جست‌وجوی استاد و پژوهشگر

Sara Stymneمشاهده پروفایل

مدرس ارشد

• Computational Linguistics
• Natural Language Processing
• Cross-lingual NLP
• +۷ مورد دیگر

Sara Stymne is a Senior Lecturer in Computational Linguistics at the Department of Linguistics and Philology, Uppsala University, where she has been working since 2012. She initially joined as a post-doc (2012-2015), then worked as a researcher (2015-2017), and served as an assistant professor (2017-2023) before her current position as Senior Lecturer. Prior to Uppsala, she was a researcher at Linköping University's Department of Computer and Information Science. Dr. Stymne earned her PhD in Computational Linguistics from Linköping University in 2012 with the thesis 'Text Harmonization Strategies for Phrase-Based Statistical Machine Translation,' following a Licentiate degree in Computational Linguistics (2009) and a Master's degree in Cognitive Science (2006), both also from Linköping University. During her doctoral studies, she spent the autumn of 2010 and spring of 2009 at Xerox Research Centre Europe in Grenoble, France. Her primary research interests focus on cross-lingual natural language processing and digital humanities, with particular emphasis on multilingual dependency parsing. Dr. Stymne is passionate about applying computational linguistics to solve research questions in other fields, including language history, literary analysis, and political science. Her earlier work concentrated on machine translation, with specific interests in discourse-aware translation, compound processing, and error analysis. She has made significant contributions to the development of language technology tools for analyzing dialogue, narrative, and stylistic features in literature. Analysis of Dr. Stymne's recent publications reveals a strong focus on cross-lingual and cross-domain natural language processing. Her work spans multiple subfields including dependency parsing across genres and topics, discourse relation analysis in low-resource languages like Egyptian Arabic, direct speech identification in Swedish literature, and causality detection in governmental documents. A notable trend is her application of NLP techniques to digital humanities problems, particularly in analyzing literary texts and historical language change. Her research often involves creating and utilizing specialized datasets for specific linguistic phenomena across multiple languages. Dr. Stymne actively supervises graduate students, having guided numerous master's and bachelor's theses on topics ranging from speech recognition to multilingual parsing and causality detection. She leads or participates in several research projects including 'Fictional prose and language change' (funded by VR, 2021-2023) and 'Enabling climate-resilient development' (funded by Marianne and Marcus Wallenberg Foundation, 2023-2027), demonstrating her commitment to interdisciplinary research with practical applications. Her work has resulted in several notable software resources including uuPronPred for cross-lingual pronoun prediction, uuparser for dependency parsing, and Docent for document-level machine translation. Within the Computational Linguistics and Language Technology group at Uppsala University, Dr. Stymne contributes to multiple research initiatives focused on developing language technology tools for digital humanities applications. Her team works closely with literary scholars and historians to create computational methods for analyzing large corpora of literary texts, particularly focusing on Swedish literature across different historical periods. Her research bridges the gap between theoretical computational linguistics and practical applications in the humanities, creating new methodologies for quantitative analysis of literary and historical texts.

Matteo Magnaniمشاهده پروفایل

استاد

• Network Science
• Social Network Analysis
• Computational Social Science
• +۱۰ مورد دیگر

Matteo Magnani is a Professor in the Division of Computing Science at the Department of Information Technology, Uppsala University. He leads the Uppsala University Information Laboratory and is a founding member of the Uppsala University Computational Social Science Lab. His research spans network science, artificial intelligence, data science, and computational social science, with a focus on social data mining and multilayer networks. PhD in Computer Science, University of Bologna, 2006 Graduated with honours in Information Sciences, University of Bologna, 2002 Studies in Computer Science at University of Marne la Vallée and Imperial College London Matteo Magnani's research interests include social network analysis, multilayer and probabilistic networks, community detection, visual analytics, and the application of AI to digital media and climate communication. His work bridges computer science and social sciences, particularly in analyzing online discourse and digital intermediaries. He has contributed significantly to the understanding of network structures, uncertainty in networks, and the ethical dimensions of algorithmic analysis. His recent publications highlight trends in fairness in community detection, visual saliency in network layouts, emotional reactions to climate visuals online, and deep learning applications in social media. Topics frequently involve YouTube, Twitter, and online public debates, using advanced network and machine learning methods. Rotary Prize for best student of the Science Faculty Best Paper Award Funniest Presentation Award Best Poster Award Pedagogical Prize from UTN Distinguished University Teacher (Sweden) Docent title (Sweden) Magnani has supervised numerous students and collaborated widely, particularly with Luca Rossi, Alexandra Segerberg, and Davide Vega. He has secured funding from major sources including VR, H2020, STINT, and MIUR. He leads active research labs focused on information systems and computational social science, fostering interdisciplinary collaboration and innovation in network-based research.

