A NATIONAL INITIATIVE ON EDUCATION AND COMPETENCE DEVELOPMENT IN ARTIFICIAL INTELLIGENCE

As AI is applied in more and more areas, AI has become an important tool in many disciplines at Chalmers, and research and education related to AI is constantly growing. For example, the Section of Data Science (jointly with Gothenburg University) has been formed, with focus on basic research and methods in artificial intelligence. In addition, research is conducted in image analysis and data security related to AI, which can be used for computer-assisted diagnostics and autonomous cars. Design and verification of so-called deep neural networks is another area where several departments have begun research. There is also a focus in research on ethical aspects of AI. Altogether, about 30 researchers at Chalmers work directly with AI and data science, and more than one hundred researchers use AI or work with applications of AI.

In terms of education, Chalmers has about ten courses aimed at artificial intelligence, both at Master’s and Master’s level, such as Machine Learning, Deep Learning, Statistical Methods for Big Data and Data-Driven Support for Cyber-Physical Systems. Chalmers is now developing three new master programs with strong links to AI, with planned start in 2019.

Chalmers concentrates cross-disciplinary activities through its Areas of Advance and the Area of Advance Information and Communication Technology (ICT) has steady AI-related activities. For example, over 20 seminars in AI and Data Science have been organized over the last two years, with over a thousand academics, business and community participants. The Areas of Advance Production, Life Science and Transport also use the AI ​​and data analytics in their research projects.

A large part of Chalmers’s activities are carried out together with Chalmers’s industrial partners: Autoliv, Husqvarna, SKF, Zenuity, Sahlgrenska University Hospital, Volvo AB and Volvo Cars. New AI-related projects are being started in collaboration with ABB, AstraZeneca and Ericsson.

Research and education within AI at Halmstad University is carried out at the School of Information Technology, within the Center for Applied Intelligent Systems Research (CAISR). CAISR focuses on proof-of-concept projects, based on actual needs, that are oriented towards aware intelligent systems. CAISR is based on three subject areas: signal analysis (image analysis), mechatronics and machine learning. The largest area (most active researchers) is machine learning, with about 30 active researchers. Several of the senior researchers at CAISR have had a good scientific impact for a long time, since the early 1990s.

Halmstad University offers campus education with connection to AI in three Bachelor’s programmes (computer and electrical engineering and mechatronics engineering) as well as in two Master’s programmes (computer technology and intelligent systems). Halmstad University also offers online courses in AI for more flexible studies, for example for professionals. Halmstad University is developing an educational programme for professionals within AI and Digital Service Innovation.

Jönköping University is a young professional-oriented university characterised by a high degree of internationalization, an entrepreneurial spirit and extensive collaboration with surrounding society. The university is organized in six Schools, among them the School of Engineering. The Department of Computing is host for Jönköping AI Lab (JAIL) that studies numeric and symbolic AI, visualization, human-computer interaction, AI transformation, etc.

Since 1975, Linköping University has conducted extensive research and education in artificial intelligence, including at the Department AI & Integrated Computer Systems (AIICS). The department has focused on knowledge representation, planning, diagnosis and development of intelligent autonomous cyber-physical systems for collaborative cognitive robots and autonomous vehicles in interaction with humans. The activities have been conducted in cooperation with, in particular, the Swedish aviation industry. Research on knowledge representation is also available in other parts of Linköping University, including in the field of semantic web, extensive ontologies, “mediated” databases and query languages for the web.

At Linköping University, there is also the research group STIMA who studies and develops methods for statistics and machine learning. STIMA cooperates among others with Ericsson in software testing. In the field of control technology, techniques for machine learning are used, for example, in systems identification and model predictive control, for example in collaboration with ABB Sweden.

Deep learning is used in natural language processing, as well as in image analysis, e.g. at the Center for Medical Imaging and Visualization (CMIV). Linked to image processing, the Analytic Imaging Diagnostic Arena (AIDA) is a national arena for research and innovation on AI for medical image analysis, where Sectra and Region Östergötland also have key roles.

Within the undergraduate and master-level education at Linköping University, there are approximately 25 technical courses, mainly at advanced level in traditional AI, robotics, machine learning and deep learning, and offered as electives in various engineering programs. In addition, there is an undergraduate program with a master’s program in cognitive science and an undergraduate program in statistics and data analysis with an add-on program in Statistics and Machine Learning.

