relevant in the context of the UN report. The scientific foundations and design principles were described, among other places, in a CAiSE publication on energy- and cost-efficient AI operations. In this way, the project helps not only to discuss the environmental impacts of AI but also to make them measurable and practically comparable.

“The energy consumption of AI data centers is real and growing, but it is not currently the dominant climate issue,” says Maaß. It is therefore crucial to consider technical development, site selection, and regulatory frameworks collectively. Against this backdrop, the question of how AI systems can be designed in the future so that their benefits do not come at the expense of unnecessarily high resource consumption is gaining importance. 

The UNU-INWEH report:https://unu.edu/inweh/collection/environmental-cost-of-AIs-Enrgy-Use-Carbon-water-and-land-footprints

Statements on the UN report:https://www.sciencemediacenter.de/angebote/un-bericht-zum-umweltfussabdruck-von-ki-und-rechenzentren-26129

Paper „Towards Decision Support Systems for Cost-Effective and Energy-Efficient AI Operations in Data Centers“: https://link.springer.com/chapter/10.1007/978-3-032-28110-4_22 

ESCADE project webpage: https://www.dfki.de/web/forschung/projekte-publikationen/projekt/escade

The formal signing ceremony took place in the presence of Dorothee Bär, German Federal Minister of Research, Technology and Space, and Philippe Baptiste, French Minister for Higher Education, Research and Space. The aim of the ambitious project is to establish a powerful European AI player at the intersection of cutting-edge research, industry, and society.

The new binational center bundles the excellent research capacities of both countries to provide viable answers to the rapid global AI transformation. In the face of intense international competition, the center makes a decisive strategic contribution to Europe’s digital sovereignty. Through a permanent, institutionalized structure and the close integration of science and industry, the development of trustworthy, transparent and competitive AI technologies “Made in Europe” is to be accelerated.
 

“The founding of the open, French-German Center marks a decisive milestone for the future of European AI,” explains Prof. Dr. Antonio Krüger, CEO of DFKI. “Through the concrete integration of the excellent AI research of Germany and France, we are moving beyond mere declarations of intent to actively create a foundation for Europe’s digital sovereignty in artificial intelligence.”

Dr. Bruno Sportisse, Chairman and CEO of Inria, adds: “This Franco-German Center is one answer to the AI challenge. We have to align our strategies and to deliver impactful projects if we want to play the race at the forefront of research, technology and innovation. This requires to have trustworthy partnerships, a joint long-term roadmap and the ability to leverage with our ecosystems (AI clusters): this is what we build with DFKI.”

The integrated “Project Factory” at the core of the Center functions as an agile innovation engine to flexibly transform bilateral research and development projects into tangible prototypes and software solutions. Furthermore, the explicitly open concept of the new Center promotes the active participation of other academic partners from both countries.

Furthermore, companies from both countries will receive direct access to projects in order to develop innovative AI applications in key sectors such as Industry 4.0, health, and mobility, and to bring them swiftly to market maturity. This research transfer is flanked by talent promotion and researcher mobility programs, which turns the Center into a highly attractive magnet for top global talent through bilateral career paths and joint summer schools. The profile is complemented by the establishment of a scientific think tank that develops well-founded recommendations for action on the social impact of AI, strengthens AI literacy among the population, and advises stakeholders from politics and business on issues regarding regulation, ethics, and standards.
 

The formal signing within the framework of Vivatech underlines the high political priority of cooperation for both governments.
 

Dorothee Bär, Federal Minister of Research, Technology and Space, declares on the occasion of the ceremony: “In today’s world, artificial intelligence (AI) is a decisive competitive factor. Hence, it was named as a key technology in the High-Tech Agenda Germany. We have to prevent Europe from being sidelined in the global AI landscape. The binational French-German Center for AI as collaboration between DFKI and Inria will help to seize emerging opportunities and leverage the combined expertise of France and Germany to drive Europe forward. It will conduct joint research on secure and trustworthy artificial intelligence, fully aligned with European standards. This partnership exemplifies how close Franco-German cooperation can shape a stronger, more innovative European AI ecosystem.”

The binational Center is deliberately not designed as a closed system. The integrated Project Factory is open to further AI research clusters, universities and scientific organizations from Germany, France and beyond, as well as partners from industry and public administration, to weave a seamless European AI network.

Following the formal signing on  June 18, the step-by-step establishment of the structures as well as the setting up of dedicated offices at the respective locations of DFKI and Inria in Germany and France will begin from July 2026, followed by the launch of the first operational programs in late 2026.

Further information can be found at: https://french-german-ai-center.org

Soofi S marks the beginning of the project’s first release phase. The model is designed for organizations that need to run AI applications transparently, adaptively, and on their own or sovereign infrastructure — for example, in industrial processes, the analysis of extensive technical and regulatory documents, code generation, or agentic AI systems. Trained from scratch on 27 trillion (27T) tokens, Soofi S is a 30 billion parameter (30B-A3B) mixture-of-experts model whose hybrid Mamba-Transformer architecture combines high throughput with low energy consumption. Soofi S has been trained primarily on English and German text and achieves top-tier results among open models in its size class in English; in German, it leads the peer group. Soofi S is initially released as a base model, which can already be fine-tuned for specific domains; post-trained variants for dialogue and agentic applications will follow.

“Whoever controls the foundation models controls a central part of future digital value creation and strengthens their sovereignty and resilience. With Soofi, we are building an open foundation on which businesses, SMEs, and the public sector can develop transparent AI applications based on their own data, without becoming permanently dependent on individual non-European models,” says Jörg Bienert, Managing Director of the Center for Sovereign AI, German AI Association.

A particular focus lies on transparency: the consortium will not only release model weights but also publish technical documentation on training methodology, data preparation, and the data pipelines used. This makes Soofi S more auditable for businesses, public authorities, and researchers, and more readily adaptable to specific use cases.

Soofi S and subsequent models are trained on Deutsche Telekom’s Industrial AI Cloud in Munich, using NVIDIA’s open-source AI framework. Initial results show that the Soofi S base model matches or outperforms international models of comparable size across German and English benchmarks.

“Soofi S is not intended as yet another general-purpose chatbot, but as a technical foundation for industrial AI. What matters is that Soofi S performs not only well in benchmarks, but can be deployed reliably, efficiently, and transparently in production,” says Nicolas Flores-Herr, Technical Project Lead for Soofi and Team Lead at Fraunhofer IAIS.

“Digital sovereignty arises where cutting-edge scientific research and industrial practice intersect directly. With ‘Soofi S,’ we are demonstrating that Europe holds the keys to the next generation of AI technologies. The DFKI is contributing its expertise here to develop models that combine performance with transparency. This is a crucial lever for providing the European economy with an independent and future-proof AI infrastructure.”

Prof. Dr. Antonio Krüger, CEO DFKI

At PLDI this year, only 10 papers were given this award out of 115 accepted papers.

