German Research Center for Artificial Intelligencenews 02 I 2022 Download this issue 0 5 e u s s i I K F D 2 2 0 2 © / 1 5 2 2 - 6 9 1 2 - n s s i DFKI Academy Yield Consortium AI Fitness for the Digital Transformation Agriculture and Remote Sensing from Space New DFKI Site in Lower Saxony Another Beacon in the AI Landscape Established

03 L A I R O T I D E 2 2 0 2 / 2 s w e N I K F D TRANSFER AT DFKI DFKI researches “Human-Centric AI.” We believe that society‘s challenges can be successfully mas- tered with the help of AI technologies. That is why it is so important to us that our research and devel- opment results be applied effectively to produce economic and ecological benefits. DFKI transfers its research results by means of collaborative research projects with partners from science and industry, educational programs, the spin-off of AI start-ups, and by the further development of cross-project applications within a solution-oriented context. The DFKI Academy (p. 6) combines DFKI‘s technological knowledge and expertise in an integrated management training program to facilitate the transfer of research results to practical uses. As a partner in the AI Campus learning platform project (p. 18), we also provide modular online seminars, and through the INVITE innovation competition (p. 32), we work on AI-supported systems for continuing professional development and vocational training. The transfer of know-how is also achieved in cooperation with strong science and industry partners in sponsored projects: The Yield Consortium (p. 8) develops forecasting models using satellite data to help an agricultural sector forced to adapt to climate change. The concrete and practical transfer is being addressed with industry partners in the now seven TransferLabs (p. 11). It is also being carried out in projects for the introduction of new technologies in small and medium-sized enterprises, such as the SME Digital Center Kaiserslautern (p. 12) and the Regional Future Center for AI and Digital Transformation Saarland and Rhineland-Palat- inate (p. 13). The project-independent, long-term research project CoMem (p. 15) develops a software prototype for a dynamic enterprise memory, which is already in use productively at a medium-sized energy supplier. DFKI´s spin-offs are another format to achieve the transfer of results: for example, Didactic Innovations (p. 16) commercializes expertise in the field of e-Learning and AI-supported teaching and learning tools. The company‘s finely tuned training and continuing education concepts not only digitalize learning but are also transforming it. AI is changing the way we communicate, work, and live with each other and with machines. The success of the digital transformation depends on AI competence. DFKI is making constructive contri- butions towards this end. Prof. Dr. Antonio Krüger Helmut Ditzer Prof. Dr. Prof. h.c. Andreas Dengel Prof. Dr. Joachim Hertzberg Prof. Dr. Dr. h.c. Frank Kirchner Prof. Dr. Philipp Slusallek

th 2424 29 A Class of its Own – B-Human Wins RoboCup-WC 2022 in Bangkok Without Conceding a Goal 30 Theme Development Workshops for the European AI Roadmap 32 AI Technologies for Continuing Vocational Education – DFKI@INVITE Imprint Issue 50, November 2022, ISSN 2196-2251 Published by German Research Center for Artificial Intelligence GmbH (DFKI) Editorial sta Heike Leonhard, Christof Burgard, Reinhard Karger, Armindo Ribeiro Translation team Glenn Peach, Armindo Ribeiro, Sylvia Krüger, Heike Leonhard Editorial address Saarland Informatics Campus D3 2, Stuhlsatzenhausweg 3, D-66123 Saarbrücken E-Mail news@dfki.de Phone +49 681 85775 5390 Photo credits DFKI, unless otherwise noted. Cover: Blue Planet Studio, stock.adobe.com Layout, Graphics Christof Burgard Production One Vision Design Responsible Heike Leonhard, M.A. Frequency of publication Semi-annual News online www.dfki.de/en/dfki-news 3636 05 T N E T N O C 2 2 0 2 / 2 s w e N I K F D t n e t n o CC C

Who are your programs intended for? HD: There is a need today for management to stay on the ball and look for new potential. We speak to middle and upper management, executives, and heads of de- partments in industry, commerce and the public sector, as well as stakeholders in government and trade unions. What are the current AI topics that impact execu- tives or employees? AK: Several existing AI methods already bring a great deal of “technology-readiness” to the table. These in- clude model-based methods for business and produc- tion processes or image and pattern recognition, which is used in visual quality control. How do you communicate the importance of in- novative AI tools and AI training to your partners? AK: First, we explain how the different approaches and technologies work. We discuss not only opportunities but also problematic experiences. The keyword is machine bias or, dirty data. In AI operations, transparency of results is key. Based on a solid foundation worked out together with the cooperation partner, we determine where the application potential is likely to be found. How does DFKI Academy build individually tailored seminar programs? AK: In preliminary discussions, we analyze the level of experience and knowledge of those responsible, for ex- ample, in the areas of strategic corporate development, digitalization, and project management. For example, have they completed online courses or attended other seminars? Have other AI-related projects been imple- mented? We also look at the company’s objectives. Is there a roadmap covering the next few years? We want to make sure the participants are prepared for the project. Do you have an example of an existing seminar of- fered by DFKI? HD: “AI-Manager” is a seminar we have been offering in cooperation with the Bitkom Academy since 2018. To date, around 100 managers and executives from com- panies in various industries have attended the training. In a pilot project funded by the German Federal Minis- try of Education and Research, we set up the “KI Cam- pus”, a learning website where we curate the content together with the Stifterverband (German joint initia- tive for promoting education, science, and innovation). AK: The academy is the next logical step. The aim of the academy is to build bridges, delve deeper into the mate- rial, and promote interaction among the participants and the seminar leaders. DFKI Academy courses are based on the general subjects of the AI Campus but are mod- ified for the individual requirements of the companies. k i p e e r F , m o c . l e x i p w a r © 07 2 2 0 2 / 2 s w e N I K F D Aren’t there already enough training providers for digital transformation and AI? What makes DFKI Academy special? HD: DFKI knows the state of research just as well as the situation in companies after many years of experience in project work with universities, research institutes, and even the research departments of companies. Meaning: DFKI Academy is best equipped to translate the techno- logical possibilities over to what is industrially feasible. AK: There is a permanent scientific exchange be- tween the DFKI and the local universities: DFKI scien- tists are often closely linked to university research pro- grams as professors, lecturers, and thesis supervisors. DFKI CEO Prof. Dr. Antonio Krüger How does the DFKI Academy benefit from strong ties to the parent company? HD: DFKI Academy can rely on support from DFKI’s speak- ers. A wide range of AI is covered by DFKI’s 27 existing research areas. The content of seminars will reflect this breadth. The academy is not dependent on software providers or their products – instead, it can draw on the expertise of DFKI spin-offs in the field of innovative di- dactics and sector-specific AI training. dactics and sector-speci AI training. sseminars based ity to present pr What objectives have you set? What objectives ve you set? AK: We have the opportunity to present precise, goal- AK: We have the opport oriented, and customized seminars based on the diverse oriented, and customiz range of our research topics – for example, machine learn- range of our research topiccss – for exampl ing, Deep Learning, Smart Data, language technologies, ing, Deep Learning, Smart DData, lang intelligent robotics, and multiagent systems. Initially, we intelligent robotics, and mmuultiagen want to further expand the range of seminars offered by want to further expand thhee rang the DFKI Academy and establish different learning forms the DFKI Academy and estaablish and learning media. Gaining certification as a recognized and learning media. Gainingg certific educational provider for AI is one path that we are evalu- educational provider for AAI is one pat ating. In the future, we will also offer focus seminars from ating. In the future, we willl aalso offer foc the individual research areas. the individual research rreeas.

