INDUSTRIAL AI, TRUSTED AI, AND 03 L A I R O T I D E 2 2 0 2 / 1 s w e N I K F D More than two years of the Corona pandemic, the blockage of the Suez Canal by the container ship Ever Given, the war in Ukraine, and the ensuing energy price crisis have shown how vulnerable supply chains can be in our globalized industrial world. Major supply interruptions can bring individual sectors and entire branches of production to a standstill, jeopardize order processing, and lead to drastic losses in sales. Industrial AI (p. 6) is the key to more ﬂexible manufacturing processes and dynamic adaptation to ever-changing production conditions. AI technologies are crucial for three of the core concepts of Industrie 4.0 – digital twins, decentralized control, and active product memory. The best way to strengthen the competitiveness of the manufacturing sector and to maintain quality leadership is with industrial AI. AI creates new added value: for example, incidentally collected data on raw materials in the food industry serves to enable the semi-automated generation of higher-value data products through decentralized AI-Services (p. 10). In the ﬁeld of agricultural food production, Nature Robots, a DFKI spin-off, is developing software components that enable robots to independently navigate between crops and weeds (p. 22). AI, which was once a niche science, has been transformed into a “mega-technology” to beneﬁt the whole of society through machine learning with artiﬁcial neural networks. However, the traceabili- ty and reliability of the results, as well as the systems‘ lack of a self-explanatory capability, are prob- lematic. The general need is for AI systems that can be trusted. Trusted AI (p. 14) is the term that refers to a new generation of AI systems that provide guarantees about their functionality, allowing use in critical applications and paving the way for the development and use of long-term autono- mous systems (p. 20). AI is assisting nurses in the intensive care unit. The service consists of holistic real-time analysis and classiﬁcation of the patient‘s vital signs, which are continuously monitored. AI-powered systems detect critical conditions at an early stage, generate alerts, and serve to actively improve patient safety. The European AI Centers of Excellence network, which is designed to be the nucleus for further activities in cutting-edge AI research and innovation in Europe, is being signiﬁcantly shaped by DFKI in the VISION, TAILOR and HumanE-AI-Net projects (p. 16). The collaboration between DFKI and Inria is also being steadily intensiﬁed: R4Agri and ENGAGE are two new projects started at the beginning of this year as part of the German-French AI cooperation (p. 33). Prof. Dr. Antonio Krüger Helmut Ditzer Prof. Dr. Prof. h.c. Andreas Dengel Prof. Dr. Dr. h.c. Frank Kirchner Prof. Dr. Philipp Slusallek
07 2 2 0 2 / 1 s w e N I K F D 76.2 percent of the machine manufacturing and plant engineering companies identiﬁed with the statement, “It is part of their professional philosophy as technolo- gy leaders to address this topic,” according to a study at the time by the Impuls Foundation. Three core concepts of Industrie 4.0 are critical – the dig- ital twin, distributed control, and active product memory. In 2011, the authors wrote, “These concepts make it possible, for example, to better meet the economic as well as the special ecological requirements of “green production” for a CO2-neutral, energy-ecient city.” It all started with product memory DFKI was addressing the topic of product memory in the SemProM project already back in 2008. The next gener- ation of mobile, embedded, and radio-based elements for semantic Internet communication between everyday objects was studied as part of the ICT-2020 research pro- gram of the Federal Ministry of Education and Research (BMBF). The goal was to enable a blank disk to access all existing operational and machine data to document the entire manufacturing process. Since the passage of the ‚Corporate Due Diligence in Supply Chains Act’ by the German Bundestag in June 2021, product memories have taken on increased importance and new meaning as they can provide an important building block for com- panies to meet the legal obligation to provide evidence. The ‘Supply Chain Act,’ which becomes effective on January 1, 2023, will initially apply to companies with more than 3,000 employees, but will be extended to compa- nies with 1,000 employees beginning in 2024. Product memory is actively discussed in terms of In- dustrial AI and is turning conventional production on its head. This leads to a rethinking of control logic: tra- ditionally, the rate, the work plan, and a central control would govern. Industrial AI enables self-adapting process control in place of isolated corrections to the machine schedules. In a tightly networked production system, the blank disk directs the manufacture of what will become the ﬁnished product. This not only enables distributed production control of individual products and very small batches but also documents resource consumption, i.e., the materials and energy used for each individual work- piece. This implies the need for seamless networking and closely detailed information exchange in the Enterprise Resource Planning (ERP) and Manufacturing Execution Systems (MES), the major systems used for corporate planning and factory control. In multimodal teach-ins, robots learn movement patterns that they can subsequently execute independently.