DFKI and Inria have been collaborating in a bilateral partnership since 2020. The focus is on joint research projects carried out by mixed teams from both organizations. Two current projects exemplify societal challenges in Germany and France and make a concrete contribution to greater social participation. The “RoGSiLT” and “NEARBY” projects will be presented at the joint booth in the German Park.

RoGSiLT (Robust and Generalizable Sign Language Translation) is developing AI-based solutions for German and French Sign Language (DGS and LSF). Innovative AI methods aim to significantly improve translations between spoken language and sign language. The goal is to improve both the translation of text into sign language and the conversion of sign language from videos into written language. Modern techniques such as multimodal neural networks, self-supervised learning, and large language models are intended to overcome existing hurdles—such as limited data availability, lack of generalizability, and unnatural translations. A key component is the development of new data resources, including extensive parallel corpora of sign language videos and associated texts.

Project presentation: Wednesday, June 17, all day, Hall 7.3, Booth 3E14

Brain-computer interfaces (BCIs) open new avenues for human-machine interaction by using brain signals to directly control technical systems. NEARBY (Noise and variability-free BCI systems for out-of-the-lab use) develops innovative BCI systems with low noise and variability that function reliably even outside the laboratory. The goal is to create robust, practical solutions that pave the way for the use of brain-computer interfaces in everyday life—for greater self-determination, efficiency, and intuitive interaction. At the conclusion of the project, the German-French team will present the current state of research.

Project presentation: Thursday and Friday, June 18–19, all day, Hall 7.3, Booth 3E14
 

DFKI and Inria are taking their partnership to a new level: The leading research institutions will sign an agreement to establish an open, binational German-French research center for artificial intelligence.

The signing ceremony will be held in the presence of Dorothee Bär, Federal Minister for Research, Technology, and Space, and Philippe Baptiste, French Minister for Higher Education, Research, and Space. This ambitious project aims to establish a strong European AI player at the intersection of cutting-edge research, industry, and society.

German Park Stage, June 18, 10:00–10:30 a.m.

www.vivatech.com
https://www.dfki.de/en/web/qualifications-networks/international-cooperation/german-french

https://french-german-ai-center.org
 

Graduates with a Bachelor’s degree in physics, mathematics or computer science can apply for a place on the programme until 30 June.

Quantum computing is widely seen as one of the key technologies of the 21st century. The global development of powerful quantum hardware systems continues to gather pace and with it grows the demand for new algorithms, software concepts and cryptographic methods. And this is where the new Master’s programme comes in. With its focus firmly on the software side of quantum computing, it deals with the theoretical foundations of information processing in quantum systems. ‘Quantum information theory is, in a sense, the theoretical underpinning of the software used in quantum computers. It is rooted equally within the fields of mathematics, computer science and physics, and calls for an integrated and interdisciplinary perspective,’ explains Professor Moritz Weber, Scientific Director at the Center for Quantum Technologies (QuTe) at Saarland University, who has been instrumental in designing the new degree programme.

Compared with other study programmes in the quantum technologies sector, many of which are strongly physics-focused, the Saarbrücken Master’s programme is based at the Department of Mathematics and focuses particularly on mathematical and computer science aspects. The M.Sc. programme in Saarbrücken therefore offers a route into the world of quantum research even for students with no prior background in physics. ‘At its core, the programme addresses the fundamental questions raised by the development of quantum computing technology: How do you actually program a quantum computer? In what way does it function differently from a classical computer? What characterizes quantum computing and what does that have to do with mathematics,’ says Moritz Weber. Students on the programme acquire a solid grounding in areas such as quantum algorithms and the mathematical foundations of quantum information. Mandatory elective modules allow students to specialize in areas such as quantum complexity, quantum error correction or other research fields of current interest.

A particularly attractive feature of the Master’s programme is that students gain early exposure to the questions of current research relevance. This is possible because of the close links that exist between the study programme and the recently established Center for Quantum Technologies, and the collaborative ties with other leading research institutes in Germany, including the Helmholtz Center ‘Forschungszentrum Jülich’. Students can also gain practical experience through a supervised internship – either in a research or industry setting. The programme also offers flexible study pathways, enabling students to combine quantum computing equally with either classical computer science or mathematics. This flexibility allows them to tailor their studies to their individual interests and longer-term career aims.

Graduates from the programme will be highly sought-after specialists in a very innovative and fast-growing sector. Career opportunities range from research and development to the quantum computing industry and the IT and cybersecurity sectors, for example in post-quantum cryptography. Further prospects include professional roles in software development, data analysis and high-performance computing. At the same time, the programme provides targeted preparation for an academic career, including doctoral study in the broader field of quantum science.

The Master’s programme is taught entirely in English and has been intentionally designed to appeal to international students as well. The standard period of study is four semesters, and the programme leads to a Master of Science degree. The deadline for applications for the coming winter semester is 30 June.

Further information and details about how to apply on this Website.

Thanks to €48 million in support from European and national funding sources, the RICAIP (Research and Innovation Centre on Advanced Industrial Production) project has created an interconnected ecosystem of industrial testbeds at CIIRC CTU and CEITEC BUT in Brno, linked with leading German research centres DFKI and ZeMA, as well as additional partner institutions across Europe. The testbeds enable systematic development and testing of new approaches in industrial AI, robotics, distributed manufacturing, and advanced automation under conditions close to real-world industrial operations, significantly strengthening the ability to transfer research results into industrial practice.

“RICAIP is a truly European effort. At the intersection of education, research, innovation and industrial development, we have built a technological infrastructure and a network of teams in the Czech Republic and German that can be a leader in the future of Industry 4.0. We have set up the RICAIP testbeds and filled them with an ecosystem of collaboration with many stakeholders. At the same time, it is an ongoing process of setting up a sustainable format as the RICAIP Centre and continuing to expand European cooperation.”

Dr. Tilman Becker, RICAIP Director

The conference opened a broader discussion on how intelligent physical systems, autonomous robotics, and AI-driven manufacturing will shape the future of European industry. Keynote speakers included Prof. Wolfgang Wahlster from DFKI, one of the founding figures of Industry 4.0, and Prof. Duncan McFarlane from the University of Cambridge, a leading expert in industrial intelligence systems and digital twins. The programme also featured Valentina Ivanova, Deputy Director for European and International Affairs at CEA-List and coordinator of the European AI-MATTERS initiative focused on testing and experimentation facilities for AI in manufacturing. Their contributions provided a forward-looking perspective on industrial AI, robotics, and intelligent physical systems in a European context.

The interaction between artificial intelligence and the physical world is one of the key scientific and technological challenges of our time, with a profound impact on the future of manufacturing, logistics, and other industrial sectors,” said Prof. Vladimír Mařík, Scientific Director of CIIRC CTU and principal investigator of the RICAIP project. “RICAIP has created a strong environment for the development of the Czech AI ecosystem and has significantly contributed to new initiatives such as the Czech AI Factory“.