09 2 2 0 2 / 2 s w e N I K F D cast will be. The answers to basic questions in the area of logistics and grain distribution are now more easily avail- able: What location is best suited for individual crop? What kind of yields can we expect this season? Which herbicides/ pesticides and how much fertilizer should be used? Yield maximization is significantly impacted by the answers to all of these questions. “Our goal is to provide forecasts of agricultural yields as accurately as possible. This should help farmers in their day-to-day decisions. We would like to gradually expand the model to other countries, take more crops into account, and improve the existing models. A model will eventually be designed that can make global predictions for all important crops.” Dr. Marlon Nuske, AI4EO Solution Factory The team is interested in acquiring additional yield data to further develop the model. “We have already begun success- ful collaborations with the agriculture-related companies Smartway and Manexa to supply their yield data. However, we are still looking for more cooperation partners who can provide high-quality yield maps,” said Dr. Marlon Nuske. “The success of the Yield Consortium will help us to at- tract additional industry partners from different subject areas for research, implementation, and practical model development. The combination of AI and EO in the project goes beyond basic research. The ongoing exchange with industry partners at DFKI facilitates knowledge transfer to different application areas via so-called TransferLabs. We look forward to collaborating with additional partners from other industrial sectors,” said Prof Andreas Dengel, Executive Director, DFKI Kaiserslautern and head of the Smart Data & Knowledge Services research area. The perspective from space enables sustainable yields DFKI researcher Dr. Michaela Vollmer describes a practical application: “As it harvests a field, the combine continuous- ly measures the yield in tons per hectare with such a high resolution that it can be assigned to a point of origin in the field. The measured harvest points or ‚geo locations‘ allow us to see at the sub-field level, the point-by-point yield for the field. We use this high-resolution data to match the images from space with a 10 x 10 meter pixel resolution. This has the advantage of being useful for optimizing the training of our machine learning model. In turn, the farm- er is provided with better information to apply individual measures on each field.” THE AI4EO SOLUTION FACTORY The AI4EO Solution Factory was established in the Fall of 2021 in cooperation with ESA. The aim of the AI factory is to apply artificial intelligence to exploit the potential of Earth Observation satellites in space and make it useful to industries on Earth. The possibilities of Earth observation are as limitless as the universe itself. Special solutions are worked out for each custo- mer. At the same time, synergies in these different areas of application are cap- tured to create a foundation on the programming side, parts of which can then be reused in a transfer ecosystem. www.ai4eo-factory.de e r e e D n h o J ©

TRANSFERLABS SUCCESS MODEL BRINGING CUTTING EDGE AI RESEARCH TO BUSINESS Current AI technology brings new application perspectives and potential to companies and business models. Companies know their products and markets; DFKI has the know-how to conduct AI research and prototype development. The cooperative TransferLabs at DFKI are where these natural partners go to meet. m o c . e b o d a . k c o t s , y fl r e t t u b n e e r g © The TransferLabs create a close link between the client and DFKI, which promotes intensive exchange and the transfer of research results into business practices. Companies send representatives who are embedded in DFKI’s excellent re- search ecosystem to work together with researchers on a variety of issues and on the development of defined deliv- erables such as demonstrators, benchmarks, or solutions. The teams are supplemented by grant recipients who con- duct basic research as part of their doctoral studies, which is of vital interest to the industry partners. TransferLabs operate within a contractually defined frame- work in which the commercial and legal aspects of the col- laboration are agreed upon, although in terms of content, there is enough room to respond flexibly and continuously to new requirements, findings, and trends. The advantages to a company are many. The company rep- resentatives are closely integrated into DFKI’s research: they exchange ideas with DFKI scientists and – as a kind of incentive – can pursue a doctorate at the local university under the supervision of a DFKI professor. They are direct- ly integrated into the international AI research scene and participate in colloquia, workshops, guest lectures, disser- tation defenses, etc. The industry-related projects of a transfer lab typically fo- cus on high-potential customer use cases and are comple- Model of the transfer lab research collaboration mented by subject-related basic research, which can also be carried out on the customer data by the grant recipients. TransferLabs facilitate early access to the skilled labor force of tomorrow: Partners net-work directly with students through the TransferLabs. These can be integrated into joint research as part of a master’s or bachelor’s thesis or as a student research assistant and later, recruited as high- ly qualified graduates. DFKI currently operates transfer labs with IAV, Sartorius, Hitachi, ESA, the Federal Criminal Police Oce, the Rhine- land-Palatinate Criminal Police Oce, and also the Deutsche Bundesbank. DFKI transfer expertise also supports part- ners BASF Digital Farming, John Deere, and MunichRe from the AI4EO Solution Factory in the Yield Consortium project (see page 8). More information www.dfki.de/en/web/technologies-applications/ industry/transferlabs Contact Prof. Dr. Andreas Dengel Executive Director DFKI Kaiserslautern andreas.dengel@dfki.de +49 631 20575 1000 PARTNER COMPANY / INSTITUTION TransferLab@ Researchers Employees Project Results Projects Grants Research Results MACHINE LEARNING GRADUATE SCHOOL Site Support University 11 2 2 0 2 / 2 s w e N I K F D m o c . e b o d a . k c o t s , r a k e S h u l a G ©