• Autonomous Underwater Vehicles (AUVs)
• Multi-Agent Systems
• Robotics
• +۶ مورد دیگر

Özer Özkahraman is a postdoctoral researcher at the Division of Robotics, Perception and Learning (RPL) at KTH Royal Institute of Technology. He works under Ivan Stenius and John Folkesson, focusing on underwater mission planning, simulation, and integration of autonomous systems. His email is ozero@kth.se . He completed his PhD at KTH under Petter Ögren, researching large-scale multi-agent coverage planning for autonomous underwater vehicles (AUVs). Current projects include the SMaRCSim multi-domain simulation platform and development of underwater vehicles like LoLo, SAM, and Evolo. Research interests span autonomous underwater systems, multi-agent coordination, control systems, and simulation infrastructure. He emphasizes modular, accessible frameworks for vehicle testing and real-world deployment. His work bridges theoretical methods (e.g., control barrier functions) with practical applications in marine robotics. Publications focus on AUV navigation, environmental sensing, and adaptive control. Projects like Real2Sim aim to align simulation with real-world vehicle dynamics using motion capture data. He collaborates internationally on topics like data-driven damage detection and model compression for resource-constrained robots. No academic awards are explicitly mentioned. He actively seeks collaborators for projects in sonar simulation, flow field modeling, and cyber-physical system integration.

• Environmental Science
• Environmental Engineering
• Multifunctional Land Use
• +۵ مورد دیگر

Henrik Haller is an Associate Professor at Mid Sweden University, affiliated with the Department of Natural Sciences, Design and Sustainable Development (NDH). His work integrates environmental science with practical applications in tropical regions, particularly focusing on land use, soil remediation, and sustainable food systems. Academic Title: Doctor of Philosophy Location: Östersund, Sweden Key Research Areas: Multifunctional land use, bioremediation, agroforestry, and sustainable development in the Global South Haller's research emphasizes transforming environmental challenges into opportunities. His work includes: Bioremediation of heavy-metal-contaminated soils using amaranth plants Urban agriculture potential in Swedish cities Life cycle assessments of cold-weather aquaponic systems Waste valorization strategies for contaminated lignocellulose sediments Universal design approaches to zero-waste communities Industrial symbiosis for local food systems He has ongoing projects in urban farming, wastewater resource recovery, and sustainable behavior transformation. His publications span topics from fungal metal tolerance to policy challenges in environmental governance.

Magnus Bångمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Human-Computer Interaction
• Automation
• +۳ مورد دیگر

Magnus Bång is a Senior Associate Professor at the Department of Computer and Information Science (IDA) at Linköping University, affiliated with the Artificial Intelligence and Integrated Computer Systems (AIICS) division. His research focuses on advancing human-AI collaboration, automation systems, and AI applications in domains like cyberphysical production, air traffic management, and process industries. He has contributed to interdisciplinary projects involving real-time human-automation interfaces, explainable AI dashboards for industrial processes, and safety-critical systems integration. His work bridges theoretical AI advancements with practical implementations in sectors such as aviation and maritime logistics. Notable collaborations include research with the Swedish Maritime Administration to enhance shipping efficiency through AI and interactive visualization. He actively participates in EU-funded initiatives like the Horizon 2020 projects targeting autonomous systems and air traffic control. Research interests span MLOps for industrial systems, glyph-based communication design for human-automation teams, and operator modeling across traffic management domains. His publications emphasize cross-disciplinary solutions to challenges in automation and human-centric AI design.

• Control Technology
• Distributed Optimization
• Machine Learning
• +۴ مورد دیگر

Mikael Johansson is a Professor at Kungliga Tekniska Högskolan (KTH), specializing in Control Technology . He teaches and coordinates courses such as Distributed Optimization (FEL3311) and various advanced-level degree projects in computer science, electrical engineering, and systems engineering. His research spans Control Systems , Machine Learning , and Optimization , with a focus on asynchronous algorithms, federated learning, and applications in energy systems and construction. His work includes 15 recent publications on topics like neural networks, distributed optimization, and battery technology. Notable areas of contribution are in asynchronous learning, federated learning with privacy constraints, and quasi-Newton methods for optimization. His research bridges theoretical advancements with practical applications in urban design, healthcare, and autonomous systems.