According to Prof. Mařík, close cooperation between Czech institutions and German partners DFKI and ZeMA has played a crucial role. “Thanks to this collaboration, CIIRC CTU in Prague and CEITEC BUT in Brno are now recognised as respected European centres of excellence in industrial AI, also involving VSB – Technical University of Ostrava. At the same time, we are working intensively to ensure the long-term sustainability of both the infrastructure and research potential, as European industry will require strong scientific and technological support during the ongoing digital transformation.” 

“Collaboration initiated within RICAIP contributes to European digital sovereignty in the field of industrial artificial intelligence. Close cooperation and the shared use of state-of-the-art test environments have created a European innovation ecosystem that enables us to independently develop, scale, and deploy key technologies in industrial AI.”

Prof. Antonio Krüger, CEO DFKI

The importance of interconnected testbeds was also highlighted by representatives of individual sites. “The future of industrial AI is not created in isolated laboratories, but in interconnected research infrastructures where technologies, expertise, and experiments can be shared across countries,” said Khansa Rekik from ZeMA. “Within RICAIP, we were able to connect locally developed robotic and AI solutions into broader distributed manufacturing scenarios.”

“RICAIP represented a major qualitative leap for our testbed,” added Dr. Pavel Burget, Director of the RICAIP Testbed Prague. “We have created an environment where cutting-edge research meets real industrial applications – from autonomous robotic manipulation and digital twins to AI-based quality inspection in extremely short production cycles.” 

“Long-term international cooperation and shared research infrastructures are key to developing future technologies. For our institute, participation in such initiatives is an opportunity not only to advance research, but also to transfer its results into industrial practice and strengthen European competitiveness in AI and advanced manufacturing,” confirmed Prof. Radimír Vrba, Director of CEITEC BUT in Brno.

The importance of cooperation between research and industry was also emphasised by representatives of the industrial sector. “Strengthening Europe’s competitiveness requires much closer cooperation between research and industry. Initiatives such as collaboration between companies, CIIRC CTU, and infrastructures like RICAIP clearly demonstrate how research results can be transformed into real industrial value. Digitalization, automation, and artificial intelligence will be the key drivers of transformation in European industry in the coming decade. At the same time, we need an environment that motivates companies to invest in research and innovation,” said Martin Jahn, Member of the Board for Sales and Marketing at Škoda Auto, Vice-President of the Confederation of Industry of the Czech Republic, and President of AutoSAP.

“If Europe is to remain competitive on the global stage, we cannot innovate in isolation,” added Eduard Palíšek, CEO of Siemens Czech Republic. “Close collaboration between industry and academia, such as that represented by CIIRC CTU and the RICAIP testbeds, allows us not only to validate new technologies in real industrial environments, but also to jointly address challenges such as manufacturing resilience and cybersecurity. True competitiveness is not built on new technologies alone, but also on the courage to share know-how and push the boundaries of what digitalization makes possible.“ 

RICAIP Days 2026 thus represented not only the conclusion of a successful European project, but above all the beginning of a new phase of European cooperation in industrial AI, intelligent physical systems, and technology transfer between research and industry.

The conference was followed by Tech Dating 2026, an open day at CIIRC CTU for companies, organised in cooperation with EDIH CTU, AI-MATTERS, the National Centre for Industry 4.0, CzechInvest, and other partners. It offered hands-on consultations, technology demonstrations, and the opportunity to discuss concrete challenges in AI, automation, and digitalisation directly with research teams from CIIRC CTU and partner institutions.

The Fonds der Chemischen Industrie (FCI) is funding the project led by Professors Tanja Gulder and Andrea Volkamer to the tune of €80,000 as part of a special funding programme designed to make data science a permanent part of chemistry degree programmes. 

The following text has been machine translated from the German with no human editing.

Whether substances are being analysed, experiments conducted, new active compounds tested or theoretical models examined: everything that takes place in a chemistry laboratory generates data. Without these measurements and observations, nothing works – if they are not recorded, the results of even the best work are lost. What has been true since the dawn of Chemistry is even more so today. “Data and its processing are an indispensable foundation for research and development. New computer-aided methods, including artificial intelligence, are creating new ways to achieve research results using large amounts of data and to make them usable for industry and society,” explains Tanja Gulder, Professor of Organic Chemistry at Saarland University. She researches and develops sustainable chemical processes modelled on nature, including for novel and improved active substances, using digital computer methods. 
“Technology is significantly transforming the chemistry and pharmaceutical industries. This is also changing the demands placed on the specialists working in these fields. Industry is looking for chemists who possess knowledge of data, its machine- -based processing and the use of AI,” says Tanja Gulder. Chemistry education must catch up and integrate digital methods into teaching from the very start. “So far, the Chemistry curriculum in Germany has not covered this area sufficiently. Even some PhD students today are reluctant to work with data. That is why we want to introduce digital content into Chemistry degree programmes using a new teaching concept, starting with the Bachelor’s degree and continuing throughout to the Master’s degree,” explains Gulder. 

To this end, the chemist at Saarland University is collaborating with Andrea Volkamer, Professor of Data-Driven Drug Design. The computational chemist develops computer-based methods—encompassing both algorithmic approaches and AI models—to predict which drug candidates are the most promising; she is also a specialist in digital teaching methods. “Knowledge of the use of artificial intelligence needs to be better integrated into the curriculum in general,” emphasises Andrea Volkamer.

The two researchers are now receiving funding for their project under the special funding programme of the Chemical Industry Fund (FCI): the Saarbrücken application was successful in a nationwide competition alongside 22 other universities and colleges. Numerous institutions had submitted applications for funding. The Saarbrücken project concept will receive 80,000 euros in funding over three years. In total, the fund is investing 1.6 million euros in data science within Chemistry degree programmes to embed innovative teaching concepts on AI, big data and laboratory automation in higher education.

Over the next three years, Gulder and Volkamer will develop a teaching concept with their teams. “The concept is intended to serve as a sustainable model,” says Andrea Volkamer. Its modules will initially be developed within the Department of Organic Chemistry at Saarland University, but they are intended to be applicable beyond the boundaries of this discipline – generally across the life sciences, such as in Pharmaceutical Science or biotechnology – and beyond the Saarbrücken campus to other universities. 

The new concept for the introductory bachelor’s practical course aims to teach students the basics of working with data and data management – in other words, how to generate data as the foundation for machine learning and how to store it in a way that is both useful and retrievable by third parties. “We also want to teach students the ‘FAIR’ principles of research data management,” explains Tanja Gulder. FAIR stands for the initial letters of the English terms ‘findable’, ‘accessible’, ‘interoperable’ and ‘reusable’. “The advanced practical course will, among other things, focus on introducing students to working with databases such as electronic lab notebooks and providing them with a basic understanding of AI, machine learning and programming languages. The aim is to equip them with the tools to analyse large volumes of data, identify complex patterns and correlations, optimise synthesis routes or predict reaction outcomes,” explains the chemist.