alone solutions, and the individual systems are not yet inter- connected. Working with MDZ Kaiserslautern, the company wants to network these systems and implement a high-qual- ity, master data concept. Master data represents the “brains of the company” and includes production and product data as well as customer data. Such essential data should be consistent and centrally stored – for accessibility by all departments. Au- tomated production planning is subsequently optimized using AI tools with respect to sustainability aspects such as resource eciency, CO2 emissions, cost, and eciency. Smart data, not big data Such innovative and promising joint projects with SMEs are possible because of the center‘s research staff. The MECO pro- ject team at MDZ Kaiserslautern includes Dr. Jesko Hermann, Keran Sivalingam, and Christian Vollmer, who contribute the results of their own research to the project. Based on data that MECO is currently collecting, the researchers develop a data model of the production processes. The model contains all current operational and production-relevant data. A specially designed AI algorithm evaluates the data model and creates a knowledge database. In the next step, the knowledge data- base is used to optimize production based on various factors such as sustainability, costs, or schedule. “The cooperation with MECO has shown that a future tech- nology such as a knowledge graph is also useful to SMEs. The keyword here is smart data, not big data. When introducing AI methods, 80 percent of the effort is in preparing the data, only 20 percent involves the actual programming of the algorithm. Without a good data structure, it is not practical to deploy AI,” said team member Keran Sivalingam. One SME as a model for others MECO is only one of the many small and medium-sized manu- facturing companies across Germany that can benefit greatly from the digital transformation and AI. The SME Digital Center Kaiserslautern (MDZ) is aware that similar needs exist at many of these other companies as well. SMEs that are considering the next step towards the digital future will find the right part- ner in the MDZ, thanks to its expertise in various subject areas in addition to AI. “The young staff members at MDZ are extremely talented in dealing with various problem-solving techniques, and they have a calm and level-headed way of attacking the problems. The vast experience in implementing such projects that they bring to the table is incredibly valuable to us,” said CEO Ludwig Scholten-Luchsen in describing the cooperation with MDZ. Keran Sivalingam (left) and Christian Vollmer (right) from SME Digital Center Kaiserslautern together with MECO CEO Ludwig Scholten- Luchsen (secondf from left), Production Manager Kai-Uwe Böttinger (in the middle) and QA Manager Thorsten Faber (second from right). The Mittelstand-Digital Zentrum Kaiserslautern (MDZ) is one of several regional centers initiated by the Federal Ministry for Economic Affairs and Climate Action (BMWK). The goal of this nationwide funding initiative is to make small and medium-sized enterprises aware of the im- portance of Industry 4.0, to inform them about the great possibilities, and to actively support them with project implementation. SmartFactory-KL is the lead manager of the consortium. DFKI contributes as a consortium partner with its Kaiserslautern-based Innovative Factory Systems research department (IFS) and the IWi department (Insti- tute for Information Systems) in Saarbrücken. Overall, DFKI AI researchers cover the spectrum of artificial intelligence and expand the center‘s portfolio to include production & development, Work 4.0, strategy & innovation, sustaina- bility, and the sharing economy. More information https://digitalzentrum-kaiserslautern.de Contact Larissa Theis Head of Public Relations Mittelstand Digital Zentrum Kaiserslautern (SME Digital Center Kaiserslautern) Research Department Innovative Factory Systems, SmartFactory-KL larissa.theis@mdz-kl.de +49 631 343 773 35 13 2 2 0 2 / 2 s w e N I K F D m o c . e b o d a . k c o t s , l a n o d o h t ©

m o c . e b o d a . k c o t s , l a n o d o h t © CORPORATE MEMORY 15 2 2 0 2 / 2 s w e N I K F D FROM RESEARCH TO REAL WORLD The cooperation with enviaM is speeding the transfer from research to product: CoMem is already being used produc- tively in municipal support, regulatory codes, construction projects, documentation of correspondence in the digital mailbox, and in knowledge-based assistance systems for accounting. “CoMem embodies the vision of enterprise memory, providing cross-functionalities for content searches as well as need-based topic and user-level dashboards. The time-consuming compilation of the entire spectrum of available data is eliminated by providing dedicated dashboards.” Christian Gruber Property Management, enviaM More information https://comem.ai Contact Dr. Heiko Maus Research Department Smart Data & Knowledge Services heiko.maus@dfki.de +49 631 20575 1110 CoMem also supports energy supplier envia Mitteldeutsche Energie (enviaM) with mobile deployment scenarios. An enterprise that desires to exploit the potential of artificial intelligence faces major challenges: hurdles in the path to implementing AI include a lack of sucient digitalization, cumbersome infrastructures, data silos, and existing sys- tems. DFKI develops an enterprise memory called “CoMem” to address these challenges by providing an infrastructure on which to build and operate an organizational memory. The software uses AI methods to tap into the potential in- herent in various data and embeds the results in employee work environments. CoMem offers extensive knowledge about the data and in- formation spaces, tasks, and processes, as well as the ex- perience and past decisions by the user and the enterprise under comparable conditions. The software combines dis- tributed and heterogeneous sources, then enhances, links, and aggregates them for an upgrade. From this wealth of data, knowledge services are created and integrated as knowledge-based assistance systems at the workstation. CoMem is embedded into the user‘s daily work, where it organizes work structures, enables intelligent search- es, and provides recommendations for upcoming tasks. CoMem is a company ecosystem of knowledge services and interfaces designed for more ecient information and knowledge work. DFKI demonstrates the practicality of the approach in co- operation with Envia Mitteldeutsche Energie (enviaM), a re- gional energy supply company. EnviaM uses CoMem for its property services, where data from a wide variety of sourc- es such as Excel files, team drives, document and image collections, geo-information, wiki instances, and existing property management inventory systems are represent- ed. It is then linked and enriched in a knowledge graph, which does not affect access privileges. The knowledge graph contains statements about plots of land, locations and topics, as well as other resources such as contracts, e-mails, or ocial notices. CoMem knowledge services enable semantic analyses of documents and site links, in addition to structured searches and information regarding a specific context (task). Special dashboards build on-de- mand views of the knowledge graphs. © enviaM, Ariane Gruber