08 D F K I N e w s 1 / 2 0 2 2 An AI-based optimization system developed at DFKI for dynamic sequencing adapts the planning of the work- ﬂows in real time to different demands, e.g. country-spe- ciﬁc variants or conﬁguration types, and enables ﬂexible manufacturing even for the smallest batch size. A market advantage can be gained with variant-rich pro- duction – keyword: Batch Size 1 – but for proﬁtable manu- facturing, it is necessary to deal with current challenges. In a globalized and networked sector, any interruption of production or delay in the supply chain presents a business risk and can lead to massive ﬁnancial losses. From optimization efforts to resilience management – Smart resilience services for the manufacturing sector Resilience management is an indispensable success factor for a future industrial production signiﬁcantly characterized by increasing complexity. Companies need to acquire the ability to anticipate internal disruptions, for example, tool wear or raw material quality ﬂuctua- tions, and to adapt proactively to external change such as supply bottlenecks. DFKI is coordinating the research project SPAICER (Scal- able, adaptive Production systems through AI-based Resilience optimization) with the aim of developing AI- based, smart resilience-services that generate useful recommendations for action that enable decision-mak- ers to initiate stabilization measures at an early stage. Using smart resilience services, an analysis of sensor data streams as well as the quality and image data of Distributed control The concept of intelligent controls, initially designed for small batches, can be modiﬁed for unstable production conditions. Work can be scheduled on that very day for which raw materials, supplier parts, and workers are available to manufacture the product, and production is still proﬁtable at the current energy price. In conventional production, workers are typically pre- assigned in “loops.” Their task is to perform the individu- al work steps sequentially from station to station and to hand over the product to be manufactured to a colleague at ﬁxed nodes. In the case of dynamic multi-variant pro- duction with small batch sizes, waiting times or incor- rect loads occur during production, which are caused by production plans that have been completed beforehand. This is a dicult challenge to solve for conventional pro- duction planning systems in light of the highly dynamic nature, the real-time requirements, and the correlation of multiple optimization aspects. An AI-based optimization system developed by DFKI adjusts workﬂow planning in real-time.
11 2 2 0 2 / 1 s w e N I K F D guarantee ownership and control of data assets as well as the execution of deﬁned taskings and sharing of results ac- cording to contract. Use case: Dry beans Dry beans are the most widely produced product in the category of edible legumes worldwide. As part of an on- going trend toward vegetarian and vegan diets, beans not only help support a low-impact lifestyle but also contrib- ute to increased energy eciency and climate protection through reduced use of nitrogen fertilizers and CO2 savings. The many varieties of dry beans exhibit a wide genetic di- versity and quality, which has a decisive inﬂuence on crop production. A dry bean classiﬁcation system is essential for both production and marketing to ensure the principles of sustainable agriculture are observed. Let’s say Farmer A wants to classify his dry beans to produce and sell uniform seed varieties at optimal prices. The farmer meets Farmer B and concludes an electronic contract via eContract Broker. The object of the contract is the result from a joint analysis of the data sets to determine an im- proved classiﬁcation. Both farmers transmit their dry bean data sets with 16 characteristics per variety to the broker. The broker then executes the analysis and generates a vari- ety classiﬁcation using neural networks on Edge. The broker sends the result to Farmer A, and both data sets are delet- ed. Farmer A pays Farmer B for his participation and can use the results to optimize his seeds and determine the optimal price for his crop. The eContract Broker also receives a ﬁ- nancial payment for ensuring sovereign, shared data anal- ysis as well as for executing the contract. PROJECT DESCRIPTION Partners: • German Research Center for Artiﬁcial Intelligence, DFKI (lead manager) • Agricultural Market Information Company (AMI) • Lindt & Sprüngli Group • Research Institute for Rationalization (FIR) at RWTH Aachen University • Software AG • Saarland University Associate Partners: BVE e.V. DIL e.V. Funding agency: Federal Ministry of Economic Affairs and Climate Action (BMWK) Sponsor German Aerospace Center (DLR) Volume 2.3 million euros The consortium‘s successful submission of the “FAST” GAIA-X use case, which deals with data interoperability and data sovereignty in the food production industry, is attributable to these technical results. The EVAREST consortium also pub- lished DIN SPEC 91452, “Business Model Development for a Data Ecosystem in Food Production.” The standard provides a design approach for specifying business models in data eco- systems and for developing and building data ecosystems. Contact Hannah Stein Research department Smart Service Engineering email@example.com +49 681 85775 5270 The EVAREST project team at the closing event on April 29, 2022, at the Digital Technologies Forum in Berlin.