Gulder, who is involved in two major collaborative research centres and two Research Training Groups run by the German Research Foundation (DFG), is working alongside colleagues at the University of Leipzig to set up another major research project in the field of digital Chemistry: the aim here will be to advance chemical research for drug discovery using modern computer-aided methods, including artificial intelligence. “With this new teaching concept, we are also training the next generation of chemists who will be working on this research project,” says Gulder, explaining her long-term goals.

The Chemical Industry Fund was established in 1950 and is the funding body of the German Chemical Industry Association. The Faculty of Natural Sciences and Technology and the Chemistry department at Saarland University are contributing an additional 20 per cent of the funding as an investment in the quality of teaching.

For further information:

Prof. Dr Tanja Gulder: Email: tanja.gulder@uni-saarland.de

Prof. Dr Andrea Volkamer: Email: volkamer@cs.uni-saarland.de

Press photos available for download:
Press photos can be found on this news website: 

https://www.uni-saarland.de/aktuell/ki-im-Chemistry-studium-47017.html
You may use the press photos free of charge in connection with this press release and reporting on Saarland University, provided you credit the photographer.

‘Software solutions are embedded in our everyday lives, and when they are faulty the consequences can be serious. So, it‘s essential that programmers understand their code and don‘t overlook errors or introduce new ones when adding further functionality,’ says Sven Apel, professor of computer science at Saarland University. Apel and his colleagues want to understand more precisely what happens in a software developer’s brain when writing and analysing code. Three years ago, he brought Axel Mecklinger, professor of experimental neuropsychology at Saarland University, into the project. Together, they combined electroencephalography (EEG) with eye-tracking data to record signals known technically as fixation-related potentials (FRPs). ‘The advantage of the FRP approach is that it allows us to record brain activity at the exact moment when the eyes stop moving and focus on a specific target,’ explains Axel Mecklinger.

The research team set out to discover how software developers react when they encounter confusing snippets of code known as ‘atoms of confusion’. These small portions of code occur quite frequently in source code and cause a person and a machine to come to different conclusions regarding the output. While the computer can interpret and execute them unambiguously, they are not intuitively clear to the programmer, which means the programmer may misunderstand how the program works. Anna-Maria Maurer, a doctoral research student in computer science working with Professor Apel, incorporated this type of confusing code into the experimental design. She recruited 24 programmers as participants, whose brain activity and eye movements were recorded over around 1,700 trials.

To analyse the measurement data, the team drew on methods and expertise from psycholinguistics, although the methodology could not simply be transferred to the study of software programming. Earlier studies had already shown that programming activates brain regions similar to those involved in natural language processing, but the way programmers approach code differs from the way people process language. ‘When we want to understand how the brain processes particular conversational situations, we ask participants to read short text passages and compare this with the EEG and eye-tracking data. But when reading code, programmers process larger contextual blocks, scanning several lines at once and perceiving complex structures as single units,’ explains Vera Demberg, professor of computational linguistics, who with her team was involved in analysing the data. To take this added complexity into account, the experimental set-up and design had to be correspondingly more sophisticated. The code snippets were presented to the participants in three thematic blocks, with each block comprising 24 individual trials, while EEG and eye-movement data were recorded and synchronized to the millisecond.

When the team compared EEG signals from earlier natural language studies with the new findings from their software programming study, they identified a striking pattern known in neuropsychology as late frontal positivity. ‘When the programmers encountered confusing snippets of code, they showed brain activity similar to that seen in linguistic experiments where participants read sentences containing unexpected turns of phrase. The brain then adapts in a split second, checking the information against long-term memory and updating the mental representation of the new situation in order to make sense of it,’ explains Vera Demberg. To illustrate what’s happening, Axel Mecklinger cites the sentence ‘Theo wants to chop wood, so he goes to fetch a jacket.’ as an example of just such an unexpected turn in conversation. Upon encountering the words ‘goes to fetch’ the reader would normally expect this to be followed by ‘an axe’. A jacket, by contrast, is certainly plausible, but still comes as a surprise in this context. ‘In our EEG experiments on language processing, unexpected words such as “jacket” generate a late frontal positivity – a signal that bears a very strong resemblance to the EEG response elicited by confusing code snippets,’ says neuropsychologist Axel Mecklinger.

‘Because programmers spend 70 to 80 percent of their time trying to understand code, it’s important that we understand how their thought processes work. The insights we gain can help us develop better tools that either eliminate coding pitfalls from the outset or make them easier to detect. These findings could also inform how we go about training software developers,’ explains computer scientist Sven Apel. In future studies, he hopes to investigate whether programmers show different patterns of brain activity when the confusing snippets of code are actually faulty, or when they are shown lines of code that do not require spontaneous rethinking, i.e. spontaneous revision of the programmer’s mental representation of the situation.

The study, published in the prestigious journal Scientific Reports, involved Annabelle Bergum, Anna-Maria Maurer, Norman Peitek, Regine Bader, Axel Mecklinger, Janet Siegmund, Vera Demberg and Sven Apel. All of the authors are researchers at Saarland University, with the exception of Janet Siegmund, who is professor of software engineering at Chemnitz University of Technology. The study is linked to several major research programmes at Saarland University and received funding from them. These include the Transregional Collaborative Research Centre 248, ‘Foundations of Perspicuous Software Systems’ (co-spokesperson: Professor Holger Hermanns), the ERC Advanced Grant ‘Brains on Code’ (PI: Professor Sven Apel), and the Collaborative Research Centre 1102 on Information Density and Linguistic Encoding (spokesperson: Professor Elke Teich), in which Regine Bader, Vera Demberg and Axel Mecklinger are involved.

Original publication:
Annabelle Bergum, Anna-Maria Maurer, Norman Peitek, Regine Bader, Axel Mecklinger, Vera Demberg, Janet Siegmund and Sven Apel, Fixation-related potentials reveal that confusing program code elicits a late frontal positivity. In: Scientific Reports 16, 16833 (2026): https://doi.org/10.1038/s41598-026-50946-9 

Further information:
Chair of Software Engineering: https://www.se.cs.uni-saarland.de 

Questions can be addressed to:
Professor Sven Apel
Chair of Software Engineering
Saarland University
Tel.: +49 681 302-57211
Email: apel(at)cs.uni-saarland.de 

The IEEE/CVF Conference on Computer Vision and Pattern Recognition, or CVPR for short, is one of the most important conferences in the field of computer vision research and took place this year from 3 to 7 June in Denver. The DFKI was represented there with several accepted papers from various areas of research. The focus was on a paper from the Augmented Vision research group that addresses a key weakness in current 3D scene analysis: systems recognise objects but often fail to understand how they relate to one another.

