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

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

This is an incredible achievement — only two out of over 5,000 accepted ICLR papers have received such an award this year!

MPI-SWS papers:

1. Automata on S-adic Words. Valérie Berthé, Toghrul Karimov, and Mihir Vahanwala (ICALP, Track B)
2. Hypersequent calculi have Ackermannian upper bounds. A. R. Balasubramanian, Vitor Greati and Revantha Ramanayake (LICS)
3. Infinite-state games with energy objectives beyond counters. Irmak Saglam and Georg Zetzsche (ICALP, Track B)
4. On the Subspace Orbit Problem and the Simultaneous Skolem Problem. Piotr Bacik and Anton Varonka (LICS)
5. On Variable-Bounded Non-Linear Expansions of Presburger Arithmetic. Piotr Bacik, Joris Nieuwveld, Joël Ouaknine, Mihir Vahanwala, Madhavan Venkatesh and Emil Rugaard Wieser (LICS)
6. Optimally Controlling a Random Population. Hugo Gimbert, Corto Mascle, Patrick Totzke (ICALP, Track B)
7. Optimal Sequential Flows. Hugo Gimbert, Corto Mascle, Patrick Totzke (ICALP, Track A)
8. Population Protocols over Ordered Agents. Michael Blondin, Michaël Cadilhac, Benjamin Courchesne, Lucie Guillou, Corto Mascle, and Isa Vialard (ICALP, Track B)
9. The Complexity of Nested Reset Counter Systems. A. R. Balasubramanian and Franzisco Schmidt (LICS)
10. The complexity of downward closures of indexed languages. Richard Mandel, Corto Mascle and Georg Zetzsche (LICS)

MPI-SP papers:

1. Complete Relational Logic for Infinite-Dimensional Quantum Programs with Unbounded Assertions. Gilles Barthe, Minbo Gao, Jam Kabeer Ali Khan, Matthijs Muis, Ivan Renison, Keiya Sakabe, Michael Walter, Yingte Xu, Tianshi Yu and Li Zhou (LICS)

MPI-INF papers:

1. A Faster Directed Single-Source Shortest Path Algorithm. Ran Duan, Xiao Mao, Xinkai Shu, Longhui Yin (ICALP, Track A)
2. Computing the (k+2)-Edge-Connected Components in k-Edge-Connected Digraphs in Subquadratic Time. Loukas Georgiadis, Evangelos Kipouridis, Evangelos Kosinas, Charis Papadopoulos, Nikos Parotsidis (ICALP, Track A)
3. Faster algorithms for k-Orthogonal Vectors in low dimension. Anita Dürr, Evangelos Kipouridis, Michael Lampis, Karol Wegrzycki (ICALP, Track A)
4. Fast decremental tree sums in forests. Benjamin Aram Berendsohn, Marek Sokołowski (ICALP, Track A)
5. Improved Tree Sparsifiers in Near-Linear Time. Daniel Agassy, Dani Dorfman, Haim Kaplan (ICALP, Track A)
6. Low Rank MSO. Mikołaj Bojańczyk, Michał Pilipczuk, Wojciech Przybyszewski, Marek Sokołowski and Giannos Stamoulis (LICS)
7. Node-Weighted Triangles: Faster and Simpler. Shyan Akmal, Nick Fischer (ICALP, Track A)
8. Permutation Patterns in Streams. Benjamin Aram Berendsohn (ICALP, Track A)
9. Random Access in Grammar-Compressed Strings: Optimal Trade-Offs in Almost All Parameter Regimes. Anouk Duyster, Tomasz Kociumaka (ICALP, Track A)

The DFKI Robotics Innovation Center in Bremen has a long-standing and successful partnership with SENAI CIMATEC. As early as 2013, SENAI (Serviço Nacional de Aprendizagem Industrial) opened the “Brazilian Institute of Robotics” (BIR) in Salvador, Bahia – modeled after the DFKI – with Prof. Dr. Dr. h.c. Frank Kirchner serving as Scientific Director. SENAI is the central organization for industrial training, applied research, and innovation in Brazil. Among other things, this collaboration resulted in the autonomous underwater vehicle (AUV) FlatFish for inspecting offshore energy infrastructure. The framework agreement now signed aims to further deepen this partnership, particularly in the areas of applied AI, robotics, and industrial innovation.