Linneaus University focuses on data-driven methods to gain deeper knowledge and understanding in a variety of applications in engineering, science and humanities. Research in computer science, media technology, signal processing and statistics represents the technical core of the center. Combined with research from application fields, such as astrophysics, engineering, linguistics, social science and e-health, we create a unique dynamics. We work in close collaboration with industry and other organizations with research, Industry PhD and competence development.

Applied Artificial Intelligence
Luleå University of Technology has many years of experience in applied artificial intelligence. Our ecosystem of AI-related research links directly to real-world applications in companies and industries. We contribute to safe and measurable AI innovations that make a difference in everyday life and that benefit society at large.

Research – Applied AI Excellence Centre
Within the framework of the Applied AI Excellent Center, we concentrate our combined expertise in Artificial Intelligence in order to create synergies between different research areas. The Centre is also a bridge to the surrounding community and industry. Our Applied AI activities connect research about learning, decision making, big data analytics, edge computing, smart machines, maintenance, critical infrastructure, automation, robotics, control, and cybersecurity research fields that are needed to create the AI ecosystem. This ecosystem will build on innovative business models that will boost the current learning practices and the innovations for improved efficiency, productivity, safety, health, gaming, and the general quality of life. Benefiting from our unique arctic location, we boost AI-applications in various industrial sectors and showcase innovative possibilities in urban and remote regions.

Collaboration and Innovation – Applied AI Innovation Hub
Applied AI Innovation Hub is Luleå University of Technology’s collaborative arena for research in the field of artificial intelligence. The aim of the Applied AI Innovation Hub is to strongly connect with world-leading national and international research organizations, the industrial sectors, the innovative local authorities, innovative SMEs, the growing data center industry and the habitats of the region. The Innovation Hub contributes to improve the quality of productivity, innovation, engineering and every form of activity that AI will influence like everyday life, health, and arts. The Innovation Hub acts as a flagship in AI activities at a national and European level, creating a direct sustainable impact in society.

Education
Our mission is to transfer our knowledge and experience in cutting-edge AI technologies to students and industries. Our needs-tailored AI-focused educational programs are the key to boosting the AI competences, enabling AI innovations and provide world-class education and and life-long learning in theory and application.

Research on AI and machine learning at Lund University takes place at several departments, e.g. Mathematics Centre, where they study basic machine learning, statistics and computer vision. In Computer Science, research is about basic AI, language technology and computer graphics. Other fields of science that concern AI are control, electrical and information technology, philosophy, theoretical physics, experimental medical science and biology.

Education in Machine Learning and AI has been available since the 1980s. Examples of first-level courses are Machine Learning, Artificial Neural Networks and Deep Convolutional Networks, Applied Artificial Intelligence, Language Technology, Image Analysis, and more. In the doctoral programs, several doctoral courses have also been devoted to various aspects of machine learning and AI.

The Artificial Intelligence and Machine Learning Network at Lund University (AI Lund) was formed to facilitate contact between students, industry and society. The innovation system at Lund University is well developed thanks to organizations such as LU Innovation, MINC, Ideon Innovation and Teknopol. Examples of new start-up companies from Lund who develop and use AI and machine learning are Qlik (big data and visualization), Axis (video analysis), Precise Biometrics (fingerprint recognition), Hövding (world’s first crash helmet for cyclists), Polar Rose (face recognition), Cellavision (cell classification) and Exini (medical image analysis).

Planned initiatives for the future at Lund University include a new master’s program in machine learning, several new courses in AI and machine learning, strengthening ties with society through the AI Lund initiative and continuing education courses for the community.

Research in machine learning and artificial intelligence at Mid Sweden University is conducted primarily within the STC research center, Sensible Things that Communicate. STC focuses mainly on developing new sensor-based systems and services that use the Internet-of-Things. The research is conducted in electronics and computer technology, in three strategic research areas: industrial IoT, next-generation measurement systems and large-scale, functional electronic surfaces.

STC is part of Smart Industry Sweden with several doctoral students in e.g. deep learning, predictive maintenance and built-in solutions for machine learning. Within STC, there is also a research profile towards Next Generation Industrial IoT with associated expert competence programs to develop strong research and to provide courses specifically developed for professionals in areas such as AI and machine learning. The courses are delivered over distance and at reduced pace, which makes it possible to combine work and studies. Mid Sweden University also offers single-subject courses in AI that are included in regular master’s programs in Computer Science and Electronics as well as the Master of Science in Computer Science and Electrical Engineering.