13 13 13 I I K K F F D D 2 2 0 2 / 1 s w e N I K F D 2 2 2 2 0 0 2 2 / / 1 1 1 S S W W W E E N N I I K K F F D D LIDARSHARED: THE ROAD TO Rather than competing for the scarce public space in the city, future motorists will share it in “shared spaces.” Shared spaces pose a challenge for autonomous drive vehicles, mainly because collision avoidance systems employed in dense, unregulated, and highly dynamic areas ask a lot from current AI algorithms. Continued research and development of special AI methods is an essential step towards ensuring a high level of safety for all road users and sustainable future transportation. team had to synchronize all sensor data and convert GPS coordinates into positions on the local, campus-wide map. The methods and datasets developed in the LidarShared project have become baselines for future projects in the ﬁeld of robust and trustworthy computer vision and auton- omous driving. The researchers have already begun to ex- ploit their experience in follow-on projects, paving the way for safe and reliable AI-based systems with little or no hu- man supervision. A presentation of results to the public is planned for summer 2022. Contact Farzad Nozarian Research Department Agents and Simulated Reality firstname.lastname@example.org +49 681 85775 5462 The LidarShared project team at DFKI‘s Agents and Sim- ulated Reality research area (ASR) uses AI algorithms in combination with solid-state Lidar sensors to bring auton- omous navigation in dense and crowded shared spaces one step closer to practical reality. The idea is to use an AI research framework based on open source operations for various computer vision tasks to reliably detect road users in camera images and Lidar point clouds, and then contin- ue to track them through long enough periods to predict their future routes. A combination of different methods and concepts is employed to realize the project goal – a robust and highly reliable collision avoidance system for autono- mous navigation. The tools include unsupervised learning, knowledge transfer, domain adaptation, and sensor fusion. The research team develops synthetic data capture, labe- ling, and visualization tools to create a multi-sensor, syn- thetic dataset for 3D object detection based on a real-world autonomous driving dataset. To better represent real-life situations, the team improved the quality of the synthetic dataset by carefully ﬁne-tuning the parameters of the sim- ulated sensors and environments. “To collect real-world data, we equipped a test vehicle with a front-facing RGB camera, lidar, IMU, GPS sensors, and an embedded processing unit and captured the data on the Campus of Saarland University,” said project manager Farzad Nozarian. We also developed tools to convert raw data into the pub- lic KITTI format for the Lidar odometric data and the 2D/3D object detection and tracking data. In addition to calibrat- ing the camera and IMU sensors, estimating camera-lidar calibration parameters, and rectifying camera images, the An AI framework is to reliably recognize trac participants in lidar point clouds and camera images.
VISION – Coordinating the European AI network 17 2 2 0 2 / 1 s w e N I K F D The objective of the VISION project is to coordinate and align the work of European networks of AI Excellence Cen- ters: AI4Media, ELISE, Huma- neAI Net, and TAILOR, as well as a vibrant exchange with the European Commission. The key role assumed by DFKI is to organize the collaboration between research and industry. www.vision4ai.eu TAILOR – Trusted European AI At present, 55 partners are working at the European level with representatives from research and industry in TAILOR to develop the scientiﬁc basis for Trusted AI. Approaches and methods from different areas of AI, such as machine learning, are integrated in meaningful combinations to address the components that are important for trusted AI, such as explainability, security, fairness, liability, responsibility, reproducibility, data protection, and privacy, as well as sustainability. https://tailor-network.eu HumanE-AI-Net – Human-centric AI HumaneAI Net brings together top European research centers, universities, and key industry players within a Centers of Excellence Network. The network combines world-leading AI competence with key players in related ﬁelds such as Human-Computer Interaction, cognitive science, and social sciences. www.humane-ai.eu More information https://claire-ai.org Contact Dr. Silke Balzert-Walter Research Department Agents and Simulated Reality Claire Oce Germany email@example.com +49 681 85775 2107
18 D F K I N e w s 1 / 2 0 2 2 (l. to r.) Clemens Hoch, Prof. Martin Ruskowski, Prof. Andreas Dengel, Prof. Philipp Slusallek, Prof. Didier Stricker, Malu Dreyer, CFO Helmut Ditzer, Prof. Paul Lukowicz, Olaf Scholz, Prof. Sebastian Vollmer, CEO Prof. Antonio Krüger. We have a major AI cluster in and around Kaiserslautern and an ambitious AI strategy for Rhineland-Palatinate. DFKI plays a central role in the transfer of research ﬁnd- ings into industrial practice and in the qualiﬁcation of sci- entists. Of course, we are particularly proud that Rhine- land-Palatinate is also providing critical support for the implementation of the federal government‘s AI strategy.” The next speaker was Prof. Professor Antonio Krüger, CEO and Scientiﬁc Director at DFKI, who said, “The visit of the Chancellor is a clear sign that the government continues to assign a high priority to the further development of Ger- many as a center of AI research – even as several global crises have recently overshadowed the