With the NEXUS AI Campus, DFKI also gains a new strategic partner. Located in Joinville, Santa Catarina, in Brazil’s industrially strong southern region, this innovation hub focuses on applied AI research, technological development, and the implementation of market-oriented solutions. NEXUS connects companies, universities, and international centers of excellence and specifically promotes global collaboration and knowledge transfer. Key areas of focus include generative AI, large language models, computer vision, health tech, industrial AI, quantum computing, cognitive robotics, and applications in agriculture and smart cities.

The goal of both partnerships is to jointly advance the development and application of innovative AI technologies, intensify the exchange of knowledge and talent, and provide new impetus for the economic use of AI.

“With Brazil as the partner country, this year’s Hannover Messe offers a particularly fitting setting to showcase the further development of our collaborations. Intensifying our collaboration with partners such as SENAI CIMATEC and NEXUS AI Campus opens up additional opportunities for us to translate our European AI research perspective and expertise into industrial applications and to further expand our international network with like-minded partners,” said Prof. Dr. Antonio Krüger, CEO of DFKI.

DFKI at Hannover Messe 2026

Hannover Messe is regarded as the world’s leading platform for technologies related to industrial transformation and brings together thousands of companies from the mechanical engineering, electrical, and digital industries, as well as the energy sector, every year. This year, DFKI will be presenting practical AI solutions in Hall 11, Booth B30, as well as at partner booths – ranging from robotic systems for aerospace and logistics to assistance solutions in medicine, management, and law, and the optimization of complex processes in industry and healthcare. Here, visitors can experience the transfer from research to industrial application firsthand, while also seeing how the developed technologies can be successfully applied to other fields.

How can artificial intelligence be effectively transitioned from research to real-world use? At Hannover Messe 2026, the German Research Center for Artificial Intelligence (DFKI) will demonstrate how AI solutions can be deployed in an economically viable, socially responsible, and technologically autonomous way. From April 20 to 24, DFKI will showcase practical AI technologies and transfer methods in Hall 11, Booth B30, as well as at partner booths, thereby strengthening Germany as an innovation hub and bridging scientific excellence and practical application.

The DFKI will present modern AI approaches applicable across various domains. Intelligent robotic systems support resource extraction on the Moon and simulate weightlessness, proving equally effective in logistics for industrial goods. As assistance and decision-support tools, AI technologies demonstrate their utility in diverse fields: from medical diagnostics and therapies to business decision-making and legal contract review. Additionally, AI systems model and optimize complex processes – such as those in medium-sized manufacturing firms or hospital emergency rooms – contributing significantly to increased efficiency, transparency, and quality assurance.

“There has never been a better time to invest in industrial and European AI. The necessary infrastructure is being built in Europe, and we have the ideas. Anyone who isn’t yet using AI to enhance products and processes should do so now, or risk losing their competitive edge. In the areas of Trusted AI, space, and healthcare, we are already experiencing the value AI provides.” — Professor Antonio Krüger, Scientific Director and CEO of DFKI

The strategic innovation fields of Trusted AI, Health AI, and Space AI define DFKI’s main themes at Hannover Messe

Trusted AI stands for transparent, secure, and compliant AI systems throughout the entire lifecycle – from data collection to practical application. Its goal is to build trust as the foundation for creating economic value and to actively help shape European standards. Trusted AI ensures that AI systems can be verified, robust, and securely certified – for autonomous systems, critical infrastructure, and industrial processes. DFKI develops methods and standards that combine security, explainability, and sovereignty.

With Health AI, DFKI integrates cutting-edge AI methods into medical practice – from diagnostics and personalized therapy to intelligent assistance systems in care and rehabilitation. DFKI combines image processing, signal analysis, and clinical expertise – for more efficient patient care and life-saving pattern recognition.

In space exploration, AI is reaching its full potential: robotics, real-time data analysis, and mission control. Space AI opens new horizons for autonomous systems, satellite data utilization, and resilient infrastructure. These advancements not only strengthen Europe’s role in space exploration but also boost industry, environmental monitoring, and supply systems on Earth. DFKI solutions for Earth observation and extraterrestrial exploration can be easily adapted to address challenges on Earth.