Artificial Intelligence (AI) research and education is an important area of the Embedded Systems research profile (one of Mälardalen University’s six prioritized research and education profiles with more than 200 researchers, lecturers and PhD students). AI is also an important research competence for the Innovation and Product Realisation (IPR) profile with many joint research projects and an important part of IoT research projects we are involved in.

Mälardalen University has a long history of applied AI research and already in 2001 the first AI research group at the university was founded by Peter Funk. The research group is well integrated in the global AI community and the Swedish network for AI and ML. AI researchers at the university are also frequently asked to be part if examination boards, promotion issues, invited guest editors and reviewers for high-ranked journals.

The AI research spans over many AI fields of high relevance for industry, health care and business:

Machine Learning and Reasoning for a wide area of application in industry and health care for monitoring, classification, diagnostics, prediction and decision support
Data analysis, feature extraction and selection, data mining, and knowledge discovery
Intelligent sensor, data fusion and sensor signal abstraction
Big data to Smart data and Predictive analytics
Distributed Artificial Intelligence and Machine Learning for Big data
Deep learning for Image Processing and Computer Vision
Evolutionary computing and optimization algorithms

Teaching and Bachelor/Masters degrees
Mälardalen University has AI courses on all levels from bachelor level, master level, PhD courses and for companies where staff wish to extend their knowledge in AI. To mention some courses that we are involved in teaching: Applied Artificial Intelligence, Project in Intelligent Embedded Systems, Machine Learning With Big Data, Deep Learning for Industrial Imaging and Predictive Data Analytics.

KTH’s extensive artificial intelligence activities are available in many different fields of science. It can be anything from basic computer science to transport, life sciences, mathematics, physics, etc. An example is Robotics, Perception and Learning, where there is research in computer vision, robotics and machine learning. Expectations are that research in this area will lead to robotic systems that can be applied in industry, rescue and care and become an integral part of society. The Speech, Music and Hearing Department studies communication and interaction between people through speech and music. There, AI has special relevance for the areas of speech technology and social robotics. The overall goal is to understand the processes involved in human communication and how these can be modeled and supported.

Specific Master’s programs in the AI ​​area at KTH are Systems, Control and Robotics and Machine Learning. KTH also has courses at basic and advanced level in AI and machine learning, deep learning, speech recognition, artificial neural networks, and more. Interest in this type of course has increased significantly over the past ten years.

KTH has extensive collaboration with Sweden’s leading industries in the field: Ericsson, ABB, Scania, Telia and others. For example, the Innovative Centre for Embedded Systems (ICES) is a networking centre for embedded systems operating within cyber-physical systems.

Stockholm University, in the capital of Sweden, is characterised by openness, innovation and collaboration. Ranked among the world’s top 100 universities, Stockholm University is one of Europe’s leading centres for higher education and research in human science and science.

Stockholm University was founded in 1878 with the ambition to revitalise higher education in Sweden. Since its inception, close contact with the wider world and active exchange of knowledge and experience have been integral to this vision.

Currently, the university has 33,000 students, 1,600 doctoral students, and 5,500 members of staff active in the scientific areas of human science and science. We offer 190 programmes and 1,700 courses in science, humanities, social sciences and law, including 75 master’s programmes taught in English. The university has a total revenue of SEK 4.93 billion.

With a global perspective and through collaboration with others, Stockholm University contributes to the development of knowledge. Education and research in human science and science in the international frontline, as well as in interdisciplinary work, make this possible. We make knowledge accessible to all through dialogue, participation in public debate and the development of society.

Research on artificial intelligence at Umeå University is characterized by a large proportion of interdisciplinary research projects and extensive collaboration with different community actors in the region. The AI ​​research includes intelligent systems and robotics for the forestry industry in cooperation with industry in northern Sweden. AI for ergonomic applications, elite athletics, clinical decision support and self-treatment with combinations of AI methods are developed and applied in collaboration with various research groups.

Strong research in methods of machine learning and deep learning takes place in the field of Life Science. In order to strengthen register research at Umeå University, the research is focused on federated databases, where data mining, machine learning and ontologies are in focus. Research on anomaly detection for distributed systems is also under development, and machine learning is also included in research on complex social and biological networks and spread of infection.