Jonas Monié-Nordinمشاهده پروفایل

دانشیار

• Sámi Archaeology
• Global Historical Archaeology
• Critical Cultural Heritage Studies
• +۶ مورد دیگر

Jonas Monié-Nordin is an Associate Professor at Stockholm University's Department of Archaeology and Classical Studies , specializing in Sámi archaeology , global historical archaeology , and critical cultural heritage studies . His research spans from the High Middle Ages to contemporary societal issues, with particular focus on resource colonialism in Sápmi and Scandinavia's role in early modern globalization. Academic Credentials: PhD in Archaeology (2005, Stockholm University), Docent in Historical Archaeology Ongoing Project: Shared Spaces – Separated Past? (Swedish Science Board funded) investigating Sámi history in Central Scandinavia His interdisciplinary methodology combines material culture analysis, landscape archaeology, and historical source criticism. Recent fieldwork includes excavations of Sámi settlements in Dalarna, Hälsingland, and Uppland. He co-edited Scandinavian Colonialism and the Rise of Modernity (Springer 2013) and authored The Scandinavian Early Modern World (Routledge 2020). Beyond academia, he serves on the Truth Commission for the Sámi People (KU2021.02) and contributes to public debates through media outlets like Dagens Nyheter and Svenska Dagbladet . His work demonstrates how archaeology bridges historical injustice and contemporary reconciliation processes.

• Artificial Intelligence
• Natural Language Processing
• Machine Learning
• +۴ مورد دیگر

Zenun Kastrati is an Associate Professor at the Department of Informatics, Linnaeus University. His research focuses on Artificial Intelligence, Natural Language Processing, Machine Learning, Semantic Web, Sentiment Analysis, and Learning Technologies. He contributes to the Data-driven Business Innovation (DBI) and Interaction Design Research Groups, leading projects like Forest 4.0, RAPID, and IGNITE. His recent work involves Explainable AI, medical imaging, and multilingual NLP. Ph.D. in Computer Science (NTNU, 2018) Master's in Computer Science (EU TEMPUS Programme) Previous Lecturer/Researcher at University of Prishtina His research spans AI applications in medical diagnostics , NLP , sentiment analysis , and semantic technologies . Key projects include Forest 4.0 (environment monitoring) and RAPID (online education in Pakistan). Publications highlight his expertise in deep learning , transformer models , and context-aware systems . Recent publications demonstrate trends in Explainable AI (XAI) for healthcare, medical imaging techniques, and multilingual NLP frameworks. Other work explores social media analytics , student feedback analysis , and pedagogical document classification . Zenun's teaching includes Fundamentals of Programming , Object-Oriented Programming , Web Applications , Data Analytics , and Adaptive Web courses at BSc and MSc levels.

Eleni Stavrinidouمشاهده پروفایل

دانشیار

• Plant Bioelectronics
• Organic Electronics
• Biohybrid Technologies
• +۵ مورد دیگر