In the stage program at Hannover Messe, DFKI researchers will discuss key future topics such as AI gigafactories and the path to technological sovereignty, agentic AI and resilient factories, trustworthy AI as the foundation of Europe’s digital sovereignty, mobile robots for extraterrestrial use, physical AI in rehabilitation, and industrial AI in a transnational context.

This honor is granted to only about 3.6% of the more than 1,700 papers accepted at the Conference on Human Factors in Computing Systems. The conference takesplace in Barcelona from April 13 to 17, 2026.

The first award-winning paper is “Scene2Hap: Generating Scene-Wide Haptics for VR from Scene Context with Multimodal LLMs.” Paul Strohmeeier explains: “In virtual reality, we are used to seeing or hearing content. Virtual worlds you can feel by touch are much rarer. While visual content is created through light and acoustic content through sound waves, our approach is based on vibration. Building on simple effects like those one might recognize from VR controllers or smartphones, we recreate the complex dynamics of the tactile world this way.” However, the vibration patterns required to create such haptic impressions (vibrotactile feedback) currently still have to be created manually, which does not scale for complex VR scenes with many objects. That is the focus of the newly awarded paper.

With “Scene2Hap,” first authors Arata Jingu from Professor Jürgen Steimle’s Human-Computer Interaction Lab at Saarland University and Easa AliAbbasi from Paul Strohmeier’s Sensorimotor Interaction group have now developed an approach for automatically designing meaningful vibrotactile feedback for objects and scenes in virtual reality. To do this, the researchers use a multimodal large language model (LLM) that can process not only language, but also image and audio data. The model automatically infers the semantics of objects, physical properties and material characteristics, as well as the physical context of the scene. “We draw on various layers of meta-information, ranging from the context of a virtual object to material properties that the LLM can recognize in the image,” explains Easa AliAbbasi. The vibrotactile feedback is then generated and transmitted separately to each hand via the VR controllers being held. In three different user studies, the team was able to show that “Scene2Hap” successfully improved users’ sense of space and perception of materials and generally contributed to a better user experience when the VR environment was created entirely with the newly developed pipeline.

The second award-winning paper, “How are Vibrotactile Experiences Visually Represented? A Taxonomy of Illustration Characteristics,” is a meta-study that examines how haptic impressions and tactile information are communicated in research. More specifically, the award-winning paper investigates how vibrotactile feedback is represented visually. “When new methods for visual rendering are developed, their quality can be shown directly in papers, for example through an image. In haptics research, things are different: we can only describe what something feels like, but we cannot easily convey the actual sensation directly. In my opinion, this limited ability to represent haptic experiences is a central challenge in haptics research,” says Paul Strohmeier.

To analyze this issue, the researchers first developed a taxonomy for representing vibrotactile experiences (VTX) and then collected a total of 1,652 papers from the past 25 years from the digital libraries of the two world’s largest professional associations in computing, the Association for Computing Machinery (ACM) and the Institute of Electrical and Electronics Engineers (IEEE). Within these, they identified 768 visual representations from 409 research papers and coded them according to their visual representation of VTX based on the taxonomy. Their results indicate that (1) half of the illustrations communicate on the timing of vibrotactile feedback with regards to users’ actions, (2) illustrations depict stimuli rather than experiences and infrequently communicate multimodal aspects of the experiences, and (3) contextual information of vibrotactile displays and experiential aspects are often distributed across several complementary figures.

“With our taxonomy, we want to give authors a tool to analyze and improve their illustrations. At the same time, in combination with the corresponding dataset it could serve as an approach for generative models to automatically create ideas or inspiration for visualizing one’s own research,” explains Dennis Wittchen from the SensInt group, who co-authored the paper as first author together with Bruno Fruchard from the French research institute Inria.

Orignal publications:
Arata Jingu, Easa AliAbbasi, Sara Safaee, Paul Strohmeier, and Jürgen Steimle. 2026. Scene2Hap: Generating Scene-Wide Haptics for VR from Scene Context with Multimodal LLMs. In Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI ’26), April 13–17, 2026, Barcelona, Spain. ACM, New York, NY, USA, 21 pages. https://doi.org/10.1145/3772318.3791297

Bruno Fruchard, Dennis Wittchen, Nihar Sabnis, Paul Strohmeier, and Donald Degraen. 2026. How are Vibrotactile Experiences Visually Represented? A Taxonomy of Illustration Characteristics. In Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI ’26), April 13–17, 2026, Barcelona, Spain. ACM, New York, NY, USA, 24 pages.
doi.org/10.1145/3772318.3790598