The company still values its roots in research and is in- volved in several lighthouse projects (beacons for digi- tal transformation and development) with DFKI: Clever develops cloud-based software that automatically creates teaching/learning modules with digital media in a project sponsored by Federal Ministry of Education and Research. YouCodeGirls is a project funded by Federal Ministry for Family Affairs, Senior Citizens, Women and Youth that bundles innovative IT learning formats on a platform (website) intended to encourage young women inter- ested in coding to pursue a course of study in computer science. Project KUPPEL is a cooperation with DFKI and other partners to integrate existing learning platforms, for example, the VHS cloud, with the EULE platform of the German Institute for Adult Education. What is interesting about this project is not the technical integration of the systems but the integration of the learning content in a common online portal based on the use of AI technologies (especially, multiagent systems). In this way, the compa- ny is making an important contribution to the idea of a national education platform. The young company has acquired well-known custom- ers like Mercedes-Benz, Siemens, and BDO in just a short time. Didactic Innovations currently employs 60 people and, according to Prof. Thomas, has the mid-term plan- ning goal of doubling this to more than 100 employees. The transfer of research findings and the cooperation with strong research partners such as DFKI are very important to both Thomas and Knopf. That‘s why they deliberately chose to locate the company in the Science Park on the campus of Saarland University in Saarbrücken. The com- pany‘s growth plan for the next two years is driven by two aspects: First, an outsourcing model with its own subsidi- ary company is currently being implemented for the pur- pose of transferring project successes in industry imple- mentations to the school sector. Secondly, the company is currently transforming itself from a service provider to a software company. The COLORS software, which plays a special role for the company, uses AI processes to ac- tively support users as they create high-quality teaching and learning materials. More information https://didactic-innovations.de Contact Caroline Collet Head of Communications Didactic Innovations GmbH Science Park II, 66123 Saarbrücken caroline.collet@didactic-innovations.de +49 681 96870894 17 2 2 0 2 / 2 s w e N I K F D k i p e e r F , l a i c ffi o _ r o t c e v o r c a m © Researchers and Entrepreneurs Prof. Dr. Oliver Thomas is Chair of Information Management and Information Systems at Osnabruck University and Head of DFKI‘s Smart Enterprise Engi- neering research. His research efforts focus on dig- ital transformation, Industry 4.0, data-driven value creation, product-service systems, augmented & virtual reality, as well as digital education and train- ing. He is the founder of several companies, includ- ing Strategion and Didactic Innovations. Univ.-Prof. Dr. Julia Knopf is Chair of German Di- dactics at Saarland University and focuses, in par- ticular, on research on digital education processes in German language training. She is head of the Re- search Institute for Digital Education (FoBiD) in Saar- brucken, which studies new educational programs for schools, universities, and industry while promot- ing the transfer of research results into practice.

© Osaka Metropolitan University 19 2 2 0 2 / 2 s w e N I K F D l. to r.: Hiroyuki Sakugari, Vice President OMU, Prof. Masahiro Tatsumisago, President OMU, Prof. Andreas Dengel, Prof. Koichi Kise. EXPANSION OF COOPERATION WITH OSAKA METROPOLITAN UNIVERSITY An important foundation stone has been laid for the planned establishment of a DFKI research lab in Japan: A cooperation agreement was signed with Osaka Metropolitan University, which describes the further procedure on the way to the „DFKI Lab Japan“. “DFKI‘s planned strategic expansion to Japan is based on a long-standing good partnership with Osaka, Japanese institutes and companies and a common philosophy: to use artificial intelligence for the benefit of people and so- ciety,” said Prof. Dr. Antonio Krüger, CEO of DFKI. “We look forward to expanding our cooperation with Japan, as a high-tech country and like-minded partner, even further in international competition and deepening it in topics rel- evant to the future.“ DFKI had already been working successfully for years with Osaka Prefecture University, which recently merged with Osaka City University this year to form Osaka Metropolitan University (OMU), making it the largest public university in Japan. OMU President Prof. Masahiro Tatsumisago: “The partnership between OMU and DFKI began before the OMU merger, and it developed through years of collaborations in fundamental and practical research in the field of arti- ficial intelligence. With this cooperation agreement, I am certain that the bond between OMU and DFKI will be even stronger, and we will work more closely together to trans- fer our knowledge and technologies to practice, as well as fostering young researchers and students.” Andreas Dengel, Executive Director of DFKI Kaiserslautern and Distinguished Honorary Professor at OMU: “With the DFKI Lab Japan, we want to intensify the existing good re- lationships and cooperations with Japanese universities, research institutions and companies, consolidate them in the long term and establish the DFKI brand even more strongly in Japan. After the worldwide pandemic made in- ternational exchange dicult in the last two years, we are even more pleased to finally be able to take the next step on this path. With Prof. Dr. Koichi Kise, we have succeed- ed in gaining a renowned Japanese AI researcher as a link, who has also known DFKI very well for decades.” k c o t S i , S _ u k a T © Koichi Kise, Professor of Core Informatics and a long-stand- ing research partner of DFKI, was selected as the coordina- tor of the “DFKI Lab Japan” project. Prof. Koichi Kise: “We have been working successfully with Professor Dengel and the DFKI for more than 25 years, promoting joint research and the exchange of personnel. That we are now launch- ing the first DFKI Lab outside Germany at our university is a milestone in our cooperation. I look forward to our ex- change becoming even more active and to positively im- pacting society internationally with our joint research - by jointly advancing the development of human-centric AI technology.” Initially, the scientific exchange will be further intensified, legal framework conditions will be explored, and funding potentials will be identified. The focus of the joint research will be on the areas of smart city, smart university, self- education, and teaching, as well as medical applications. More information www.omu.ac.jp/en Contact Prof. Dr. Andreas Dengel Executive Director DFKI Kaiserslautern and Head of Research Department Smart Data & Knowledge Services andreas.dengel@dfki.de +49 631 20575 1000 Professor Ph.D. Koichi Kise Department of Core Informatics, Graduate School of Informatics Osaka Metropolitan University 1-1 Gakuencho, Naka, Sakai, Osaka 599-8531, Japan kise@omu.ac.jp

