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On the page
Computer Science
Computer Science is the analysis and development of concepts, methods and tools aimed at making the development and use of digital systems easy, reliable and efficient.
Computer Science is a broad discipline that covers a range of topics from theoretical studies of algorithms to the practical issues of implementing computational systems in hardware and software.
The main topic studied at Malmö University is different aspects of Artificial Intelligence (AI), which aims at implementing goal-oriented processes, such as decision-making, adaptation, planning and learning, which are normally found in humans and animals. In particular, we are focussing on Machine Learning (ML), Multi-Agent Systems (MAS), Autonomic Computing (AC), Procedural Content Generation (PCG), and Human-Centred AI. Related to AI, we are also investigating issues like the trustworthiness of systems and user experience.
Other research topics include the study of algorithms in two areas, Recommender Systems (RS) and Computational Geometry. Moreover, research Information Security, in particular with respect to privacy issues, and Systems Engineering, for example, with respect to edge computing and interaction technology. Finally, we are conducting research in modelling, optimization, and simulation for decision support.
Often we study these research topics in different application areas, such as the Internet of Things, sensor networks, building management, computational games, e-commerce, e-health, energy systems, smart homes, smart cities, supply chain management, technology-enhanced learning, public health, and transportation.
Researchers, publications and projects
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2024 | Conference paper
Promising AI Applications in Power Systems: Explainable AI (XAI), Transformers, LLMs
Oleh Lukianykhin, Vira Shendryk, Sergii Shendryk, Reza Malekian
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2024 | Conference paper
Conceptual Design of Multimodal Learning Analytics for Spoken Language Acquisition
Hamza Ouhaichi, Daniel Spikol, Zaibei Li, Bahtijar Vogel
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2024 | Conference paper
EdgeFL: A Lightweight Decentralized Federated Learning Framework
Hongyi Zhang, Jan Bosch, Helena Holmström Olsson
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2024 | Licentiate thesis, comprehensive summary
Machine Learning-Driven Analysis of Sensor Data for Objective Assessment of Parkinson's Disease Motor Symptoms in Home Environments
Gent Ymeri
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2024 | Conference paper
Improving Online Bin Covering with Little Advice
Andrej Brodnik, Bengt J. Nilsson, Gordana Vujovic
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2024 | Conference paper
Blueprinting Organ Donation: A ‘Policy-first’ Approach for Developing Agent-based Models
Michael Belfrage, Christopher Frantz, Bertilla Fabris, Fabian Lorig
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2024 | Article in journal
Artificial Intelligence, Datafication and Exploring the Minimum Content of Nationality
Jason Tucker
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2024 | Conference paper
HOMEFUS: A Privacy and Security-Aware Model for IoT Data Fusion in Smart Connected Homes
Kayode Sakariyah Adewole, Andreas Jacobsson
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2024 | Article in journal
Energy disaggregation risk resilience through microaggregation and discrete Fourier transform
Kayode Sakariyah Adewole, Vicenç Torra
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2024 | Conference paper
LPM: A Lightweight Privacy-Aware Model for IoT Data Fusion in Smart Connected Homes
Kayode Sakariyah Adewole, Andreas Jacobsson
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Research project
Multistakeholder perspectives and experience of trust in digital health and AI
michael.strange@mau.se -
Research project
Agent Based Social Simulation of Organ Donation Policies
fabian.lorig@mau.se -
Research project
Digital when possible, physical when necessary: An exploration of the digiphysical world of Ängelholm hospital
carljohan.orre@mau.se -
Research project
Decent & dignified digital work from the margins. Anticipations from the Global South & invisible platform workers
jakob.svensson@mau.se -
Research project
Customized travel support for travelers with special needs
johan.holmberg@mau.se -
Research project
Future Society and Democracy in Europe
michael.strange@mau.se -
Research project
Artificial Intelligence as an issue for Global Political Economy – actors, structures, constraints, and possibilities
michael.strange@mau.se -
Research project
Evacuation Assistance System
arezoo.sarkheyli-haegele@mau.se -
Research project
Multi-objective optimization and optimal integration of hybrid energy systems
reza.malekian@mau.se -
Research project
Swedish Riksdag 1867–2022: An Ecosystem of Linked Open Data
fredrik.noren@mau.se -
Research project
Facilitators and barriers to the use of agent-based social simulation in organ donation
fabian.lorig@mau.se -
Research project
Climate-Induced Migration in Africa and Beyond: Big Data and Predictive Analytics (CLIMB)
haodong.qi@mau.se -
Research project
DigIT Hub Sweden
paul.davidsson@mau.se -
Research project
Intelligent and Trustworthy IoT Systems
paul.davidsson@mau.se -
Research project
Intelligent Management of Hybrid Energy Systems
reza.malekian@mau.se -
Research project
Fair Data!
sara.leckner@mau.se -
Research project | DOCTORAL PROJECT
Autonomous transport and connected vehicles
reza.malekian@mau.se -
Research project
Realizing the Potential of Agent-Based Social Simulation
paul.davidsson@mau.se
Research environments
Doctoral studies in Computer sciences
Malmö University offers doctoral studies in Computer sciences.
Computer Science is the analysis and development of concepts, methods and tools aimed at making the development and use of digital systems easy, reliable and efficient.
Contact for doctoral studies in Computer science: Reza Malekian