Further information:
Website of the Conference on Human Factors in Computing Systems: https://chi2026.acm.org/
Website of the Sensorimotor Interaction group: https://sensint.mpi-inf.mpg.de/

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

The paper solves a long-standing open problem in the field of quantitative games. Weighted timed games were introduced in several works in the early 2000s, and constitute a fundamental model for formal verification and control. The key decision problems for quantitative games are the existence of winning strategies and the ‘value problem’: is the inf-sup across all pairs of Minimizer/Maximizer strategies smaller than a given rational? With three clocks, the value problem was proved undecidable in 2015. With a single clock, the problem was shown to be decidable in 2022. This paper finally closes the gap: with two clocks, both problems are shown to be undecidable using a novel and ingenious reduction, resulting in a deep contribution

Ziel des UdS-KI-Tages für Studierende im Innovation Center ist es, das Thema Künstliche Intelligenz im Studienkontext und den Copilot Chat speziell für Studierende vorzustellen. Die vorläufige Agenda (ca. 9:30 – 15:00 Uhr) beinhaltet Fachvorträge von Microsoft.

Geplante Themen sind:

• News from the Valley – Überblick über die neuesten Entwicklungen aus dem Silicon Valley zu KI und Co.
• AI & Careers – Karriereperspektiven: Wie KI die Arbeitswelt verändert, welche Skills gefragt sind und wie man in Big Tech oder AI-Startups einsteigt
• Beiträge von UdS-Vertreterinnen und -Vertretern zum Einsatz von KI-Lösungen (z.B. Tutor-Bots) und KI-Projekten (z.B. UdS Info-Bot).

Das Programm wird durch interaktive Elemente („Spot the Fake – KI‑Bilder & Täuschung; Bewusstsein für Risiken von KI“) und Networking-Möglichkeiten ergänzt.

Teilnehmerinnen und Teilnehmer können einen Nachweis erhalten.

More Information:

https://www.uni-saarland.de/forschen/quantentechnologien.html

Questions answered:

Prof. Dr. Moritz Weber
Tel.: 0681-302-2556
E-Mail: weber(at)math.uni-sb.de

All large language models are currently based on the so-called Transformer architecture. This architecture is modeled after the human ability to focus on relevant information and ignore less important details. Michael Hahn, Professor of Computational Linguistics at Saarland University, was able to mathematically prove that Transformers fail at tasks in which every part of the input is relevant to the output. Thus, changing even a single character can alter the correct result. This allows the computational linguist and his interdisciplinary team at the Saarland Informatics Campus to gain theoretical insights that can be used to better predict the strengths and weaknesses of large language models.

Just recently, Michael Hahn received 1.4 million euros from the German Research Foundation for his research at the intersection of machine learning and computational linguistics, to establish an Emmy Noether Research Group (see press release dated November 13, 2025). The Heinz Maier-Leibnitz Award is considered one of the most prestigious prizes in the German-speaking world for early-career researchers. It is endowed with 200,000 euros, intended to support the laureates in pursuing their scientific careers. The prize is named after the physicist and former president of the German Research Foundation, Heinz Maier-Leibnitz, and has been awarded since 1977.

Background
The Heinz Maier-Leibnitz Prize is considered one of the most prestigious awards for early-career researchers in the German-speaking area. It comes with a prize of 200,000 euros, intended to support the laureates in pursuing their academic careers. The prize is named after the physicist and former president of the German Research Foundation, Heinz Maier-Leibnitz, and has been awarded since 1977.

Background Saarland Informatics Campus
1,000 researchers (including 540 doctoral candidates) from more than 80 nations make the Saarland Informatics Campus (SIC) one of the leading locations for computer science in Germany and Europe. Four world-renowned research institutes, namely the German Research Center for Artificial Intelligence (DFKI), the Max Planck Institute for Informatics, the Max Planck Institute for Software Systems, the Center for Bioinformatics as well as Saarland University with three departments and 24 degree programs cover the entire spectrum of computer science.