topic. Part of our mission is to ensure AI from Germany and Europe is reli- able and trustworthy and ranked among the top leaders in international competition. Today, we demonstrated at the highest level how we are tackling this challenge Accompanied by Minister President Malu Dreyer and State Science Minister Clemens Hoch, the German Chancellor Olaf Scholz was briefed by DFKI CEO Prof. Antonio Krüger and Prof. Andreas Dengel, site director in Kaiserslautern, about selected projects and examples of transfer activities in the innovation-rich atmosphere of SmartFactory-KL. The Chancellor noted the outstanding performance of DFKI in technology transfer, while referencing the many spin-off companies that have been launched and the nu- merous industry partners that make use of DFKI’s exper- tise. Overall, “an impressive visit, a great opportunity to learn, and also ﬁlled with a bit of pride because it‘s hap- pening right here in our country,” said Scholz. “I am very grateful to be here and very impressed. it is important to know that in the ﬁeld of Artiﬁcial Intelligence, Germany is among the world’s leading nations.” German Chancellor Olaf Scholz at the end of his visit to DFKI in Kaiserslautern on March 18, 2022 Minister President Malu Dreyer went on to say, “Digitaliza- tion and the associated modernization is a central polit- ical issue of our time, for the state, for the economy, and for the society. In Rhineland-Palatinate, DFKI has been a leading, commercially-oriented research institute in the ﬁeld of Artiﬁcial Intelligence for more than 30 years. Health and work safety: BIONIC smart sensor network is used to reduce physical loads.
19 2 2 0 2 / 1 s w e N I K F D The centerpiece of the program was “Human-Centric AI” and successful transfer to business and society. in cooperation with the federal government, the states, our shareholders, and industry partners, and we explained our ambitious plans to continue shaping this path in the future.” Prof. Dr. Andreas Dengel, Scientiﬁc Director and Site Man- ager at DFKI-Kaiserslautern and AI ambassador for Rhine- land-Palatinate, said, “The integration of beneﬁcial tech- nologies into society relies on the sustainable transfer of research results. A successful transfer is not a one-way street but depends on a vital ecosystem of research and applications and close cooperation. Today, using selected practical examples, we showed how artiﬁcial intelligence can improve people‘s cognitive work and how AI can help to master major societal challenges such as a pandemic and climate change. The visit by the Federal Chancellor, the Minister President, and the Science Minister under- lines the relevance of AI research. It expresses a great appreciation of the research and transfer achievements of our employees, not just at the Kaiserslautern site, but all of DFKI.” Third Mission: The DFKI transfer ecosystem The presentations included DFKI’s transfer ecosystem, represented by selected technological advances from the Kaiserslautern transfer labs. Special transfer labs provide custom plans for companies of all sizes to enable partners outside of the funded con- sortium projects to continuously and actively participate in current AI developments. The labs follow a proven suc- cess model for the direct transfer of research results to private industry: customer proﬁles and wishes are incor- porated into the targeted design of innovative solutions from the broad ﬁeld of AI research. Over at the AI4EO Solution Factory, DFKI AI expertise is combined with Earth observation data from ESA to de- velop new business models and products. Currently, the largest project in this is the Yield Consortium transfer lab. The aim is to develop better yield prediction and risk models using AI to estimate the condition and growth trajectories for all important crops. The SAIL/Sartorius transfer lab is concerned with develop- ment and use of AI tools for biopharmaceutical products. Researchers here study Deep Learning algorithms and image recognition of cells and organoids for the analysis and modeling of biological systems and for simulation and optimization of biopharmaceutical production processes. The transfer lab known as AIforPol focuses on police work with state and federal authorities (BKA/LKA), researching and testing possible AI applications in the area of inter- nal security. Intelligent solutions are required, in particu- lar, for the analysis of the data associated with evidence gathering and administration, as well as for the recogni- tion of speciﬁc patterns in mass data. Pandemic simulation for municipalities and smart sensor systems for manual labor Other highlights included two practical demonstrations: The AScore Pandemic Cockpit facilitates local level de- cision-making about Corona measures. The intuitive dashboard evaluates the data used to estimate the im- pact of speciﬁc measures at the local level using simu- lation software. AScore: The Pandemic Cockpit for municipalities allows crisis staff to simulate the speciﬁc outcomes of local measures. The BIONIC project demonstrates an intelligent sensor network for reducing physical stress. Objective, real-time motion analysis is performed by mobile secure data sys- tems that are robust and user-friendly to alert people to their poor posture. The technology recently made its way from research to market with the spin-off Sci-Track. Contact Christian Heyer Head of Communications Department DFKI Kaiserslautern firstname.lastname@example.org +49 631 20575 1710