Centerpiece of new extension and crowd magnet: Multifunctional hall with artificial lunar crater landscape. patio area and its own playground. This all benefits the staff of 163 employees – supported by around 80 student assistants, temporary staff, and visiting scientists – who currently work in the Robotics Innovation Center and the Cyber-Physical Systems department. Around 90 guests accepted the invitation to attend the ceremony – including former Supervisory Board members Dr. Susanne Reichrath and Dr. Volker Saß, who were hon- ored for their many years of dedicated support. Following the event, the doors to DFKI were opened to the public, and around 1,300 visitors took the opportunity to explore the new laboratories and test facilities, learn about cur- rent projects, experience robotic systems in action, and talk to scientists. Contact Prof. Dr. Frank Kirchner Executive Director DFKI Bremen frank.kirchner@dfki.de +49 421 178 45 4101 21 2 2 0 2 / 2 s w e N I K F D k c o t S i , s t r A e n i L r a t S © The open house following the festive ceremony attracted many interested citizens to the lab and test facility in Bremen. Group photo with Charlie the Robot (back row, l.-r.): Tim Cordßen-Ryglewski, Prof. Frank Kirchner, Prof. Rolf Drechsler and (front) Dr. Andreas Boven- schulte. Missing from photo: Dr. Anna Christmann and Prof. Antonio Krüger, who both appeared via live link. “The building extension again demonstrates the importance of DFKI research to Bremen as a center of science and education. Not only in the areas of artificial intelligence but also in con- tributing to digital transformation, robotics, and lightweight construction. I congratulate DFKI on this innovative development.” Prof. Dr. Antonio Krüger, CEO DFKI It‘s not just another building; it‘s really a research instru- ment with test facilities that are not duplicated anywhere else in Germany.” The new testing facilities, workshops, integration, and oce space afforded by the extension supplement the Maritime Exploration Hall completed in 2013. The exten- sion was one-third financed by the European Regional Development Fund (ERDF) and two-thirds by the com- pany‘s own funds. The centerpiece of the extension is a 17-meter-high multifunctional hall with an artificial lunar crater landscape. An overhead crane with a lifting ca- pacity of 12.5 tons and extensive project areas allow for the deployment of large systems to pursue a wide range of research projects. The two-story experimental struc- ture provides sucient space for motion testing of ro- botic walking, flying, and driving systems. Experiments with walking robots and exo-skeletons are possible in a six-and-a-half-meter high Living Lab with a gravity com- pensation system. Last but not least, the new building also includes an in-house childcare center, which has a Exciting for old and young: DFKI researcher Steen Planthaber controls the SherpaTT robot over a 3D landscape at the Virtual Reality Lab.

23 2 2 0 2 / 2 s w e N I K F D The AROX and LeRO farm robots from the Plan-Based Robot Control department were among the many exhibits set up and staed at the technology fair by all four departments. Prof. Daniel Sonntag (left), Head of Interactive Machine Learning, and Lower Saxony‘s Science Minister Björn Thümler viewing the Visual Awareness Recognition exhibit. as being useful for the technology transfer from basic re- search to application. “We are taking research out of the ivory tower and literally to the field. It’s cool that we do both,” was the general consensus as the event came to a successful end. Contact Prof. Dr. Joachim Hertzberg Executive Director DFKI Niedersachsen joachim.hertzberg@dfki.de +49 541 386050 2251 A supporting program included many exhibits with tech- nology demonstrations in and around the castle, which was very well-received by the guests on a glorious summer day. Celebrating the opening of the fourth DFKI location in Lower Saxony (l. to r.): Prof. Oliver Thomas, Prof. Daniel Sonntag, Lower Saxony‘s Science Minister Björn Thümler, Osnabrück University President Prof. Susanne Menzel-Riedl, Prof. Joachim Hertzberg, DFKI-CEO Prof. Antonio Krüger, Prof. Oliver Zielinski, Oldenburg Mayor Jürgen Krogmann, Oldenburg University President Prof. Ralph Bruder. Not pictured: Osnabrück Mayor Katharina Pötter.

intelligence has faded into the background. The much big- ger challenge is posed by the wonderful mechanics of the human body. Muscles can quickly produce a high acceler- ation, which is generally dicult for robots – even though robots are more accurate and faster. We have mastered this challenge and developed a robot with accelerations similar to those of a human, but this only leads us to the next diculty: A human can step to the side and then per- form the same action again there. A robot would have to be placed on a mobile base before it could do the same, and that implies the need for enormously complex hard- ware, making implementation dicult. Whereas a sta- tionary robot arm is limited in its mobility, it can still learn many different actions while in that position. Nevertheless, table tennis presents a comparatively routine situation. For example, when played according to the rules, the ball must always bounce on the opponent‘s side of the table. The situation in an exciting game of air hockey is not comparable. Unlike table tennis, air hockey can be almost chaotic. For example, hitting the puck in just a minimal- ly different way causes it to end up in a completely dif- ferent spot, and a whole new response must be found if the shot is to be returned. And in air hockey, humans are good at making feints, for example, hinting at moving in a wrong stroke direction. A robot has to learn to react to such tricks. In our research prototype, we let two robotic arms play against each other and positioned other robots in support, for example, to throw in the puck. We consider what kind of intelligence is needed for the game at every level. Air hockey requires motor skills. Furthermore, it involves perception-based input (percep- tual) and more long-term strategies (planning). The ro- bot must have predictive skills and be able to model the opponent. Then, it too can intelligently trick opponents and a more exciting gameplay occurs. These are all dif- ferent cognitive levels and we can draw a lot of insights about how they interact as well as about the differences between neural networks and symbolic AI. Two robotic arms play against each other in the air hockey prototype. What do you see as the future potential of teacha- ble robots? How will this area be further developed? Prof. Daniel Sonntag (links), Leiter des Forschungsbereiches Interaktives Maschinelles Lernen und Niedersachsens Wis- senschaftsminister Björn Thümler am Exponat „Visuelle Aufmerksamkeitserkennung“. Prof. Jan Peters, head of the Systems AI for Robot Learning research area at the new DFKI Lab in Darmstadt. “A huge potential awaits industrial robotics if we no longer have to adapt the environment to the robot.” Prof. Jan Peters At present, robotic applications rely on manually adapting the environment to the robots. Industrial robot environ- ments are so highly developed that hardly a need exists for any sensors to be used. Machines navigate the same trajectories with an accuracy of 150 micrometers. That can be life-threatening for a human who happens to en- ter the workspace. That‘s why you often see often cages around the robots, and great care is taken to keep people away from them. The real potential in industrial robotics exists if we no longer have to adapt the environment to the robot. A former executive board member of Kuka, the global automation company, gets right to the point: “The robots of today perform the same movement millions of times. The robots of the future will perform thousands of different movements just a few times.” This is probably what will characterize the customer-centric products of the future, but it is not feasible with conventional robot programming. To get it right, robotics will have to funda- mentally change: no longer will the environment be adapt- ed to the robot; rather, the robot will learn the tasks and adapt to the environment. This is precisely what the field of “Robot Learning” is working to achieve. In Part 2 of the interview, Jan Peters talks about the affordability of home robots, the fear of the “Terminator,” and sha- res some advice for young resear- chers. Continue reading at www.dfki.de/en/web/news/20000 -euros- for-a-household-robot-prof-jan-peters- expert-interview 25 2 2 0 2 / 2 s w e N I K F D k i p e e r F , y f i d n a r b i ©