Further information:

Press release from the German Research Foundation 

Information on the Heinz Maier-Leibnitz Prize

Persönliche Webseite von Professor Michael Hahn: Professor Michael Hahn’s personal website: https://www.mhahn.info

For further inquiries, please contact:

Prof. Dr. Michael Hahn
Chair of Language, Computation, and Cognition
Tel. 0681 302-4343
Email: mhahn(at)lst.uni-saarland.de

Experten bewerten Gebäudebestände mit KI und Mixed Reality

Eine große Herausforderung beim Urban Mining in Immobilien ist das fehlende Wissen über Art, Menge und Qualität der zu bergenden Bauprodukte. Hier setzt das Forschungsprojekt MIRAKEL an. In dem Verbundprojekt aus Industrie und Forschung entwickeln die Projektpartner ein innovatives System, das es Experten mithilfe von künstlicher Intelligenz und Mixed Reality ermöglicht, anthropogene Lager in Immobilien präzise und umfassend zu bewerten. Durch die gesteigerte Transparenz über die vorhandenen Bestände und die nötigen Rückbauschritte soll sich Urban Mining zukünftig von der reinen Bergung von Rohstoffen lösen. Das Ziel besteht darin, auch Bauteile, Bauelemente und Komponenten gezielt zurückzugewinnen, um eine möglichst hochwertige Anschlussnutzung der Bauprodukte zu erreichen und Urban Mining zu einem zentralen Baustein einer ressourceneffizienten, klimaneutralen Bauwirtschaft zu machen.

„Mit MIRAKEL machen wir den Wert der verborgenen Rohstoffe in Gebäuden sichtbar und wirtschaftlich nutzbar“, heißt es aus dem Projektteam. „So wird Rückbau vom Kostenfaktor zur Ressourcenquelle für die Bauwirtschaft von morgen.“

Sieben Partner entwickeln Prototyp für die Praxis

Das Projekt wird im Rahmen der Förderung „Ressourceneffiziente Kreislaufwirtschaft – Urban Mining: Erschließung anthropogener Lager als Rohstoffquelle“ durch das Bundesministerium für Forschung, Technologie und Raumfahrt (BMFTR) gefördert. Während der 30-monatigen Projektlaufzeit arbeiten die sieben Projektpartner Concular GmbH, Wilhelm Knepper GmbH & Co. KG, ryze technologies GmbH, Berliner Immobilienmanagement GmbH, SRH University, Deutsches Forschungszentrum für Künstliche Intelligenz GmbH (DFKI) und CIRCULAR STRUCTURAL DESIGN an einem ersten Prototyp des Assistenzsystems, der in ausgewählten Immobilien praktisch erprobt und wissenschaftlich evaluiert wird. Das Projekt ist im November 2025 gestartet und läuft bis einschließlich April 2028.

The EATCS Fellows Program was established by the association in 2014 to recognize outstanding EATCS members for their scientific achievements in the field of Theoretical Computer Science.

Further Information: 

• https://eatcs.org/index.php/component/content/article/1-news/3028–eatcs-fellows-class-of-2026-named
• https://www.eatcs.org/index.php/eatcs-fellows

“Study Computer Science in Germany” on Thursday, 26 March 2026 at 16:00 (CET)

“Study Electrical Engineering in Germany” on Thursday, 23 April 2026 at 16:00 (CET)

Study Computer Science in Germany (Master’s): Online Webinar with Saarland University & DFKI 

Thinking about a Master’s in Computer Science or in Visual Computing in Germany and not sure how programs work, what admissions look for, or how to compare universities? Join the English webinar “Study Computer Science in Germany” on Thursday, 26 March 2026 at 16:00 (CET).

You’ll get a clear overview of how Computer Science Master’s programs in Germany are structured — and you’ll be able to ask questions directly to university representatives to compare options and find the right fit.

What we’ll cover (and what you can ask):

• What a CS Master’s in Germany typically looks like (focus areas, workload, expectations)

• Admissions basics — and what makes a strong application

• How to compare programs across universities (university vs. university of applied sciences)

• Live Q&A with program representatives

Saarland University & DFKI contribution:
Prof. Dr.-Ing. Philipp Slusallek (Saarland University; Scientific Director at the German Research Center for Artificial Intelligence (DFKI)) will introduce the Master’s programs M.Sc. Computer Science and M.Sc. Visual Computing.