20 D F K I N e w s 1 / 2 0 2 2 Autonomous underwater vehicles (AUVs) independently inspect, maintain, and repair offshore underwater systems – this vision is closer to becoming a reality – thanks to the work of the Mare-IT project, a consortium led by DFKI, which is developing an innovative, two-armed AUV integrated into a powerful IT infrastructure. Regular inspection and maintenance is essential for the safe operation of offshore infrastructures like wind tur- bines and oil and gas production facilities. However, un- derwater work is not only complex and expensive; it also poses a signiﬁcant risk to the divers who perform it. Re- motely operated underwater vehicles (ROVs) are already deployed to monitor the condition of maritime systems. The trend is toward systems that remain in the water for long periods of time, so-called subsea-resident-AUVs, which can operate autonomously and also, if required, via remote control with the help of Artiﬁcial Intelligence (AI) based algorithms. The dual-arm AUV Cuttleﬁsh is launched in the DFKI‘s Maritime Exploration Hall in Bremen. “Once again, Mare-IT demonstrates that machine learning and artiﬁcial intelligence methods are essential to the development of autonomous robots for complex underwater applications. Our research represents an impor- tant building block in making the vision of using AUVs in the offshore industry a practical reality. We appreciate the outstanding collaboration with our strong partners and are very pleased about the successful completion of the project despite the dicult challenges caused by the Corona pandemic.” Prof. Dr. Frank Kirchner Head of DFKI Robotics Innovation Center A consortium of leading companies and research insti- tutes participate in the Mare-IT project in the ﬁelds of IT, robotics, drive systems technology, and offshore engineer- ing under the lead management of DFKI Robotics Inno- vation Center. The team, which in addition to the Cogni- tive Assistants and Embedded Intelligence departments of DFKI, includes WITTENSTEIN cyber motors, SAP SE, and ROSEN Technology and Research Center, made signiﬁ- cant progress. At the end of the project, the project part- ners demonstrated an integrated system that performed successfully. The project developed an innovative,
22 22 D DD F F KK K I I N N e e ww w s s 1 1 / / 2 2 00 0 2 2 2 2 IN THE In a typical market garden, 30 to 50 varieties of vegetables are grown on two and a half acres. Such cultivation is a form of bio-intensive agriculture. It is high yield and soil friendly. If located close to urban areas, the route to the consumer is a short one. Farming demands extensive knowledge about plants and soils as well as manual labor. AI researcher Sebastian Pütz promotes the introduction of innovative management approaches to agriculture. In a startup project, he designs autonomous robots to make it easier to monitor and manage the crops. In times of increasing demand for food from the world‘s expanding population, the worsening climate crisis, and competitive pressures in the agricultural industry, farm- ers are forced to rethink the way they do business and ﬁnd new ways to survive the pressures in this ﬁeld. Smart technologies can strike a balance between economic ef- ﬁciency and ecology. “In my opinion, the exciting thing in agriculture is not the use of AI algorithms for the con- tinuous optimization of what already exists, but in doing things that have not been possible before,” said Pütz from the Plan-based Robot Control research unit at DFKI-Lab Niedersachsen. Within the next two years, he and four DFKI colleagues will develop the software necessary to enable robots to independently record data and navigate between various vegetable crops, grasses, and weeds. Camera-equipped robots create a 3-D plant map, which provides real-time data about the environment in the garden for compari- son. The information is used as a basis to recommend ac- tions to the farmer. Open-source algorithms for robots in uneven terrain, the subject of Putz‘s Ph.D. thesis, are al- ready i n use from Auckland to Oxford in both research A neural network can recognize plants pixel by pixel. For example, a robot is able to differentiate between lettuce and weeds. and practice. Now, these can ﬂow into the development project – PlantMap, a startup project funded by the Ger- man Federal Ministry of Economic Affairs and Climate Ac- tion (BMWK). Under the EXIST research transfer program, around 800,000 euros have been provided since October 2021. The new company was registered in January 2022 and will stand on its own legs by the end of 2023. The concept focuses on so-called market gardens, which are also popping up all over Germany. Modern market gardens, oriented on the Parisian city gardens of the 19th century, reject the use of pesticides and take account of natural soil maintenance and avoid monocropping. The harvest is dependent on knowledge and careful labor. Heavy equipment cannot be used to increase the e- ciency of this cultivation method. This form of agriculture requires ﬁne-tuned machinery that understands small- scale environments and can move carefully within them to assist with crop maintenance – a made-to-order task for AI and robotics. Julian Plagemann from Grööntüügs (north German di- alect for plants) is a market gardener and the ﬁrst user to become a project partner. He majored in agricultural sciences and took over the approximately 25-acre farm from his parents: “I was looking for ways to make the farm sustainable. We don‘t have unlimited land on which to expand our production. Now, I sell my regional and seasonal vegetables online directly to the customer. The math works out well economically.