The DFKI contributions to the main conference cover a broad spectrum of visual AI. From the Augmented Vision research area come “ReLaGS: Relational Language Gaussian Splatting”, “DriverGaze360: OmniDirectional Driver Attention with Object-Level Guidance”, “LiREC-Net: A Target-Free and Learning-Based Network for LiDAR, RGB, and Event Calibration”, and “SIMSPINE: A Biomechanics-Aware Simulation Framework for 3D Spine Motion Annotation and Benchmarking”. 

These are joined by “OpenMarcie: A dataset for multimodal action recognition in industrial environments” and “When Pretty Isn’t Useful: An investigation into why modern text-to-image models fail as reliable generators of training data”, as well as “YieldSAT: A multimodal benchmark dataset for high-resolution yield prediction” from Kaiserslautern, “Synthesising Visual Concepts as Vision-Language Programs” from Darmstadt, and “SceMoS: Scene-Aware 3D Human Motion Synthesis by Planning with Geometry-Grounded Tokens” from Saarbrücken. Collectively, the topics range from open 3D scene understanding and multimodal perception to sensor calibration, medical simulation, synthetic training data and generative motion modelling.

Within this spectrum, ReLaGS stands out. The paper by Yaxu Xie, Abdalla Arafa, Alireza Javanmardi, Christen Millerdurai, Jia Cheng Hu, Shaoxiang Wang, Alain Pagani and Didier Stricker combines a hierarchical 3D scene representation with an explicit scene graph that models relationships between objects. This makes it possible not only to identify objects within a scene, but also to process relational queries such as ‘the cup next to the laptop’ or more nuanced part-whole relationships within complex 3D environments.

The method is based on Gaussian splatting, a state-of-the-art technique for high-resolution 3D reconstruction. ReLaGS supplements this with linguistic semantics and relational reasoning, organises scenes hierarchically – from parts through objects to the entire space – and does not require scene-specific training.

“With ReLaGS, we have shown that 3D scene understanding need not stop at the recognition of individual objects. The key lies in modelling relationships, hierarchies and semantic contexts together – only then does reconstruction truly become machine understanding.”

In the paper, the researchers report that ReLaGS generates a complete scene graph in under 15 minutes and renders at over 200 frames per second. Compared to RelationField, the approach is therefore 4.7 times faster and 7.6 times more memory-efficient. On benchmarks for open 3D segmentation, scene graph prediction and relation-guided instance segmentation, ReLaGS also achieves state-of-the-art results. 

This is relevant to research because 3D scene understanding is increasingly needed in areas where machines are required to operate safely and contextually in complex environments: in robotics, XR, industrial digital twins, or semantically rich human-machine interfaces. ReLaGS demonstrates how geometric reconstruction, linguistic semantics and relational structure can be integrated into a single framework.

In addition to the Main Conference, DFKI was also represented in other formats at CVPR 2026. From the Augmented Vision research group, “GHOST: Fast Category-Agnostic Hand-Object Interaction Reconstruction from RGB Videos Using Gaussian Splatting” and “ReConText3D: Replay-based Continual Text-to-3D Generation” were accepted as findings posters. “TAUE: Training-free Noise Transplant and Cultivation Diffusion Model” was also featured among the Findings posters. 

In addition, there were workshop presentations entitled ‘Probing the Reliability of Driving VLMs: From Inconsistent Responses to Grounded Temporal Reasoning’ at the AUTOPILOT workshop, and ‘Inpaint360GS: Efficient Object-Aware 3D Inpainting via Gaussian Splatting for 360° Scenes’ at the SPAR-3D workshop. This demonstrated DFKI’s presence at CVPR 2026 not only at the main conference but also in formats where current methodological issues and new fields of application are discussed.

• ReLaGS: Relational Language Gaussian Splatting – Yaxu Xie, Abdalla Arafa, Alireza Javanmardi, Christen Millerdurai, Jia Cheng Hu, Shaoxiang Wang, Alain Pagani, Didier Stricker 
• DriverGaze360: OmniDirectional Driver Attention with Object-Level Guidance – Shreedhar Govil, Didier Stricker, Jason Rambach 
• LiREC-Net: A Target-Free and Learning-Based Network for LiDAR, RGB, and Event Calibration – Aditya Ranjan Dash, Ramy Battrawy, René Schuster, Didier Stricker 
• SIMSPINE: A Biomechanics-Aware Simulation Framework for 3D Spine Motion Annotation and Benchmarking – Muhammad Saif Ullah Khan, Didier Stricker 
• OpenMarcie: Dataset for Multimodal Action Recognition in Industrial Environments – Hymalai Bello, Lala Ray, Joanna Sorysz, Sungho Suh, Paul Lukowicz 
• When Pretty Isn’t Useful: Investigating Why Modern Text-to-Image Models Fail as Reliable Training Data Generators – Krzysztof Adamkiewicz, Brian Moser, Stanislav Frolov, Tobias Christian Nauen, Federico Raue, Andreas Dengel 
• SceMoS: Scene-Aware 3D Human Motion Synthesis by Planning with Geometry-Grounded Tokens – Anindita Ghosh, Vladislav Golyanik, Taku Komura, Philipp Slusallek, Christian Theobalt, Rishabh Dabral 
• GHOST: Fast Category-Agnostic Hand-Object Interaction Reconstruction from RGB Videos Using Gaussian Splatting – Ahmed Tawfik Aboukhadra, Marcel Rogge, Nadia Robertini, Abdalla Arafa, Jameel Malik, Ahmed Elhayek, Didier Stricker 
• Probing the Reliability of Driving VLMs: From Inconsistent Responses to Grounded Temporal Reasoning – Chun-Peng Chang, Chen-Yu Wang, Holger Caesar, Alain Pagani 
• Inpaint360GS: Efficient Object-Aware 3D Inpainting via Gaussian Splatting for 360° Scenes – Shaoxiang Wang, Shihong Zhang, Christen Millerdurai, Rüdiger Westermann, Didier Stricker, Alain Pagani 
• ReConText3D: Replay-based Continual Text-to-3D Generation – Muhammad Ahmed Ullah Khan, Muhammad Haris Bin Amir, Didier Stricker, Muhammad Zeshan Afzal
• TAUE: Training-free Noise Transplant and Cultivation Diffusion Model – Daichi Nagai, Ryugo Morita, Shunsuke Kitada, Hitoshi Iyatomi
• YieldSAT: A Multimodal Benchmark Dataset for HighResolution Crop Yield Prediction – Miro Miranda, Deepak Pathak, Patrick Helber, Benjamin Bischke, Hiba Najjar, Francisco Mena, Cristhian Sanchez, Akshay Pai, Diego Arenas, Matias Valdenegro-Toro, Marcela Charfuelan, Marlon Nuske, Andreas Dengel
• Synthesizing Visual Concepts as Vision-Language Programs – Antonia Wüst, Wolfgang Stammer, Hikaru Shindo, Lukas Helff, Devendra Singh Dhami, Kristian Kersting

Jointly presented by the ACM Symposium on Principles of Distributed Computing (PODC) and the EATCS Symposium on Distributed Computing (DISC), the prize recognizes work that has had significant impact on the theory and practice of distributed computing over at least a decade. This years awardees are Atish Das Sarma, Stephan Holzer, Liah Kor, Amos Korman, Danupon Nanongkai, Gopal Pandurangan, David Peleg, and Roger Wattenhofer. Their paper shows that in distributed graph computations, the data links between machines form the key bottleneck. The system’s performance is thus fundamentally constrained by the bandwidth of these connections. This insight helped to define the modern theory of bandwidth-constrained distributed computing, as mentioned in the award citation.