Date & time: Thursday, 26 March 2026, 16:00 (CET)
Language: English
Format: Online (Zoom) | approx. 60–75 minutes

Registration / event page:
https://www.mygermanuniversity.com/de/webinar/2026-03-26/study-computer-science-in-germany/1035

The “traveling salesman problem” is probably the best-known example of a so-called optimization problem that poses major challenges for mathematicians: as the number of stops increases, it becomes increasingly difficult to calculate the shortest possible route that visits all locations and returns to the starting point. But such optimization problems don’t just affect salespeople—they appear everywhere in daily life, for example in manufacturing complex products or calculating prices.

Fortunately, we have computers today that can solve such problems in no time. Or do we? Not always. Even today, classical computers can often only approximate solutions to difficult mathematical problems rather than solve them completely—and often only with long runtimes. Their algorithms are typically based on real-world problems and exploit their structure heuristically. “That works surprisingly well. Algorithms that are theoretically slower can still be faster in practice,” explains Peter P. Orth, Professor of Theoretical Physics of Quantum Information at Saarland University. However, despite their quality, these solutions are often just the best possible under given circumstances—essentially: “We make the best of it; more isn’t currently possible.” But that is not enough for Peter P. Orth, his colleague Markus Bläser (a computer scientist specializing in complexity and algorithms), the industry partners Infineon and BMW, and the quantum start-up planqc.

In a new research project called “QIAPO – Quantum-informed approximate optimization on NISQ and partially fault-tolerant quantum computers,” they are therefore taking a new approach: a special quantum computer based on neutral atoms, built by planqc in Garching, will first “shrink” highly complex logistical tasks—such as those arising in the production and distribution of cars or computer chips—so that classical computers can handle them more effectively using proven algorithms. Quantum computers can outperform classical ones in certain cases because their computing units, qubits, can exist in a superposition of states 0 and 1, whereas classical bits can only be either 0 or 1. This makes quantum computers particularly well suited for solving or simplifying highly complex mathematical problems that would overwhelm classical systems.

Once the “jungle” of a mathematical problem has been cleared, researchers can continue working on classical computers using well-established algorithms to solve the now much smaller problem. However, even this hybrid approach will not yield perfect solutions for the kinds of challenges faced by companies like Infineon and BMW, Orth notes—which is why the project includes “approximate optimization” in its title. In other words, the goal is to use a combination of quantum and classical algorithms to improve solutions incrementally. For example, if a problem can currently be solved with 80% accuracy, the hybrid approach might improve this to 85% or even 95%. “This is where quantum computers could ‘fill the gap’ to increase accuracy and achieve a quantum advantage,” says Orth.

“The QIAPO project not only shows how far quantum computing has already progressed,” says Dr. Martin Kiffner, Head of Algorithms at planqc. “We are already demonstrating how highly complex, industry-relevant challenges can be translated into quantum algorithms that can ultimately be tested on quantum computers.”

Physicist Peter P. Orth describes a realistic goal of the project: “Over the next three years, we won’t immediately solve the biggest problems. But we will very likely find out whether our approach can fundamentally solve such problems—and then continue exploring them further.” After all, even small efficiency gains in complex industrial production and distribution processes could have significant impact. As the project description notes: “Even minor resource savings can lead to substantial financial effects at large production scales.”

At a glance:
The project “QIAPO – Quantum-informed approximate optimization on NISQ and partially fault-tolerant quantum computers” has been funded since January 2026 for three years with €2.33 million by the German Federal Ministry of Research, Technology and Space. It is coordinated by Prof. Dr. Peter P. Orth (Saarland University). Other participants include Prof. Dr. Markus Bläser (Saarland University), BMW AG, Infineon Technologies AG, and planqc GmbH. planqc develops quantum computers based on neutral atoms—the fastest path toward scalable quantum processors for industrial applications. Founded in April 2022 in Garching near Munich by Alexander Glätzle, Sebastian Blatt, and Johannes Zeiher, planqc is the first spin-off of the Max Planck Institute of Quantum Optics within the Munich Quantum Valley initiative.

Related Links:
www.quantensysteme.info/projektatlas/projekte/q/qiapo
www.planqc.eu

More Information:
Prof. Dr. Peter P. Orth
Tel.: (0681) 3024960
E-Mail: peter.orth(at)uni-saarland.de
Webseite: https://www.uni-saarland.de/lehrstuhl/orth.html

This text has been machine translated from the German and has undergone no postediting.

Max Planck researchers investigate “quantum neural networks” as a building block for more efficient visual-computing models.