30 D F K I N e w s 1 / 2 0 2 2 Minister President Malu Dreyer Visits DFKI Branch Oce in Trier “AI technologies have the potential to aid in solving the most pressing societal challenges of our time, whether in the area of health, the environment, or in the social sector. The State of Rhineland-Palatinate recognized this potential 30 years ago and has since supported not only DFKI itself, but also the establishment of additional structures.” Malu Dreyer, Minister President of the State of Rhineland-Palatinate on the occasion of a visit to DFKI branch oce at Trier University on March 28, 2022 Aliated with DFKI‘s Smart Data & Knowledge Services research department in Kaiserslautern, the scientists at the Trier oce conduct research at the interface of AI and business informatics. Prof. Dr. Ralph Bergmann‘s work in the ﬁeld of Experi- ence-based Learning Systems includes, among other things, new approaches to intelligent process monitoring and control in various application areas such as medicine, software robotics, crisis management, and manufactur- ing. The visit included a demonstration showing a model production plant that is monitored and ﬂexibly controlled by artiﬁcial intelligence systems. Another demonstration by researchers on the Agent- Based Social Simulation team, led by Prof. Dr. Ingo Timm, showed the AScore dashboard for pandemic management and introduced its follow-on project AKRIMA. Project AScore – Simulation- based Pandemic Management System for Municipalities Successfully Closed-out The project was speciﬁcally implemented for municipal crisis teams with a management cockpit where, based on real data, information is displayed and the future course of the pandemic is simulated. The combination of intel- ligent information management and AI-based simulati- on was put into practice as part of the ongoing project in the summer 2021, when the crisis team of the city of Kaiserslautern used AScore to better assess the impact of opening recreational facilities relative to the corona- virus pandemic. Project team members presenting the pandemic management cockpit: Dr. Jan Ole Berndt, Benedikt Lüken-Winkels, Alexander Schewerda, Prof. Dr. Ingo J. Timm (l. - r.). AScore uses a user-friendly operator console to display various data and predictions made by the connected si- mulation software regarding the impact of speciﬁc ma- nagement decisions. The overall impact on the population is shown by a Pandemic Pressure Score. In addition to the usual indicators like rate of incidence and hospitalization, the score includes non-medical factors like insolvencies and unemployment as economic and social burdens. This broader base use of key ﬁgures sets the system apart from similar administrative services. At the close-out workshop in November 2021, project manager Prof. Dr. Ingo Timm and his team demonstrated the pandemic management cockpit to the consortium and – in an unusual move for a research project – to the general public via livestreaming. On the Trier University campus, the DFKI team will pursue follow-up projects based on AScore in the coming years. More information https://ascore.kl.dfki.de Contact Prof. Dr. Ingo Timm Head of Cognitive Social Simulation research team Research Department Smart Data & Knowledge Services DFKI Branch Trier Prof. Andreas Dengel, Minister President Malu Dreyer, Prof. Dr. Michael Jäckel, Prof. Ralph Bergmann, and Prof. Ingo Timm. email@example.com +49 651 201 2859
Dr. Shoya Ishimaru Named to DFKI‘s First Endowed Professorship at TU Kaiserslautern Prof. Andreas Dengel Honored with Prestigious Japanese Order of Merit in Artiﬁcial Intelligence 31 2 2 0 2 / 1 s w e N I K F D Dr. Shoya Ishimaru personally coined the term “Psyber- netics” to describe a ﬁeld of research that is developing a sensing-feedback loop between humans, machines, and science. His goal is to use eye-tracking and physi- ological sensing systems to extend the measurable and controllable domain of cybernetics. This involves not only information space and physical space but also in- cludes psychological space, i.e., emotions, affects, and knowledge states. Ishimaru has long been interested in enhancing human cognitive abilities such as learning, thinking, and communicating through the development of new technologies. A longtime employee of the Smart Data & Knowledge Services department of DFKI, he earned his Ph.D. in 2019. That same year, he was awarded the title of MITOU Su- per Creator, which is only awarded to outstanding young researchers by the Japanese Ministry of Economy, Trade, and Industry. Now, the Junior Professor heads the inter- disciplinary research unit “Psybernetics Lab” of the Com- puter Science department at Kaiserslautern University of Technology (TUK). Ishimaru remains connected to DFKI through the Immersive Quantiﬁed Learning Lab (iQL). More information https://psyberlab.de Japanese Consul General Shinichi Asazuma present- ed Professor Dr. Andreas Dengel with the high ranking “Order of the Rising Sun, with Gold Rays and Neck Ribbon” in the name of His Majesty Kaiser Naruhito. The Order was established in 1875 and is awarded in various degrees. The design features rays of sunlight from the rising sun symbolizing the Japanese national ﬂag “hi no maru.” The presentation ceremony was held at the Japanese Consu- late in Frankfurt am Main on April 13, 2022. The country‘s oldest award recognizes Den- gel‘s outstanding contribution to the academic exchange between Japan and Germany in the ﬁeld of artiﬁcial intelligence and his contributions to promoting understanding between the two countries. Andreas Dengel is Executive Director and head of DFKI‘s Smart Data & Knowledge Services research department at DFKI-Kaiserslautern. He is also the Chair of the Artiﬁ- cial Intelligence Department at Kaiserslautern Universi- ty of Technology and an AI Ambassador for the state of Rhineland-Palatinate. In Japan, he is a sought-after con- sultant for science, industry, and politics. He has initiated numerous collaborative projects in research and industry in the ﬁeld of artiﬁcial intelligence and has long been an advocate of German-Japanese cooperation in the eco- nomic exploitation of artiﬁcial intelligence. Dr. Shoya Ishimaru. Prof. Andreas Dengel and Consul General Shinichi Asazuma.