Originally published at the ACM Symposium on Theory of Computing (STOC) in 2011 and later in the SIAM Journal on Computing in 2012, the paper introduced a framework to determine the fundamental limits of distributed computing, a method where multiple computing systems act as a single unit. By connecting communication theory with network verification, the authors created a systematic way to prove the minimum time required to solve various problems. This applied to many key tasks, such as finding the shortest path or minimum cuts. Today, these methods are standard tools in the field. Also, the insights presented in the paper have shaped subsequent research, such as extending the framework to new problems and designing algorithms with matching bounds.

The 2026 Dijkstra Prize Committee comprises James Aspnes (Yale University), Keren Censor-Hillel (Technion), Cyril Gavoille (University of Bordeaux), Seth Gilbert (National University of Singapore), Andrzej Pelc (Université du Québec en Outaouais), and Eric Ruppert (York University); the award will be presented at PODC 2026.

Danupon Nanongkai is a Scientific Director at the Max Planck Institute for Informatics in Saarbrücken, Germany since 2022, where he heads the Algorithm and Complexity department. He received a Ph.D. in Algorithms, Combinatorics, and Optimization (ACO) from Georgia Tech in 2011 and a docent (aka habilitation) in Computer Science from KTH Royal Institute of Technology, Sweden, in 2017.

His research focuses on graph algorithms and computational complexity, with particular interest in developing algorithmic techniques that are effective across a range of computational models. He has contributed to efficient algorithms for fundamental graph problems, such as connectivity and distances, in settings ranging from sequential to distributed and dynamic algorithms.

Further information:
Prize Announcement by PODC/DISC: https://www.podc.org/2026-edsger-w-dijkstra-prize-in-distributed-computing/
Website of the Algorithms and Complexity department: https://www.mpi-inf.mpg.de/de/departments/algorithms-complexity

Editor:
Philipp Zapf-Schramm
Max Planck Institute for Informatics
Phone: +49 681 9325 4509
Email: pzs@mpi-inf.mpg.de

The Saarland Ministry of Economic Affairs, in cooperation with the Saarland Informatics Campus, has presented the Journalism Prize for Informatics. The German Informatics Society is a partner of the prize. The main prizes were awarded to a radio feature by Austrian Broadcasting (ORF), an article from the magazine “c’t – Magazin für Computertechnik” , and an online piece by Swiss Radio and Television (SRF). A special prize was awarded to an article in the children’s science magazine “GEOlino.”

The Journalism Prize for Informatics was first announced in 2006 and is endowed with a total of 16,000 euros. The prize money for the main awards in the three categories “Text,” “Audio,” and “Video and Multimedia,” each endowed with 5,000 euros is provided by the Saarland Ministry of Economic Affairs, Innovation, Digitalization, and Energy. Additionally, the German Research Center for Artificial Intelligence (DFKI) is once again sponsoring a special prize endowed with 1,000 euros this year. The goal of the Journalism Prize for Informatics is to promote high-quality reporting on informatics topics beyond specialist circles.

Jürgen Barke, Saarland’s Minister of Economic Affairs, Innovation, Digitalization, and Energy and patron of the prize, says: “With the Journalism Prize for Informatics, we honor outstanding and critical reporting on digital topics while strenghtening trust in complex technologies. Journalists make the opportunities and risks of informatics understandable, promote digital education, and enable citizens to form their own well-founded opinions—a central contribution to social responsibility in the age of artificial intelligence.”

This year, the jury evaluated a total of 84 submissions. The jury of the Journalism Prize for Informatics consists of Peter Bylda, a long-time editor of the Saarbrücker Zeitung and now a freelance journalist; Peter Hergersberg, editor-in-chief of the science magazine MaxPlanckForschung; Isabel Münch, Fellow of the German Informatics Society; Dr. Wolfgang Pohl, Managing Director of the nationwide informatics competitions; Florian Possinger from Saarländischer Rundfunk; Vera Sikes, Head of Department at the Federal Office for Information Security and Head of the BSI Saarbrücken office; Dr. Christel Weins, a scientist and co-founder of the journalism prize; freelance technology and science journalist Peter Welchering; and Prof. em. Dr. Dr. h.c. Reinhard Wilhelm, Professor of Informatics at Saarland University and long-time Director of the Leibniz Center for Informatics at Schloss Dagstuhl.

The main prize in the “Text” category, endowed with 5,000 euros, goes to Greta Friedrich for her article “Koste es, was es wolle: Big-Tech-Unternehmen verschwenden mit ihren Investitionen Ressourcen,” published on September 10, 2025, in the magazine “c’t – Magazin für Computertechnik” and on heise online. The article is available at:

https://www.heise.de/ratgeber/Wie-Big-Tech-Unternehmen-Umwelt-und-Mensch-gefaehrden-10508672.html

Jury’s Statement: In her article, Greta Friedrich highlights the devastating consequences of the AI boom for the environment and people. Using numerous examples and studies, she describes how major tech corporations recklessly consume resources in their “gigantomania” to stay ahead in the race for AI market leadership. The piece reports on overloaded power grids and (re)commissioned nuclear power plants supplying energy to data centers. It also addresses water shortages in regions surrounding these centers, as vast amounts are diverted to cool AI accelerators. Additionally, the article examines the psychological strain on workers fine-tuning language models. It provides an overview of the current state of affairs and compellingly argues that every use of AI should be questioned. The piece holds tech corporations accountable while raising awareness among users. An outstanding contribution to a socially explosive and highly relevant topic.

The main prize in the “Video & Multimedia” category, endowed with 5,000 euros, goes to Julian Schmidli, Pascal Albisser, Keto Schumacher, and Marina Kunz for their online article “Der toxische Sog der Manosphere,” published online on December 4, 2025, by Swiss Radio and Television (SRF). The piece is available at: https://www.srf.ch/news/schweiz/radikalisierung-auf-tiktok-der-toxische-sog-der-manosphere

Jury’s Statement: The visually sophisticated online feature by Julian Schmidli, Pascal Albisser, Keto Schumacher, and Marina Kunz powerfully demonstrates how quickly young people can be drawn into the so-called “Manosphere” on TikTok—a social media subculture defined by toxic masculinity, misogyny, and self-loathing. The piece reveals a disturbing reality: Within just five minutes of scrolling, the team’s test accounts encountered the first toxic content from this environment. A dangerously escalating trend with measurable impacts on the mental health of young men, as the authors substantiate with research. Through its multimedia approach—featuring striking graphics, embedded videos, and illustrations—the contribution explores multiple facets of the issue while creating its own compelling narrative pull, making it nearly impossible to look away. Especially relevant in the context of current debates on potential social media bans for minors, this is a highly insightful and urgent piece of journalism.