OUTSIDE OF THE LAB DFKI ROBOT ON AN ICY MISSION IN NORTHERN SWEDEN 27 2 2 0 2 / 2 s w e N I K F D harsh environmental conditions and whether the devel- oped algorithms performed as expected. After just a few days, it was clear that the extensive preliminary project work, the many test dives in the laboratory pool, and the dedication of the research team had paid off. DeepLeng managed to find its own way back to the ice hole from a distance of 250 meters, and then it docked, fully au- tonomously, with the docking station. This is a small but necessary milestone on the long road to exploration on Jupiter‘s moon, Europa. EurEx-LUNa is the follow-on project to the Europa Ex- plorer and EurEx-SiLaNa projects and has been funded by the Federal Ministry for Economic Affairs and Climate Action (BMWK) since March 1, 2020, under the funding code 50 NA 200 More information www.dfki.de/ric Contact Dr.-Ing. Marc Hildebrandt marc.hildebrandt@dfki.de +49 421 17845 4127 Group photo in front of the tent. Is there life on Jupiter‘s moon Europa? Scientists hope there might be - in an ocean that is suspected to exist un- der a kilometer-thick ice sheet. But the challenge is how to reach it and explore it. The DFKI Robotics Innovation Center has been investigating this question in the Europa Explorer (EurEx) project series since 2012. The develop- ment effort focuses on robotic systems that can pene- trate to the water, autonomously explore it, and remain there for long periods of time. A third project phase on long-range under-ice navigation (EurEx-LUNa) features the AUV DeepLeng, which was initially tested under re- alistic conditions outside the laboratory. In March 2022, five DFKI scientists from Bremen traveled to Abisko, in northern Sweden, to test the feasibility of the concept of autonomous navigation under ice. The task was to use the three-meter-long, signal-yellow AUV to autonomously explore the frozen Lake Torneträsk, which is up to 168 meters deep and located in a national park of the same name. Hosted by the Abisko Scientific Research Station, the researchers spent almost two weeks in the small town north of the Arctic Circle with the support of the station staff. They drove daily from their accommoda- tion to the lake, where they pitched their tent over a hole drilled into the ice, braving the quickly changing winter weather and temperatures ranging from -9 to +5 degrees Celsius. They lowered DeepLeng, which weighs almost 300 pounds (130 Kilograms), into the water through this hole, where it descended under the watchful gaze of the scientists and disappeared beneath the ice cover. From that moment on, it was on its own because Wi-Fi and GPS do not work underwater. It was up to the robot to explore the alien environment, collect data, and find its way back to the ice hole without human help, in murky visibility and a water temperature just above freezing point. The system was active for more than 50 hours in this un- derwater environment. The aim of the dives was to find out whether the vehicle and sensors could withstand the The DFKI tent on Lake Torneträsk. Final prep before the dive.

A CLASS OF ITS OWN WITHOUT CONCEDING A GOAL 29 2 2 0 2 / 2 s w e N I K F D Back after a two-year hiatus due to the Covid pandemic, the World Robotic Soccer Championships were again cont- ested face-to-face – this time in Bangkok, Thailand, in July 2022. Many technical developments have been made in the intervening time. Still, the results in the Standard Plat- form League have not changed much since the last tour- nament in Sydney in 2019: The old and new champion is Team B-Human from DFKI and the University of Bremen. It dominated the final match against the HTWK robots from Leipzig. With a total of 48:0 goals in seven games without conceding a single counter goal, B-Human remains the undisputed world champion. The team from Bremen won the victory in Bangkok with a solid lead over second-place finisher HTWK Robots. The rUNSWift team from Sydney took third place, and the Nao Devils from Dortmund finished in fourth place. Neverthe- less, the pandemic left its mark on this competition. For one thing, there were fewer teams entered. Some teams participated via remote connection from afar. There were also more additional technical competitions. The so-cal- led Technical Challenges are included as a way to explore possible rule changes in the future. For example, this time some matches were played using teams of seven NAO ro- bots. Until now, teams have had only five robots. Another test event checked to see if the robots can recognize the gestures of the referee, which would facilitate direct in- teraction in the future instead of referee decisions being relayed to the players by radio signal. Team B-Human cap- tured the top spot after the final combined score for the four Technical Challenges was announced. Two of the Team B-Human NAO robots with trophies: 1st Place in the main competition and 1st Place in the Technical Challenges. Winners photo with team members who traveled to Bangkok for the RoboCup. The main competition this year was essentially about re- ducing communication between the robots during the matches. Previously, each NAO was allowed to send up to one message per second. The new rule applies to the entire team for the entire game. It limits communication to a maximum number, which effectively corresponds to a reduction in message data by a factor of five. The ro- bot must now consider in advance if it really makes sense to send a message in the current situation. The Bremen team used numerous criteria in order to continue coope- rative team play as well as implementing a sliding upper limit aligned with the remaining match time. It is this team play, in particular, that characterizes B-Human‘s strength, as seen once again in this tournament. Flexible positioning and the dynamic division of duties among the field play- ers, together with the ability to make accurate passes to better-positioned teammates this year, led to B-Human‘s clear superiority on the field in all RoboCup competitions. Team B-Human has now earned its ninth world title in the Standard Platform League. Contact Dr. Thomas Röfer Research Department Cyber-Physical Systems thomas.roefer@dfki.de +49 421 218 64200

31 2 2 0 2 / 2 s w e N I K F D e pres prees e know d wl know know ble AI a ble AI a d the meded m 15 toto n ions tions ns d ntatioi t n h oache ach d mis ing AI. The pr ding A AI. The presen ng nding A i ocra racy and knowled of de democra o e responsible AI app e e w to use w to u nst preconc ceptions and targe n prec preco k h ocused on the f workshop fp d 84 particip formation surrounding AI. The presentations covered the topics of democracy and knowledge in the digital age and how to use responsible AI approaches to pro- tect against preconceptions and targeted misinforma- tion. The workshop focused on the media industry and attracted 84 participants from 15 countries, including representatives from Hensoldt Analytics and Deutsche Welle. Besides TAILOR and Humane-AI-Net, they were joined by the European Network of AI Excellence AI- 4Media (ai4media.eu). Following the opening talk by Alexander von Hum- boldt-Professor Holger Hoos (RWTH Aachen), inter- esting presentations were given by professors Sander van der Linden (University of Cambridge) and Virginia Dignum (Umeå University), as well as by Miguel Poiares Maduro (Chairperson, European Digital Media Obser- vatory EDMO) and Mijke van den Hurk (National Police Lab, Utrecht University). In the breakout sessions after the presentations, participants took the opportunity to exchange ideas, define challenges, and propose possi- ble solution approaches for specific topics. More information https://vision4ai.eu/tdw https://tailor-network.eu/activities/ theme-development-workshops Additional Theme Development Workshops are cur- rently in planning for the Energy, IT Services & Soft- ware, and the Finance & Insurance sectors. Advance contact is now possible via the e-mail address below: tailor_ict48-dfki@dfki.de Contact CLAIRE Oce | Saarbrücken oce-germany@claire-ai.org +49 681 85775 5296 Adra-e: New project on cross-sector collaboration for AI in Europe A new coordination and support activity called Adra-e was launched in July 2022. The project is designed to support the Adra Association (adr-association.eu), especially in its activities concerning the European Com- mission‘s Partnership for AI, Data, and Robotics (ADR). The goal is to connect the European AI, data, and robot- ics communities, map the research and innovation landscape, promote the cross-sectoral application and the development of common standards, and to ensure a degree of sustainability. DFKI is responsible for the work pack- age for coordination between the European ADR initiatives and aims to contribute to a stronger network between the different communities. More information about the project and the Adra association at: https://adra-e.eu

