Artificial Intelligence and Intelligent Systems
Focus:
Foundational and applied research in Artificial Intelligence and Machine Learning for Intelligent Systems for both industrial, medical and business applications. The research focuses on methods and techniques enabling learning, reasoning, Explainable AI, experience reuse, and experience sharing. We work with both autonomous AI applications as well as decision support systems.
Divisions:
To create intelligent behaviour in systems and services we use artificial intelligence including machine learning and reasoning, deep learning, data analysis, multimodal and lifelong machine learning, knowledge discovery, ontologies, domain knowledge, instance-based learning, deep learning, Explainable AI, multi-agent systems (MAS) to mention some of the methodologies and techniques. AI is today an essential "core" technology in many projects which is reflected in our broad collaboration with other groups, projects and universities both national and international.
Research Focus:
- Research on Machine Learning and Reasoning for a wide area of application in industry and health care for monitoring, classification, diagnostics, prediction and decision support.
- Research on Data analysis, feature extraction and selection, data mining, and knowledge discovery
- Research on Intelligent sensors, data fusion and sensor signal abstraction
- Research on Multimodal and lifelong machine learning,
- Research on Big data to Smart Data and Predictive analytics
- Research on Distributed Artificial Intelligence and Machine Learning for Big data
- Research on Deep Learning for Image Processing and Computer Vision
- Research on Trustworthy AI including technical robustness, explainability/transparency, algorithmic fairness and auditability
Awards and Achievements
The Artificial Intelligence and Intelligent Systems group at Mälardalen University is one of the 6 most productive and successful AI groups in Sweden according to Sweden's innovation agency (Vinnova’s governmental report of April 2018). Members of the group are frequently notified by Research gate to be the most-read authors of scientific papers in the department. Members of the group are frequently invited to give speeches, internationally, at companies (ABB, Siemens, Hägglunds, etc) and by government organisations (e.g. VR, Vinnova) and conferences with an audience of up to 1000 participants. Both Peter Funk and Shaina Begum were nominated and are listed on IVAs (the Royal Swedish Academy of Engineering Sciences) 100-list of influential researchers in digitalization (based on a set of criteria including innovation potential, productivity, application in society, and scientific excellence).
Teaching and Bachelor/Masters Thesis
The AI group has courses on all levels from bachelor level, a master level, PhD courses and for companies where staff wish to extend their knowledge in Artificial Intelligence. The courses are consistently getting high ratings from students in course evaluation. Students in our Bachelors's and Master's programs are confronted with solving real problems for health care and industry and in their master's thesis, they are strongly linked to ongoing research projects. Many master’s projects and research projects have been performed with both SME companies and large companies, e.g. SAAB Group, Volvo CE, ABB Automation, GKN (former Volvo Aero), Volvo Cars, SKF, Ericsson and Siemens.
To mention some courses those we involved in teaching: Applied Artificial Intelligence, Project in intelligent embedded systems, Machine Learning With Big Data (a distance course for industrial professionals), Deep learning for industrial imaging, Predictive analytics etc.
Funding and Grants
The AI group collaboration with industry and projects are in healthcare, road safety, air transport management, and industry 4.0. T industry and business sector with an interest and need for a Trustworthy AI and ML competence. We are always looking for new companies and organisations to collaborate with, much of the funding we receive requires co-funding from companies and we are always looking for partners for interesting and applied AI projects, don’t hesitate to contact us if you have an idea or challenge we may help with, we are both collaborating with large multinational, organisations and Small medium-sized companies.
History of AI group at MDH
The group was founded in 2001 by Peter Funk and is well integrated into the global AI community and the Swedish network for artificial intelligence and machine learning. Peter was the chairman of the Swedish AI society (2006-2009), invited as a conference chair/organiser (ECAI Spain 2004, SAIS Västerås 2005, SCAI 2008 at IVA, ICCBR 2018 hosted by the group, located at Stockholmsmässan), Members in the group are also frequently asked to be part of examination boards, promotion issues, invited guest editors and reviewers for high ranked journals. Strong track record in applied research.
The Artificial Intelligence group is part of one of 4 key research groups within Mälardalen University’s Embedded Systems research profile (one of Mälardalen University's six prioritized research and education profiles with +200 researchers, lecturers and PhD students) and the Artificial Intelligence and Intelligent Systems group is also an active partner in Innovation and Product Realisation profile with joint research projects and applications.
Chip Analysis for Tool Wear Monitoring in Machining: A Deep Learning Approach (Aug 2024) Atiq Ur Rehman, Tahira Salwa Rabbi Nishat, Mobyen Uddin Ahmed, Shahina Begum, Abhishek Ranjan Journal of IEEE Access (Access'18)
Research Issues and Challenges in the Computational Development of Trustworthy AI (Aug 2024) Shahina Begum, Mobyen Uddin Ahmed, Shaibal Barua, Md Alamgir Kabir IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET 2024)
Balancing Fairness: Unveiling the Potential of SMOTE-Driven Oversampling in AI Model Enhancement (May 2024) Md Alamgir Kabir , Mobyen Uddin Ahmed, Shahina Begum, Shaibal Barua, Md Rakibul Islam International Conference on Machine Learning Technologies (ICMLT)
Enhancing Speech Emotion Recognition Using Deep Convolutional Neural Networks (May 2024) M M Manjurul Islam , Md Alamgir Kabir , Alamin Sheikh , Muhammad Saiduzzaman , Abdelakram Hafid, Saad Abdullah International Conference on Machine Learning Technologies (ICMLT)
Deep-IDS: A Real-time Intrusion Detector for IoT Nodes using Deep Learning (May 2024) Sandeepkumar Racherla , PRATHYUSHA SRIPATHI , Nuruzzaman Faruqui , Md Alamgir Kabir Journal of IEEE Access (IEEE-Access)
Combining Ontology and Large Language Models to Identify Recurring Machine Failures in Free-Text Fields (Apr 2024) Marcus Bengtsson, Mobyen Uddin Ahmed, Ricky Stanley D Cruze , Peter Funk, Tomohiko Sakao , Rickard Sohlberg Dr H.C. THE 11th SWEDISH PRODUCTION SYMPOSIUM (SPS24)