The main prize in the “Audio” category, endowed with 5,000 euros, goes to Sarah Kriesche for her radio feature „Wie Algorithmen unser Leben formen“, the fourth installment of a series on algorithms, broadcast on May 8, 2025, on Austrian Broadcasting Corporation (ORF) Ö1. The episode is available online at: https://oe1.orf.at/programm/20250508/794317/Wie-Algorithmen-unser-Leben-formen-4

Jury’s Statement: In a society increasingly shaped by algorithms, Sarah Kriesche explores a critical question: Which decisions should machines be allowed to make, and which must remain the domain of humans? The piece opens with a striking example from the Netherlands, where an AI system falsely accused people of welfare fraud for years—immediately establishing a strong sense of the stakes involved. From there, the contribution examines multiple dimensions of an algorithm-driven society: It explains the fundamentals of machine learning, addresses the problematic anthropomorphization of AI (the attribution of human traits and emotions), and tackles key questions of accountability, power, and transparency. It also considers how to empower citizens to engage critically with these systems. MAde accessible by fitting statements and musical interludes, the piece delivers an engaging listening experience while covering a breadth of topics. The jury particularly commends the meticulousness and accuracy with which this complex subject matter was handled.

The €1,000 Special Prize from the German Research Center for Artificial Intelligence (DFKI) is awarded to David Krenz for his article “So klappt’s mit der KI,” published on September 12, 2025, in GEOlino, the science magazine for children.

Jury’s Statement: In GEOlino, David Krenz takes on the challenging task of making complex computer science topics accessible to young readers. Using clear, age-appropriate language and engaging visuals, he explains how AI systems work, highlights practical applications, and addresses potential risks. Carefully selected experts help contextualize the content, while firsthand accounts from young AI users create relatable connections to children’s everyday lives. The jury particularly emphasizes the importance of introducing children to new technologies early and fostering a reflective, informed approach. David Krenz achieves this exceptionally well in his three-part series on AI, with the award-winning first installment standing out as a prime example of how to engage young audiences with cutting-edge topics.

Background Saarland Informatics Campus

To support this work, Höller will receive funding of up to €1.8 million through the German Research Foundation’s (DFG) Emmy Noether Programme.

The following text has been machine translated from the German with no human editing.

When planning complex processes, it is advantageous if the systems used can react flexibly to changes in the environment. ‘The advantage of systems from automated planning is that they can solve different problems without the system itself needing to be changed. They operate based on a model, a simplified description of the problem,’ explains Daniel Höller, an research associate at Saarland University. The behaviour of these model-based systems is mathematically provable and therefore reliable. It is also possible to explain exactly why a particular behaviour occurs. ‘However, these systems also have some disadvantages. In particular,  they may solve small problems but require a great deal of computing time once the problems become larger. Furthermore, the model must also be adapted to minor changes, making it relatively inflexible,’ explains Daniel Höller.

 For this reason, researchers are increasingly using machine learning algorithms in automated planning. Such computer programmes have the advantage that they can adapt flexibly and are more scalable. They can therefore be trained on small-scale scenarios and then also work for large-scale applications. ‘Compared to systems from automated planning, however, behaviour based purely on machine learning is difficult to interpret or explain to a human. Why, for example, does the robot do what it does?’ says the computer scientist, who has a doctoral degree in Computer Science.

 His aim is therefore to develop planning systems that combine traditional, explainable techniques with machine learning. ‘This combination is useful not only when solving planning problems, but also right from the model-building stage. If, for example, you look at a city’s road network and want to predict how long a particular journey will take, factors such as the day of the week, the time of day or weather conditions come into play. Using machine learning techniques, these factors can be incorporated into the model and thus into the planning process," explains Daniel Höller.

 A main application of machine learning in the context of automated planning is  to speed up the systems and find solutions more quickly. ‘Here, we will be working in particular on systems that can provide guarantees despite the integration of machine learning, such as the optimality of the resulting behaviour,’ explains the Computer Science expert. In addition to this integration of machine learning techniques into planning systems, work is also being carried out in the opposite direction. ‘We want to use techniques from automated planning to prove that following a learned action policy can never result in unsafe states,’ explains Daniel Höller, who has previously been researching the fundamentals of AI in Professor Jörg Hoffmann’s group at Saarland University. 

Daniel Höller’s research project on ‘Neuro-Symbolic Methods in Sequential Decision Making’ was successful in a special call for proposals on ‘Artificial Intelligence Methods’ under the Emmy Noether Programme. An internationally renowned panel of experts selected 36 out of 178 outline project proposals for submission of a full application. Of these, only 15 were selected for funding. Daniel Höller will now receive – subject to a successful interim evaluation – a total of 1.8 million euros to establish an Emmy Noether Group. Through the Emmy Noether Programme, the German Research Foundation (DFG) supports exceptionally qualified researchers in the early stages of their careers whose doctoral degrees were awarded no more than four years ago, who have international experience and who have completed a postdoctoral phase. 

Further information:

Emmy Noether Programme of the German Research Foundation (DFG): 

Press release on the call for proposals ‘Methods of Artificial Intelligence’

Emmy Noether Programme website 

Daniel Höller’s website:  https://fai.cs.uni-saarland.de/hoeller/

For further information, please contact:

Dr. Daniel Höller
Academic Research Associate
Foundations of Artificial Intelligence (FAI) Group
Email: hoeller(at)cs.uni-saarland.de

This new phase of the CRN focuses on understanding the heterogeneity of Parkinson’s disease and why it varies from person to person. To this end, research will be advanced to enable more precise diagnostics and the development of improved therapies. Novel resources will be created to enable the global research community to work on a shared, high-quality basis and to overcome technical barriers that currently impede drug development.

For over a decade, Andreas Keller, Professor of Bioinformatics at Saarland University, and his team have been researching neurodegenerative diseases such as Parkinson’s and Alzheimer’s. Their work focuses on microRNAs, which are short, non-coding segments of ribonucleic acid (RNA) that regulate the translation of genetic information within cells. ‘Analysing them generates huge amounts of sequencing data, which we process using our bioinformatics methods. As part of the newly approved funding, we will have access to over a hundred terabytes of data from Parkinson’s patients,’ explains Andreas Keller. Using artificial intelligence, his team will analyse this data to find novel RNA-based therapeutic candidates for the treatment of Parkinson’s disease.