DFKI is a project partner in four INVITE projects KIPerWeb KUPPEL Choosing the course that best matches your in- terests, goals, professional contexts, and prior knowledge from among the many thousands of online learning resources available today is di- cult. The KIPerWeb project has the primary goal of personalizing job-related e-Learning. The DFKI Educational Technology Lab (EdTec) project devel- ops new recommendation systems to help learn- ers find the courses that are right for them – even when few data are available. DFKI is collaborat- ing with the f-bb and IFBB institutes of vocational education, along with the continuing education platforms bfz, BNW, Provadis, and Oncampus, in the KIPerWeb project. Contact Dr. Benjamin Paaßen Research Department Educational Technology Lab benjamin.paassen@dfki.de +49 30 23895 0 KUPPEL is developing a hybrid cloud that helps learners access the programs of other platforms directly from one platform. AI generates recom- mended learning content and learning partnerships to support the knowledge acquisition process and verify individual progress through blockchain-based, secure certificates. Project KUPPEL aims to facil- itate access to learning and make artificial intel- ligence more needs-based, learner-friendly, and transparent. Contact Thorsten Krause Research Department Smart Enterprise Engineering thorsten.krause@dfki.de +49 541 386050 4846 TripleAdapt INVITE-Meta An adaptive triplet is helping to network educa- tion platforms in a socio-technical system. A digi- tal learning environment expands on the concept of digital twins and supports the worker at critical job sequences through adaptive and logical learn- ing paths and recommendations. Recommenda- tions are tailored to the current task and individual training situation and the skills and knowledge of the employee. Middleware networks the various platforms. Blockchain-based micro certificates document the learning progress. Contact Prof. Dr. Peter Fettke Sarah Rübel Institute for Information Systems (IWi) at DFKI peter.fettke@dfki.de | sarah.ruebel@dfki.de +49 681 85775 3106 The 35th project in the competition performs sup- porting research for the 34 INVITE development projects. The task of INVITE-Meta is to systemati- cally support processes in and among all the INVITE projects. The project consortium assesses state- of-the-art science, conducts its own studies, and facilitates networking the projects through reg- ularly scheduled workshops. The focus is on the cognitive and innovation content that is relevant for many INVITE projects, for example, standards for the setup, operation, and review of AI-enabled learning platforms and education technologies. IN- VITE-Meta is jointly managed by the MMB Institute and the DFKI EdTec-Lab. Contact Dr. Berit Blanc Research Department Educational Technology Lab berit.blanc@dfki.de +49 30 23895 5394 33 2 2 0 2 / 2 s w e N I K F D k i p e e r F , m o c . l e x i p w a R ©

35 2 2 0 2 / 2 s w e N I K F D Research department Intelligent Networks celebrates 10 years at DFKI Kaiserslautern DFKI Niedersachsen expands cooperation with Indonesia The Intelligent Networks research department celebrated its tenth anniversary on October 1, 2022. Under the direc- tion of Prof. Hans Schotten, an interdisciplinary team of 51 employees, 9 visiting research scientists, and 28 stu- dent research assistants has contributed to 24 national and European projects. The team works on innovative AI-based concepts for im- plementing particularly sophisticated communication systems in the fields of mobile communications (5G and 6G), industrial communications, and IT security. The aim of the “Open6GHub” project is to develop a 6G vision for people in the highly connected world to come after 2030. By that time, our digital twins will ensure our safety and health, people will interact intuitively with their environment, and AI-based algorithms will guarantee sustainability and protection of critical infrastructures. Additionally, the research department deals with the in- telligent digitalization of production, where automated transport and working machinery will support humans. “Intelligent Networks” are multifaceted and offer compre- hensive research opportunities. They purposefully drive the growing importance of communication networks, as the research group has done now for ten years, and they are highly motivated to continue doing so in the future. More information www.dfki.de/in Contact Prof. Dr. Hans Schotten Head of Research Department Intelligent Networks hans_dieter.schotten@dfki.de +49 631 20575 3000 DFKI Niedersachsen has further strengthened its relations with Indonesia. In early summer 2022, researchers from the Marine Perception research area met with representatives of the Indonesian “Coordinating Ministry for Maritime and Investment Affairs” in Berlin. Under the direction of Prof. Dr. Oliver Zielinski, the research department is heavily in- volved in the field of AI for environmental protection. He has been active in Southeast Asia since 2019, where float- ing plastic waste is being collected in a project that uses drone images and AI-based assessments. As part of several projects funded by the World Bank, studies are conducted in countries heavily affected by plastic waste: Cambodia, Vietnam, the Philippines, and most recently, Indonesia. After their meeting in Berlin, DFKI researchers visited In- donesia to familiarize themselves with the location. The trip was a scientific exchange, which also had the effect of expanding contact with government and business stake- holders for the purpose of intensifying the transfer (and use) of AI methods designed to combat plastic waste. In addition to the Indonesian Bandung Institute of Technolo- gy, the DFKI researchers from Lower Saxony also met with representatives from the ministries and leading environ- mental experts from the World Bank. They also toured the “Interceptor,” a boat from The Ocean Cleanup that auton- omously collects floating debris. More information www.dfki.de/en/web/research/research- departments/marine-perception Contact Mattis Wolf Research Department Marine Perception mattis.wolf@dfki.de +49 441 99833 4714 Ten years "Intelligent Networks": Prof. Schotten's team (third from left, front). Talks in Berlin about possible follow-on projects for AI-based detection of plastic waste in Indonesia: (l. to r.): Dr. Nani Hendiarti (Deputy Minister for Environment and Forest Management), Dr. Ilham Habibi, Luhut Binsar Pandjaitan (Coordinating Minister for Maritime Aairs and Investment), DFKI research scientists Mattis Wolf, Dr. Christoph Tholen, Dr. Frederic Stahl, and Cherie Nursalim.