32 N B R I E F D F K I N e w s 1 / 2 0 2 2 N E W S I in Lübeck f DFKI at AI Week 2022 e i r b n 01.–04. November 2022 In today‘s world, we ﬁnd that AI is already being ap- plied at various levels in many industries and, as it continues to evolve, it is creating new opportuni- ties while raising numerous questions. But, what is Artiﬁcial Intelligence? What does it require for use? How does it beneﬁt SMEs? Why does it make sense to engage with Artiﬁcial Intelligence now? The University of Lübeck, Technical University of Applied Sciences Lübeck (THL), Lübeck Chamber of Commerce and Industry, DFKI, and the Hanse Inno- vation Campus Lübeck have joined forces to answer these and many more questions and to showcase the Hanseatic city‘s expertise in the ﬁeld of AI. You are cordially invited to join us and attend the events under the umbrella of AI Week! More information: https://woche-der-ki.de Prof. Dengel Elected to Member- ship on the Executive Committee of INDRC INDRC (International Neurodegenerative Disorders Research Center) is the world‘s leading interna- tional nonproﬁt research center for Alzheimer‘s disease and other neurodegenerative disorders. Its mission is to combine biological approaches with artiﬁcial intelligence and Big Data techniques to develop new treatment methods. As the newest member of the six-member Exec- utive Committee, Dengel gave a presentation en- titled “The Role of Data in Medicine” at the INDRC Symposium attended by Helena Langšádlová, the Czech Minister of Science, Research, and Innova- tion, in Prague on March 10, 2022. This network- ing strengthens the ongoing activities at DFKI in the ﬁeld of human medical research and opens up new avenues to cooperation partners. More information: https://indrc.cz/executive-board i s w e N The Team Around Prof. Drechsler Received “10-Year Retrospective Most Inﬂuential Paper Award” at ASP-DAC 2022 Quantum computing today is considered a technology of the future and a game-changer par excellence. More than ten years ago, researchers at the University of Bremen and DFKI‘s Cyber-Physical Systems department saw its huge potential at a time when quantum computing was little more than an academic thought experiment. In 2012, at the 17th Asia and South Paciﬁc Design Automation Conference, research team members Dr. Mathias Soeken, Prof. Dr. Robert Wille, Christoph Hilken, Dr. Nils Przigoda, and Prof. Dr. Rolf Drechsler published their paper titled “Synthesis of Reversible Circuits with Minimal Lines for Large Functions.” The paper introduced a method for automatically generating reversible circuits that serve as basic building blocks for today‘s quantum programs. In retrospective recognition of their pioneering work, which laid one of the developmental foundations for today‘s quantum computing, they were honored in January 2022 at the 27th Asia and South Paciﬁc Design Automation Conference (ASP-DAC 2022) with the “10-Year Retrospective Most Inﬂuen- tial Paper Award.” More information: https://aspdac2022.github.io Photo from the past: The QBIT project team responsible for the groundbreaking paper in 2012 Photo: AGRA / University of Bremen
34 D F K I P R O F I L E D F K I N e w s 1 / 2 0 2 2 The German Research Center for Artiﬁcial Intelligence (DFKI) was founded in 1988 as a non-proﬁt public-private partnership. It has re- search facilities in Kaiserslautern, Saarbrücken and Bremen, labora- tories in Berlin and Niedersachsen and branch oces in Lübeck and Trier. In the ﬁeld of innovative commercial software technology using Artiﬁcial Intelligence, DFKI is the leading research center in Germany. Based on application oriented basic research, DFKI develops product functions, prototypes and patentable solutions in the ﬁeld of infor- mation and communication technology. Research and development projects are conducted in 24 research departments, nine competence centers and eight living labs.Funding is received from government agencies like the European Union, the Federal Ministry of Education and Research (BMBF), the Federal Ministry for Economic Affairs and Energy (BMWi), the German Federal States and the German Research Founda- tion (DFG), as well as from cooperation with industrial partners.Twice