جست‌وجوی استاد و پژوهشگر

György Kovácsمشاهده پروفایل

مدرس ارشد

• Speech and Language Technology
• Automatic Speech Recognition
• Natural Language Processing
• +۵ مورد دیگر

György Kovács is a Senior Lecturer at Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, working within the Embedded Intelligent Systems LAB. His primary research focus is on Machine Learning applications, particularly in speech and language technology. His research interests span multiple areas of speech and language processing, including: Automatic Speech Recognition across diverse conditions and languages Paralinguistic Speech Processing for emotion detection and speaker state analysis Audio event classification, including medical applications like cough sound analysis Sentiment analysis in written text, with particular interest in hateful language detection Bot detection in social media analysis Kovács has supervised numerous Master's theses since 2021, with topics ranging from accent classification and sentiment analysis to AI-generated code quality assessment. Many of these supervisions have led to co-authored publications with students. His recent publications demonstrate a strong focus on applying machine learning to diverse domains including remote sensing, healthcare technology, and natural language processing. The research shows a clear pattern of interdisciplinary work connecting machine learning with practical applications across environmental monitoring, healthcare, and social media analysis. His academic contributions include co-supervising PhD students such as Sana Al-Azzawi and Nosheen Abid, whose dissertation work on Unsupervised Curriculum Learning for Earth Observation represents significant contributions to the field. Notable publications include work on cloud detection using synthetic datasets, seagrass classification, and emotion classification using EEG in healthcare settings. Kovács also teaches courses including Introduction to Artificial Intelligence (D0032E) and Machine Learning and Pattern Recognition (D0033E), demonstrating his commitment to both research and education in the field of artificial intelligence.

Nosheen Abidمشاهده پروفایل

پژوهشگر ارشد

• Machine Learning
• Unsupervised Curriculum Learning
• Computer Vision
• +۴ مورد دیگر

Nosheen Abid is a Postdoctoral Researcher at Malmö University's Faculty of Technology and Society, Department of Computer Science and Media Technology. Her research focuses on machine learning applications, particularly unsupervised curriculum learning methods for various domains including earth observation, robotics, and computer vision. Her primary research interests include: Machine Learning and Deep Learning Unsupervised Curriculum Learning Computer Vision and Image Analysis Earth Observation and Remote Sensing Human-Robot Interaction Artificial Intelligence for Environmental Applications Abid is actively involved in the project "Human-robot collaborative learning for ultralight electric utility vehicles," which aims to enhance autonomous capabilities through the integration of end-to-end imitation learning with interactive machine learning. Her publication record shows consistent output across multiple application domains, demonstrating expertise in applying advanced machine learning techniques to solve real-world problems in environmental science, neuroscience, infrastructure analysis, and social media. She is affiliated with the Sustainable Digitalisation Research Centre at Malmö University, which studies both social and technological aspects to promote sustainable digitalisation. Her collaborative work with researchers like Marcus Liwicki and others indicates strong interdisciplinary connections across multiple institutions.

• Stochastic Control Theory
• Artificial Intelligence for Optimization
• Power Systems Engineering
• +۳ مورد دیگر

Magnus Perninge is an Associate Professor in Electrical Engineering at Linnaeus University (LNU), Sweden. He previously completed his undergraduate and PhD studies at KTH Royal Institute of Technology and held postdoctoral/researcher positions at Lund University. His teaching includes courses in Automatic Control (basic and advanced), Electric Power Systems , and Electrical Machines . He supervises Alexander Marcial , a doctoral student in Mathematics. Current Affiliation: Linnaeus University (School of Engineering & Faculty of Technology) Past Affiliations: KTH Royal Institute of Technology, Lund University Research Interests: Magnus specializes in the optimal control of stochastic systems with applications in electrical energy systems . He integrates artificial intelligence and machine learning to solve large-scale optimization problems in power systems, aiming to enhance efficiency and sustainability. His work bridges stochastic analysis , operations research , and renewable energy integration . Research Projects: Efficient Hydropower Planning : Optimizing Sweden's hydropower for future intermittent energy scenarios Sustainable Energy & Food Production : Enhancing rural farm energy systems Smart Electrification : Supporting SMEs in Kronoberg and Kalmar regions Research Groups: AI and Machine Learning for Optimization and Operations Research Stochastic Analysis and Stochastic Processes Waves, Signals and Systems