Eleni Stavrinidou serves as Senior Associate Professor and Head of Unit at Linköping University's Department of Science and Technology within the Faculty of Science and Engineering. She is Principal Investigator at the Electronic Plants research group within the Laboratory of Organic Electronics (LOE), where she leads groundbreaking research at the intersection of plant biology and electronics. Her educational background includes: Bachelor's degree in Physics (2008) from Aristotle University of Thessaloniki, Greece Master's degree in Nanotechnology (2010) from Aristotle University of Thessaloniki, Greece PhD in Microelectronics (2014) from École Nationale Supérieure des Mines de Saint-Étienne, France Stavrinidou's research focuses on developing bioelectronic devices for plant science with applications in sustainable food production and enhancing plant resistance to environmental stress. Her work explores the integration of electronic circuits within living plants, creating what she terms 'Electronic Plants.' She envisions technologies that enable new discoveries in plant biology while developing next-generation biohybrid systems that combine living and artificial components. Her research spans plant physiology, organic electronics, energy storage in biological systems, and sustainable technological concepts that harness nature's own processes. Her publications demonstrate a clear trend toward developing practical applications of plant bioelectronics, with recent work focusing on energy harvesting from plant motion, glucose-sensitive biohybrid roots, and molecular delivery systems within plants. These studies bridge plant science, materials engineering, and sustainable technology development. Notable scientific recognition includes: ERC Starting Grant (2021) Tage Erlander Prize for Natural Sciences and Technology (2023) L'ORÉAL-UNESCO For Women in Science prize (2019) Future Research Leaders grant from Swedish Foundation for Strategic Research (2020) Marie Skłodowska-Curie Fellowship (2016) Stavrinidou has secured significant research funding including a Swedish Research Council Starting Grant, an EU FET-OPEN grant (which she coordinated), and the ERC Starting Grant for her 4D-PhytoHybrid project. Her research group has developed innovative technologies such as implantable organic electronic ion pumps for hormone delivery in plants, electrically conductive 'soil' for hydroponics, and methods for storing energy in plant roots. She collaborates extensively with the Umeå Plant Science Center and participates in the EU's Horizon 2020 program through the HyPhOE initiative. As leader of the Electronic Plants group at the Laboratory of Organic Electronics, Stavrinidou directs research that follows two main avenues: incorporating electronic circuits into plants for energy storage applications, and developing bioelectronic devices to influence plant functions for greater environmental stress resistance. Her team has achieved notable breakthroughs including creating electronic circuits within rose vascular systems and developing methods to store energy in living bean plants.

• Robotics
• Human-Robot Interaction
• Machine Learning
• +۷ مورد دیگر

Christian Smith is an Associate Professor and Lecturer at the Department of Robotics, Perception and Learning at Kungliga Tekniska Högskolan (KTH Royal Institute of Technology). His research focuses on robotics and applications in human-centered environments like home environments, small workshops, and healthcare facilities, including the development of new robotic systems for research. Teaching Roles: Course Coordinator/Teacher/Examiner for courses such as Introduction to Robotics (DD2410), Research Project in Robotics (DD2411), and Java Programming for Python Programmers (DD1380) Research Themes: Human-Robot Interaction, Behavior Trees, Exoskeletons, Intent Recognition, and Multimodal Perception Awards: No specific scientific awards mentioned in the provided text His KTH profile highlights work on adaptive robotics systems and formalized control strategies. The research portfolio spans from theoretical studies on behavior tree programming to applied work in assistive technologies and teleoperation systems.

Roger Herbertمشاهده پروفایل

مدرس ارشد

• Hydrology
• Hydrogeology
• Biogeochemistry
• +۹ مورد دیگر

Roger Herbert is a Senior Lecturer in Hydrology and Associate Professor in Biogeochemistry at the Department of Earth Sciences, Uppsala University, where he also serves as Director of the Civil Engineering program in Environmental and Water Engineering. His research is centered on biogeochemical processes in water-saturated systems, particularly focusing on denitrification in bioreactors, groundwater remediation, and contaminant transport in double porosity media. His research interests include: Denitrification in woodchip and biochar bioreactors Groundwater and mine drainage treatment Reactive transport modeling in porous media Arsenic speciation and uptake in plants Silica nanoparticle interactions in soil-plant-water systems Microbial controls on nitrogen cycling and greenhouse gas emissions His recent publications (2023–2025) demonstrate a strong focus on innovative bioremediation technologies for wastewater and mine drainage, particularly using biochar and woodchip systems. These works emphasize modeling, microbial ecology, and field-scale applications, showing a consistent trend toward sustainable and scalable solutions for water quality challenges in cold climates and industrial settings. Roger Herbert leads the EIT RawMaterials project NITREM, which aims to upscale bioreactor technology for the mining and quarrying industry. He has supervised or collaborated on numerous studies related to mine waste treatment and environmental impact mitigation. He is actively involved in collaborative research projects and has published extensively in high-impact journals such as Water Research , Journal of Environmental Quality , and Environmental Science & Technology . His work bridges experimental studies, field applications, and numerical modeling, contributing significantly to environmental engineering and hydrogeology.