a year, a committee of internationally renowned experts (Scientiﬁc Ad- visory Board) audits the progress and results of state-funded projects. Apart from the state governments of Rhineland-Palatinate, Saarland and Bremen, numerous renowned German and international high- tech companies from a wide range of industrial sectors are repre- sented on the DFKI supervisory board. The DFKI model of a non-proﬁt public-private partnership (ppp) is nationally and internationally considered a blueprint for corporate structure in the ﬁeld of top- level research. DFKI is actively involved in numerous organizations representing and con- tinuously advancing Germany as an excellent location for cutting-edge research and technology. Far beyond the country’s borders DFKI enjoys an excellent reputation for its academic training of young scientists. At present, approx. 850 highly qualiﬁed researchers, administrators and 630 graduate students from more than 65 countries are contributing to more than 400 DFKI research projects. DFKI serves as a stepping stone to leading positions in industry and successful careers as founders of spin-off companies. Over the years, more than 160 staff members have been appointed professors at universities in Germany and abroad. More information www.dfki.de Contact Reinhard Karger, M.A. Corporate Spokesperson German Research Center for Artiﬁcial Intelligence GmbH Saarland Informatics Campus D3 2, 66123 Saarbrücken, Germany firstname.lastname@example.org +49 681 85775 5253 Established 1988, non-proﬁt organization (public-private partnership) Executive Board Prof. Dr. Antonio Krüger Helmut Ditzer Supervisory Board Dr.-Ing. Gabriël Clemens, VSE AG (Chair) Dr. Susanne Reichrath, Representative of Saarland’s Minister President for Higher Education, Science and Technology (Vice Chair) Shareholders Accenture, Airbus Group, Bilﬁnger SE, BMW AG, Cerence GmbH, CLAAS KGaA mbH, Daimler AG, Deutsche Börse AG, Deutsche Messe AG, Deutsche Telekom AG, Empolis Informati- on Management GmbH, Fraunho- fer Gesellschaft e.V., Google Inc., HARTING AG & Co. KG, Intel Corporation, John Deere GmbH & Co. KG, KIBG GmbH, Microsoft Deutschland GmbH, Münchener Rückversicherungs-Gesellschaft Aktiengesellschaft in München, NVIDIA GmbH, RICOH Company Ltd., Robert Bosch GmbH, ROSEN Swiss AG, SAP SE, Sartorius Ventures GmbH, Schwarz-Gruppe, Software AG, Technische Univer- sität Kaiserslautern, Universität Bremen, Universität des Saarlan- des, Volkswagen AG, VSE AG, ZF Friedrichshafen AG International Scientiﬁc Advisory Board Bi-annual evaluation of publically funded projects: Prof. Dr. Andreas Butz, Ludwig-Maximilians-Universität, München (Chairman) Key Figures 2021 Annual Budget: ca. € 76,3 million Professional sta: 850 Graduate student sta: 630
INDUSTRIE 4.0, Digital Twins, Semantic Product Memories • Smart Data – Intelligent Analytics for Massive Data • Wearable Computing and Interactive Textiles • Deep Learning and Machine Learning • Knowledge Management and Document Analysis • Softbots, Digital Assistants, and Chatbots • Educational Technologies • Verification and Evaluation of Safety-critical Applications • Cognitive Social Simulation • Information Extraction and Intelligent Web Retrieval • Multiagent Systems • Experience-based Learning Systems • Visual Computing and Augmented Vision • Mobile and Collaborative Robotic Systems • Multimodal User Interfaces and Autonomous Systems • Shopping Assistance and Intelligent Logistics • Safe and Secure Cognitive Systems and Intelligent Security Solutions • Ambient Intelligence and Assisted Living • Driver Assistance Systems and Autonomous Driving • Cyber-physical Systems • Multilingual Technologies and Language Understan- ding • Business Process Management and Smart Services • Affective Computing • AI in Medicine and Healthcare Kaiserslautern Site Trippstadter Straße 122 D-67663 Kaiserslautern +49 631 20575 0 Saarbrücken Site Saarland Informatics Campus D3 2 D-66123 Saarbrücken +49 681 85775 0 Bremen Site Robert-Hooke-Straße 1 D-28359 Bremen +49 421 17845 0 Laboratory Berlin Alt-Moabit 91c D-10559 Berlin +49 30 23895 0 Laboratory Niedersachsen Berghoffstraße 11 D-49090 Osnabrück +49 541 386050 0 www.dfki.de email@example.com