The “4D Quantum Computer Vision” research group at the Max Planck Institute (MPI) for Informatics in Saarbrücken, Germany, is investigating the potential of quantum computing for computer-based image processing, also known as visual computing. A new hybrid model, developed together with partners from the University of Udine and the University of Naples Federico II, combines a so-called “quantum neural network” with a classical neural network. In tests on established metrics the model outperforms previous methods while using significantly fewer network connections and requiring a shorter training time.

Researching technologies that cannot yet keep up with the state of the art today, but have the potential to transform entire fields tomorrow—that is the aim of basic research. One such technology is quantum computing. Quantum computers are still rare, difficult to access, and in many applications slower than classical computers. At the same time, quantum computers promise major advantages thanks to their special properties: the ability to represent many quantum states simultaneously (superposition), and to link qubits into a coherent shared state so they can no longer be regarded as independent of one another (entanglement). Investigating where these properties can be beneficial is a new and active field of research.

At the MPI for Informatics, the “4D Quantum Computer Vision” group led by Dr. Vladislav Golyanik is exploring how quantum computing could advance computer-based image processing, particularly in visual computing and 3D computer vision. “On the one hand, we look for alternative ‘quantum solution paths’ for problems that are already known. Beyond that, of course, we also look for entirely new research questions that can benefit from quantum computing,” explains Vladislav Golyanik. The goal is ambitious: in the future, the team aims to reconstruct arbitrary real-world scenes photorealistically on a computer from just a few recorded images—and from novel, unrecorded viewpoints—even when objects in the scene move or deform. Such tasks are extremely computationally intensive, pushing even modern high-performance computers to their limits.

To address this challenge, the group is currently working on so-called “quantum neural networks” (QNNs). In such models, quantum circuits, usually simulated on classical hardware, are treated as trainable functions, similar to classical machine learning, and are adjusted using data-driven training and optimization methods.

In a recently published paper titled “Quantum Visual Fields with Neural Amplitude Encoding,” presented in December 2025 at the Conference on Neural Information Processing Systems (NeurIPS), the team—consisting of PhD student Shuteng Wang, Dr. Vladislav Golyanik, and Professor Christian Theobalt, Scientific Director of the Visual Computing and Artificial Intelligence department at the MPI for Informatics—describes a method for processing image data so that QNNs can handle it more efficiently. To this end, the researchers developed an initial hybrid model that combines a classical neural network with a QNN to encode input signals in 2D or 3D, as well as collections of such signals.

Building on this, a follow-up project titled “QNeRF: Neural Radiance Fields on a Simulated Gate-based Quantum Computer” was carried out together with partners from the University of Udine and the University of Naples Federico II. In this project, the researchers developed a hybrid model for “novel-viewpoint rendering,” that is, synthesizing new viewpoints of objects or scenes that were not contained in the original data. In experiments, the new model achieved comparable or better quality on the established PSNR metric than previous approaches, while using less than half the required network parameters and requiring fewer training steps. “For our tests, we simulated the quantum circuits on classical hardware. That meant the absolute training time was higher, but we were able to reduce the number of training steps, which could indicate shorter training times on ‘real’ quantum hardware in the future,” explains Golyanik. “QNeRF” is currently publicly available as a preprint.

Additionally, the work of the research group 4D Quantum Computer Vision is funded by the German Research Foundation (DFG) through the project “Applied Quantum Computing for Computer Vision.”

Professor Christian Theobalt says: “For us, quantum computing is a bet on the future, a high-risk, high-gain approach: we want to understand early on which fundamental principles of quantum computing could truly be useful, so that we are scientifically and technologically prepared when quantum resources become more widely available.”

In the long term, the ability to reconstruct complex scenes more efficiently could enable applications in areas such as robotics, manufacturing, medicine, or film and visual effects—anywhere computers need to represent reliable 3D information from camera footage and compute novel viewpoints.