• Total Productive Maintenance
• Artificial Intelligence
• Multi-Criteria Decision Making
• +۳ مورد دیگر

Ebru Turanoglu Bekar is a Senior Lecturer at the Department of Industrial and Materials Science, Chalmers University of Technology, specializing in Smart Maintenance and Production Systems. She contributes to the Production Service Systems & Maintenance research group. Research Interests: Total Productive Maintenance (TPM), Artificial Intelligence applications in manufacturing, Multi-Criteria Decision Making, Performance Measurement systems Recent Focus: Development of data-driven algorithms for predictive maintenance, integration of digital twins in industrial contexts Key Projects: Factory SensAI (2025–2028) - Data integration for AI in manufacturing Trustworthy Predictive Maintenance TPdM (2022–2025)

Panagiotis Papapetrouمشاهده پروفایل

استاد

• Data Science
• Machine Learning
• Time Series Analysis
• +۵ مورد دیگر

Panagiotis Papapetrou is a Professor of Data Science and Deputy Head of Department at the Department of Computer and Systems Science , Stockholm University (since 2017). He also serves as Head of the Data Science Research Group and holds an Adjunct Professor position at Aalto University (Finland). As a Board Member of the Swedish Association for Artificial Intelligence (SAIS) , he contributes to shaping AI research directions in Sweden. Research Pillars: Algorithmic data mining, interpretable machine learning, time series classification, and health informatics Key Projects: AI for societal fairness, digital twins for smart buildings, EXTREMUM for explainable medical AI, and e-learning personalization Teaching Legacy: Developed courses in Data Mining (HT2013-2022), Machine Learning (VT2022-2024), and Health Informatics (VT2018-2021) His work focuses on interpretable AI for healthcare applications, particularly through counterfactual explanations for time series classification and forecasting. This includes developing methods like Glacier for constrained counterfactuals and Ijuice for k-justified explanations. His research also explores multimodal clustering of sepsis patient records and federated learning approaches for ICU mortality prediction. Recent scientific contributions include: CounterFair (2024): Group fairness analysis via counterfactual burden metrics M-ClustEHR (2024): Multimodal clustering for electronic health records COMET (2024): Constraint-based glucose forecasting explanations Temporal pattern mining (2024-2025): Enhanced forecasting models through decomposition Z-Time (2024): Interpretable multivariate time series classification His editorial leadership includes: Action Editor at Machine Learning Journal (since 2024) Action Editor at Data Mining and Knowledge Discovery (since 2018) Guest Editorial Board for ECML/PKDD Journal Track (2014-2019)

Franziska Klüglمشاهده پروفایل

استاد

• Multi-Agent Systems
• Agent-Based Simulation
• Artificial Intelligence
• +۴ مورد دیگر

Franziska Klügl is a Professor in Computer Science at Örebro University's Faculty of Business, Science and Engineering, affiliated with the Center for Applied Autonomous Sensor Systems (AASS). She currently leads the KKS-funded TeamRob project on Human-Robot Teamwork and serves as Deputy Dean of the faculty since January 2023, chairing the academic appointment committee. Previously, she headed the Computer Science department (2020-2022) and served on the faculty board (2019-2022). Her research focuses on: Multi-agent systems : Development of languages, processes, and tools for agent-based simulation Interdisciplinary applications : Transportation, economics, epidemics, production, and mining simulations Simulation engineering : Integrating AI, machine learning, and formal methods to create accessible modeling tools for domain experts She created SeSAm , a visual programming tool for agent-based simulation that enables rapid prototyping of complex models. Analysis of her recent publications reveals three dominant themes: Human-robot collaboration frameworks and intention recognition systems Economic impacts of automation on labor markets and engineering services Advanced simulation methodologies using affordance theory and reinforcement learning She teaches software engineering, multi-agent systems, and agent-based modeling across multiple programs, including the WASP AI&ML PhD course. She leads research groups at the Machine Perception and Interaction Lab and oversees the TeamRob human-robot teamwork project.

Anders Pousetteمشاهده پروفایل

مدرس

• Organizational Psychology
• Leadership Training
• Information Security
• +۴ مورد دیگر

Anders Pousette is a Lecturer at the University of Gothenburg, affiliated with the Department of Organization, Health and Addiction. His academic work focuses on organizational psychology, leadership training, information security, occupational safety, and psychosocial working conditions in high-risk industries such as healthcare and construction. His research explores the interplay between organizational support climates and workplace safety, with a particular emphasis on ethical value conflicts in healthcare, leadership practices in construction, and security culture in nuclear and transportation sectors. He employs mixed-methods approaches and longitudinal studies to evaluate interventions and workplace dynamics. Recent publications highlight his work on managerial training programs, cross-cultural comparisons of safety practices, and the impact of psychosocial factors on information security behavior. His collaborations span multiple disciplines and institutions, particularly with Marianne Törner and Martin Grill.