Education in the AI ​​field takes place in the field of engineering education on bachelor’s and master’s levels and master’s programs in computer science and cognitive science, as well as master’s programs in robotics and control engineering. Development of new courses in the field has taken place in recent years in order to develop master’s programs in the area and meet demand from students and industry.

The strong growing research environment within AI is being formed on the UmeAI network, with researchers from different departments and faculties. Various research and innovation labs are available at Umeå University, where researchers, students, industry and future users of AI can meet. These labs are being developed, among other things, to create a distributed environment that includes the County Council in Västerbotten lab and the virtual health rooms in the region by Glesbygdsmedicinsk Centrum. “Sliperiet”, in connection with Umeå Design and HumLab, is one of these meeting places with lab resources in the form of a data-driven social innovation lab and SoftLab for smart textiles. Industrial cooperation takes place regionally and internationally with companies, such as Volvo Trucks, Komatsu Forest, Tieto, Boliden Mineral, LKAB, Ericsson Research, IBM, RedHat, Google and Intel.

The University of Gothenburg is a broad academic institution where research and education focused artificial intelligence take place in several fields of science, e.g. behavioral research on effects on behavior of individuals, companies and organizations, ethical aspects and legal responsibility, and more. Economics research can instead address effects of machine learning and AI on companies and society as well as effects of robotic trade in financial and equity markets. In medicine and health science there is research in collaboration with Chalmers and Sahlgrenska University Hospital on digitalization and AI in connection with health care. In artistic activity, interaction design between humans and AI is studied.

At the University of Gothenburg, there is today the cognitive science program with courses in AI, Psychology, Cognition and Design as well as Master’s programs in Data Science and Digital Leadership, the latter dealing with innovation models related to AI. The School of Business, Economics and Law, in collaboration with researchers in archive science and informatics, is building the Master’s program Digital Management focusing on how digitalization, robotization and AI change Swedish administration.

The research program CLASP (Centre for Linguistic Theory and Studies in Probability) uses AI in language technology research. In sociology, together with Chalmers and Harvard, they are also studying how AI can be used to evaluate the impact of social policy in developing countries. In the marine sciences, there is preparedness to create a platform for innovation of different AI systems underwater.

University of Gothenburg wants to develop AI-related research and education in areas, such as pedagogy, humanities, medicine and economics / law in the future.

Artificial intelligence (AI) and the increasing digitalisation of society are changing the way people live and work, and influencing society in general. The consequences need to be studied from multiple perspectives, involving issues relating to technology, ethics, law, philosophy, gender studies, human-computer interaction, linguistics, the education sector, politics and other fields.

Uppsala University’s ambition is to establish a position of strength in research and education in the digitalisation of society and the associated challenges and opportunities. The University has therefore started a five-year strategic action – AI4Research – aimed at strengthening interdisciplinary research and education in AI and machine learning (ML).

Research in artificial intelligence at Örebro University is primarily conducted within one of the university’s strong research environments, namely the Centre for Applied Autonomic Sensor Systems (AASS). The centre today has a special strength when it comes to integrating AI with physically, embedded systems, such as a sensor network or a robotic system. Most of the researchers at AASS are international and have over the years worked with a large number of EU initiatives in collaboration with other international AI researchers.

At AASS, basic research and applications are interwoven in a natural way. Basic research issues focus on knowledge representation and reasoning, planning and scheduling. Research applications are found among heavy industrial vehicles, smart environments (e.g. smart homes) and service robots. Within the Örebro region there is a strong application, not least through a test bed environment within AI and autonomous systems (AI.MEE) with particular emphasis on how AI can strengthen small and medium-sized companies. The use of research within the AI ​​area and the development of innovations also receive support from the University Innovation Office.

The engineering programs in computer engineering at Örebro University have a special focus on intelligent systems. In addition, AASS coordinates a program that offers advanced-level courses in machine learning and artificial intelligence for professionals. The program is in a pilot phase and will expand within the next few years.

Örebro University is a young and cohesive university with a scientific breadth that offers good opportunities to conduct interdisciplinary projects, something that AASS has used over the years. Interdisciplinary projects are ongoing and more initiatives are under way together with researchers from other subjects such as medicine and health, economics, biology, meal science and psychology.