Original publications:

Wang, Shuteng; Theobalt, Christian; and Golyanik, Vladislav. “Quantum Visual Fields with Neural Amplitude Encoding.” Neural Information Processing Systems (NeurIPS), 2025.
Project page: https://4dqv.mpi-inf.mpg.de/QVF/

Lizzio Bosco, Daniele; Wang, Shuteng; Serra, Giuseppe; and Golyanik, Vladislav. “QNeRF: Neural Radiance Fields on a Simulated Gate-based Quantum Computer.” arXiv preprint arXiv:2601.05250, 2026.
Project page: https://4dqv.mpi-inf.mpg.de/QNeRF/

Further information:

Website  of the 4D Quantum Computer Vision group: https://4dqv.mpi-inf.mpg.de/

DFG project “Applied Quantum Computer Vision”: https://gepris.dfg.de/gepris/projekt/534951134?language=en

Scientific contact:
Dr. Vladislav Golyanik
Research Group Leader, MPI for Informatics
E-Mail: golyanik@mpi-inf.mpg.de

Prof. Dr. Christian Theobalt
Scientific Director, MPI for Informatics

Editor and press contact:
Philipp Zapf-Schramm
Max-Planck-Institut für Informatik
Tel: +49 681 9325 4509
E-Mail: pzs@mpi-inf.mpg.de

The school will focus on deepening understanding of biological systems by combining modern biomedical technologies with innovative approaches to artificial intelligence. The aim is to train a new generation of scientists who will develop algorithms that can learn, explain, and predict the principles of living systems and use these findings for molecular design.

People increasingly use artificial intelligence today in important decisions that have a major impact on people’s lives – from improving medical diagnosis and increasing efficiency in research to supporting data-based decision-making in business and administration. However, AI cannot ‘understand’ like a human being why something happens or how damage could be avoided by acting differently, for example when driving an autonomous vehicle or in robotics. ‘Many real-world systems today are based on AI, but their actions are difficult to interpret because we often don’t know exactly what the neural networks are calculating in the background. This means that IT systems are not particularly reliable and are difficult to manage when they have to comply with safety regulations, for example,” says Sara Magliacane.

The computer scientist therefore wants to research at Saarland University how ideas of causality can be used to make complex AI models safer and more reliable. Among other things, the focus is on the large language models on which ChatGPT and similar programs are based. It will also look at so-called vision language models, in which AI is trained to link text data and visual data such as images and videos. Another focus will be on ’embodied AI,’ which can be used to program care robots, for example, to ‘understand’ information from their environment and translate it into their own actions.

Sara Magliacane’s areas of focus enrich the research environment at the Saarland Informatics Campus in many ways. They are particularly well suited to the Research Training Group ‘Neuroexplicit Models for Language Processing, Image Recognition and Action Decisions’, in which several computer science research institutes in the region are involved alongside Saarland University and which will continue to receive funding from the German Research Foundation until 2028.

Short CV of Sara Magliacane 

Sara Magliacane has been an assistant professor at the Amsterdam Machine Learning Lab at the University of Amsterdam since 2020. From 2019 to 2025, she was also a researcher at the renowned MIT-IBM Watson AI Lab in Cambridge, Massachusetts (USA), where she was IBM’s principal investigator for several projects in collaboration with the MIT faculty. Born in Italy, she completed her master’s degree at the Polytechnic University of Milan (Italy) and received her Ph.D. from the Free University of Amsterdam (Netherlands) in 2017. She then spent two years conducting research at the IBM Thomas J. Watson Research Centre before moving to the MIT-IBM Watson AI Lab and the University of Amsterdam.

The Harlan D. Mills Award is presented by the international engineering association IEEE (Institute of Electrical and Electronics Engineers) and recognizes long-standing and impactful research contributions to software development. Andreas Zeller is being honored for his lasting contributions to software debugging, program analysis, mining software repositories, and automated test generation.

The Harlan D. Mills Award will be presented to Andreas Zeller in April at the International Conference on Software Engineering in Rio de Janeiro. IEEE has more than 500,000 members from over 190 countries. It publishes about one third of the world’s technical literature in electrical engineering, computer science, and electronics, and supports more than 2,000 conferences each year.

Background Saarland Informatics Campus:
900 scientists (including 400 PhD students) and about 2,500 students from more than 80 nations make the Saarland Informatics Campus (SIC) one of the leading locations for computer science in Europe. Four world-renowned research institutes cover the entire spectrum of computer science, namely the German Research Center for Artificial Intelligence (DFKI), the Max Planck Institute for Informatics, the Max Planck Institute for Software Systems, the Center for Bioinformatics as well as Saarland University with three departments and 24 degree programs.

This text was machine translated from the German with no human editing.