37 F E I R B N I S W E N 2 2 0 2 / 2 s w e N I K F D Professor Slusallek Reappointed to the Scientific Council of the Institute for Advanced Studies (IAS) at the University of Luxembourg In his second term as a council member for the term Oc- tober 2022 to September 2024, Slusallek will participate in the annual evaluation of interdisciplinary projects and the work of PhD students, and will comment on key IAS activities. Founded in 2020, the Institute‘s mission at the University of Luxembourg is to promote interdisciplinary research, strengthen the research community network, and attract talented early-career researchers to the university. The 13 members of the Scientific Council support and advise the IAS in these efforts. More information: www.fr.uni.lu/ias/ias_governance/members_of_the_ scientific_council_of_the_ias Professor Slusallek Distinguished Speaker at ISC The “International Super- computing Conference (ISC)” in Hamburg is where the international High Per- formance Computing (HPC) community meets with more than 3,000 conference par- ticipants from 59 countries. The distinguished talk series featured Philipp Slusallek, who presented a concept of digital reality developed at DFKI to the professional audience: “Digital Reality: From Learned Models via Synthetic Data to Trusted-AI and Back!” The approach combines modeling, simulation, AI, and HPC to drive the development of “Trusted AI” systems. More information: www.isc-hpc.com/distinguished-talk-2.html DFKI Scientist Dr. Hristina Uzunova Receives Two Scientific Awards Currently employed at the DFKI Lübeck branch oce, Uzunova completed her dissertation “Generative Deep Learning Models for the Automatic Analysis and Synthesis of Medical Image Data Featuring Pathological Structures” summa cum laude. She is now the winner of the prestigious BVM-AWARD 2022 (Medi- cal Image Processing) and the Focus Finder Award 2022 in the category “Image processing applications for X-Ray/MRI/MPI.” In her dissertation, Hristina Uzunova developed machine learn- ing methods, in particular, deep learning methods that improve the automatic processing and analysis of medical images while focusing on pathological findings (for example, tumors). M V B © Prof. Heinz Handels, Director of the Institute for Medical In- formatics at the University of Lübeck and Head of the DFKI research area “AI in Medical Image Processing” at the DFKI Lübeck branch, supervised the doctoral thesis. Prof. Thomas Tolxdor, BVM Program Committee, Dr. Hristina Uzunova. More information: www.initiative-bildverarbeitung.de/veranstaltungen/durchgefuehrte https://www.bvm-workshop.org Second Place at the “Data-driven Business Process Optimization Competition” Prof. Peter Fettke and Alexander Rombach from DFKI’s Institute for Information Systems took second place honors at the first “International Workshop on Data-Driven Business Process Optimization (BPO)” at the 20th Conference on Business Process Management (BPM 2022, Sept. 11-16). The subject of the competition was to develop a scheduling method to simulate and optimize the credit application process at a financial institution over the course of a year. The prize-winning solution prior- itizes resource-critical tasks and avoids potential bottlenecks during process execution. The participation took place within the scope of the Automated Process Planning and Mining project (Project APPaM).

Intelligent Solutions for the Knowledge Society Niedersachsen Site Osnabrück Prof. Dr. Joachim Hertzberg Plan-Based Robot Control Prof. Dr. Oliver Thomas Smart Enterprise Engineering Branch Office Lübeck Prof. Dr. Heinz Handels AI in Medical Imaging Prof. Dr. Alfred Mertins AI in Biomedical Signal Processing Prof. Dr. Ralf Möller Stochastic Relational AIin Healthcare Lübeck Oldenburg Prof. Dr. Daniel Sonntag Interactive Machine Learning Prof. Dr. Oliver Zielinski Marine Perception Oldenburg Bremen Osnabrück Branch Office Trier Smart Data & Knowledge Services Prof. Dr. Ralph Bergmann Topic Field: Experience-based Learning Systems Prof. Dr. Ingo Timm Topic Field: Cognitive Social Simulation Bremen Site Prof. Dr. Rolf Drechsler Cyber-Physical Systems Prof. Dr. Dr. h.c. Frank Kirchner Robotics Innovation Center Berlin Laboratory Berlin Prof. Dr. Gesche Joost Interactive Textiles Prof. Dr. Volker Markl Intelligent Analytics for Massive Data Prof. Dr. Sebastian Möller Speech and Language Technology Prof. Dr. Niels Pinkwart Educational Technology Lab Trier Darmstadt Kaiserslautern Saarbrücken Laboratory Darmstadt Prof. Dr. Carsten Binnig Systems AI for Decision Support Prof. Dr. Kristian Kersting Foundations of Systems AI Prof. Dr. Jan Peters Systems AI for Robot Learning Saarbrücken Site Prof. Dr. Josef van Genabith Multilinguality and Language Technology Prof. Dr. Antonio Krüger Cognitive Assistants Prof. Dr. Peter Loos Institute for Information Systems Prof. Dr. Wolfgang Maaß Smart Service Engineering Prof. Dr. Philipp Slusallek Agents and Simulated Reality Kaiserslautern Site Prof. Dr. Prof. h.c. Andreas Dengel Smart Data & Knowledge Services Prof. Dr. Paul Lukowicz Embedded Intelligence Prof. Dr. Martin Ruskowski Innovative Factory Systems Prof. Dr. Hans Schotten Intelligent Networks Prof. Dr. Didier Stricker Augmented Vision Prof. Dr. Sebastian Vollmer Data Science and its Applications k k i i p p e e e r r FF ©©©© y y z e e ee e e e t t c c c c c e e e e e e v v v / / / / s s s s t t t t r r r r a y r r a H © Living Labs Testing, evaluation, and demonstration of innovative technologies in comprehensive application scenarios Advanced Driver Assistance Systems Living Lab, Bremen Ambient Assisted Living Lab, Immersive Quantified Learning Lab (IQL), Innovative Retail Lab, Robotics Exploration Lab, Smart City Living Lab, SmartFactory-KL, Smart Office Space Living Lab Competence Centers Coordination of research activities in particular areas AI for Environment and Sustainability, Ambient Assisted Living, Autonomous Driving, Deep Learning, Emergency Response and Recovery Management, Safe and Secure Systems, Semantic Web, Smart Agriculture Technologies, Wearable AI