‘Based on our analyses, we will propose RNA candidates suitable for therapeutic development. Our research partners at the Weizmann Institute in Israel and at Columbia University in the USA will then test these in cellular models. If the results are promising, we will investigate them further in preclinical studies with a view to progressing as quickly as possible towards clinical applications,’ says bioinformatician Andreas Keller, who also heads a research group at the Helmholtz Institute for Pharmaceutical Research Saarland.

Parkinson’s disease is shaped by multiple interacting factors. Biological characteristics such as age and gender influence the risk of developing the disease and its progression, yet they have often not been given sufficient consideration in molecular research to date. ‘At the same time, cell type, genetic background, and environmental influences contribute to its complexity. They also affect disease progression and how patients respond to treatment,’ explains Keller. Even within a single cell type, Parkinson’s disease can exhibit different molecular patterns influenced by these factors. ‘We expect to identify patterns within these large-scale datasets that will enable us to develop more effective and personalized drug therapies. We are already benefiting today from large datasets containing information on people with Parkinson’s disease, including blood samples, cerebrospinal fluid analyses and brain tissue data from deceased patients,’ he adds.

Using AI-supported methods developed over many years, the bioinformatics team in Saarbrücken will analyse these Parkinson’s datasets and correlate them with information on age groups and gender. The goal is to create a comprehensive, freely accessible molecular knowledge base for Parkinson’s disease, which will assist further research within the newly funded network. Key partners include Tal Iram and her team at the Weizmann Institute in Tel Aviv, as well as Philip De Jager, Vilas Menon and their respective teams at Columbia University in New York. The US$9 million grant (approximately €7.7 million) from ASAP will be awarded primarily to Saarland University.

Further information: 

https://www.asapcrn.org/funding

https://www.ccb.uni-saarland.de/
https://www.helmholtz-hips.de/de/forschung/people/person/prof-dr-andreas-keller/

 Press photographs that can be used free of charge with this press release can be found at the bottom of the following web page. 

For further information, please contact: 
Prof. Dr. Andreas Keller
Tel. +49 681 302 68611
Email: andreas.keller(at)ccb.uni-saarland.de

Karol Myszkowski is honored with the Eurographics Outstanding Technical Contributions Awardfor his long-standing and impactful work in computer graphics research. The laudation notes that his work “[…] for decades has helped shape how we understand, model, and visualize the world,” and that his contributions have made him one of the most relevant researchers in the field in Europe. His research bridges the gap between graphics and perception “with exceptional elegance and technical soundness, defining standards of excellence in many fields,” particularly in high dynamic range imaging (HDR), a technique for representing images with especially high contrast and detail. Among other things, Karol Myszkowski is co-author of the book High Dynamic Range Imaging: Acquisition, Display, and Image-Based Lighting, which has since become a standard reference for students, researchers, and practitioners alike.

Furthermore, he is well-known for his work on image quality analyses and metrics. He has also made fundamental contributions to so-called “perceptual rendering,” developing methods of image generation guided by human perception that restrict detail reconstruction to what is perceptually discernible.

Other important research areas in which he has made important contributions include stereoscopic imaging, where a slightly different image is generated for each eye, creating 3D depth in films or VR applications, as well as the realistic rendering of materials. More recently, he has increasingly focused on virtual reality research. Overall, his work has helped to use computational resources more efficiently.

In addition to his scientific work, Myszkowski is deeply involved in the professional community. In 2020, he chaired the Technical Papers Program of SIGGRAPH Asia and is active in numerous committees and editorial boards. Particularly noteworthy is his commitment to supporting early-career researchers, where he is regarded as a role model through his mentorship and scientific integrity.

Karol Myszkowski has been conducting research at the Max Planck Institute for Informatics since 2000, where he leads the research group “HDR Imaging, Rendering and Advanced Displays” as a senior researcher. Prior to that, he worked for many years in Japan, including as an associate professor at the University of Aizu. His academic career began at the Szczecin University of Technology. He received his PhD in 1991, followed by his habilitation in 2001, both in computer science at the Warsaw University of Technology. In 2011, he was awarded a lifetime professor title by the President of the Republic of Poland. In 2025, he was already named a Eurographics Fellow and inducted into the ACM SIGGRAPH Academy, the latter being among the highest international honors in computer graphics research.

The “Young Researcher Award” for Marc Habermann underscores the role of the Max Planck Institute for Informatics in promoting internationally leading research in computer graphics.

The award recognizes Habermann’s significant contributions to human performance capture, digital human reconstruction, and photorealistic human rendering. His work innovatively combines computer graphics, computer vision, and machine learning, as highlighted in the laudation.

During his doctoral research, Marc Habermann introduced “LiveCap,” the first method capable of generating a detailed, movable 3D model of a human, including clothing deformations, from image data captured by a standard camera, such as those found in smartphones. He subsequently developed “DeepCap,” the first learning-based framework for high-fidelity human performance capture, for which he received a CVPR Best-Paper Honorable Mention. Currently, Marc Habermann is researching how classical computer graphics methods can be combined with machine learning approaches (neural-explicit methods) to create even more realistic and efficient digital humans. Such technologies could be used in the future for virtual meetings, games, films, and anywhere digital humans play a role.

Habermann’s research findings have been published in the most important conferences and leading journals in computer graphics and computer vision, including SIGGRAPH, ACM Transactions on Graphics, CVPR, ICCV, ECCV, EUROGRAPHICS, and NeurIPS. His work has received multiple awards, including the EUROGRAPHICS PhD Award, the DAGM MVTec Dissertation Award, and the Otto Hahn Medal from the Max Planck Society.

Since 2017, the Saarland native has been conducting research at the Max Planck Institute for Informatics, initially as a doctoral student in the group of Professor Christian Theobalt. After earning his doctorate in November 2021, he began leading the “Graphics and Vision for Digital Humans Group” and serving as the Scientific Manager of the Real Virtual Lab in the Visual Computing and Artificial Intelligence department headed by Director Christian Theobalt. In December 2024, he was appointed Senior Researcher at the Institute.

Further Information:
Karol Myszkowski’s Website: https://people.mpi-inf.mpg.de/~karol/

Award citation for Karol Myszkowski: https://www.eg.org/wp/eurographics-awards-programme/the-outstanding-technical-contributions-award/outstanding-technical-contributions-award-2026-karol-myszkowski/

Website of the Graphics and Vision for Digital Humans group: https://gvdh.mpi-inf.mpg.de/

Award citation for Marc Habermann: https://www.eg.org/wp/eurographics-awards-programme/the-young-researcher-award/young-researcher-award-2026-marc-habermann/

Website of the Real Virtual Lab: https://www.mpi-inf.mpg.de/de/departments/visual-computing-and-artificial-intelligence/real-virtual-lab

Website of the Eurographics Conference 2026: https://eg2026.github.io/

Editor:
Philipp Zapf-Schramm
Max Planck Institute for Informatics
Phone: +49 681 9325 4509
Email: pzs@mpi-inf.mpg.de