Find Academic Supervisors

• Chemical Risk Assessment
• Science-Policy Interface
• Environmental Toxicology
• +4 more

Marlene Ågerstrand is a Senior Lecturer at the Department of Environmental Science , Stockholm University . Her research focuses on the science-policy interface in chemical risk assessment and management, emphasizing how scientific data inform decision-making, the effectiveness of regulatory strategies, and the role of experts in policy development. She actively collaborates with ecologists, toxicologists, chemists, political scientists, and environmental lawyers. Key affiliations: International Panel on Chemical Pollution (IPCP) Board member Co-developer of the SciRAP web tool for structured chemical evaluations Member of the Baltic Sea Fellows interdisciplinary network Research Interests include improving environmental risk assessments of chemicals, science-policy interactions in chemical management, and pathways to a non-toxic circular economy. She specializes in qualitative methods like document analysis and stakeholder interviews. Recent Publications span environmental quality standards under the Water Framework Directive, essential-use concepts in REACH authorization, regulatory disparities in antimicrobial substance controls, and systematic review frameworks for endocrine disruptors.

• Network Performance
• Cybersecurity
• Congestion Control
• +4 more

Simone Ferlin is an Adjunct Senior Lecturer at Karlstad University and a Senior Performance Engineer. She holds a PhD in Computer Science from Simula Research Lab and Universitetet i Oslo (2017), focusing on robustness in multipath transport protocols like MPTCP. Her research spans network performance, security, and congestion control in mobile/5G networks and the Internet. She collaborates actively with academia and industry, co-supervising students in areas such as edge computing, container orchestration, and distributed systems. Affiliations: Department of Informatics, Karlstad University; Red Hat Research; Ericsson R&D. Education: PhD (2017), Simula/UiO; Master’s and Undergraduate studies emphasized networking and electronics. Her work includes projects like AIDA (AI-driven edge networking) and DRIVE (latency-sensitive mobile services). She has published over 50 papers on topics like QUIC, eBPF, and containerized microservices. Awards include the Best Paper at IEEE ICIN 2021 and ANRP 2025 Prize. Teaching responsibilities include Future Internet Design and Service Quality . Advising spans 15+ students across institutions like TU Berlin, KTH, and Unifesp. She chairs conferences (e.g., ACM SIGCOMM 2025) and serves on editorial boards (IEEE Communications Magazine). Key interests: network observability, low-latency protocols, and sustainability in networking.

• Wireless Communication
• Communication Systems
• Cellular Networks
• +4 more

Ki Won Sung is an Associate Professor at KTH Royal Institute of Technology, specializing in wireless communication systems and network optimization. His research focuses on 5G/6G technologies, integrated sensing-communication systems, cell-free massive MIMO, and stochastic network modeling. Research interests include: Wireless network architecture design and optimization Resource allocation in multi-user communication systems Integrated sensing and communication (ISAC) Stochastic modeling of ultra-dense networks Energy-efficient communication protocols Millimeter wave and massive MIMO systems His recent publications demonstrate strong emphasis on beyond-5G systems, particularly cell-free massive MIMO deployments and URLLC applications. Research trends show consistent focus on network optimization through advanced signal processing, geometric decomposition methods, and cross-layer protocol design. Teaching activities include course management and examination for multiple degree projects and core courses: Communication Systems (IK2200) Mathematical Statistics (IX1501) Mobile Networks and Services (IK2560) Radio Networks (IK2510) Stochastic Simulation (II2206) Wireless Systems (IK1330)

Johan EklundView profile

Associate Professor

• Computer Networks
• Real-Time Systems
• Transport Layer Protocols
• +3 more

Johan Eklund is an Associate Professor in the Department of Computer Science at Karlstad University. He also serves as the Director of Undergraduate Studies and is finalizing his PhD thesis while working part-time as a lecturer. His research focuses on performance issues in computer communication, particularly latency reduction in real-time applications over IP networks, with a strong emphasis on transport layer protocols. He has collaborated extensively with regional industry through initiatives like 'Campus Connect.' Education: B.Sc. (2001) and M.S. (2004) in Computer Science from Karlstad University, followed by doctoral studies. Teaching responsibilities include 'Introduction to Programming and Data Processing' and supervision of bachelor's projects in Computer Science. Research interests span real-time systems, IoT communication, energy efficiency in networks, and transport layer optimization. His recent work includes evaluating NB-IoT energy efficiency and latency reduction in SCTP-based protocols. He has over 20 publications since 2004, with a focus on improving network performance and reducing energy consumption in modern communication systems. Notable collaborations include projects with SNITS (Swedish National Infrastructure for Computing) and industry partners. His work bridges academia and industry, addressing practical challenges in network design and implementation.

Seif HaridiView profile

Professor

• Parallel Computing
• Distributed Computing
• Cloud Computing
• +4 more

Seif Haridi is a Professor at KTH Royal Institute of Technology in Stockholm, Sweden, specializing in parallel and distributed computing systems. He holds dual roles as Chair-Professor of Computer Systems and Chief Scientific Advisor at RISE SICS. His research integrates systems engineering with theoretical foundations, focusing on programming systems, distributed computing, and big data technologies. Key contributions include co-designing SICStus Prolog, the Mozart Programming System, and Apache Flink, as well as leading the development of HOPS, a European big data platform awarded the IEEE Scale Prize 2017. He has led major EU projects like EIT-Digital’s cloud computing initiative and co-founded startups such as LogicalClocks and HiveStreaming. His teaching includes courses on distributed algorithms and peer-to-peer computing at KTH. Notable awards include the European Data Science Technology Innovation 2019. His work spans systems like HOPS, Flink, and Kompics, emphasizing scalability and robustness in distributed environments. Current projects include CDA (Continuous Deep Analytics) and ExtremeEarth for geospatial data analysis. Research interests include distributed algorithms, consensus protocols, and cloud-native systems. His lab’s contributions to scalable storage (e.g., HopsFS) and stream processing (Apache Flink) highlight his impact on both academia and industry.

• Artificial Intelligence
• Machine Learning
• Data Mining
• +12 more

Slawomir Nowaczyk is a Professor at the School of Information Technology , Halmstad University. His research focuses on Artificial Intelligence , Machine Learning , and Data Mining , particularly for Streaming Big Data and Knowledge Representation with Weakly-Supervised Models . Practical applications: Predictive maintenance, healthcare informatics, smart industry, and energy systems Developing interestingness metrics for distributed data analysis and self-organization in AI systems Publication Trends : Recent work spans Explainable AI , spatiotemporal forecasting , feature selection , and smart city applications. Key areas include healthcare diagnostics , transportation optimization , and industrial fault detection . Academic Leadership : Serves as Research Leader for the School of Information Technology. Supervises six PhD students and co-supervises one additional student across academic and industrial domains.

Farzin GolzarView profile

Assistant Professor

• Sustainable Energy Systems
• Artificial Intelligence Applications in Environmental Science
• Circular Economy
• +3 more

Farzin Golzar is an Assistant Professor at KTH Royal Institute of Technology, affiliated with the Heat and Power Technology Division under the Digital Futures Faculty. His research focuses on sustainable energy systems, AI-driven environmental solutions, and circular economy strategies. He is part of a cross-disciplinary initiative at Digital Futures, addressing societal challenges through digital technology innovation. Key research interests include energy transition pathways for oil-dependent economies, optimization of renewable energy systems (e.g., solar-battery hybrids), and AI applications for CO₂ emission prediction. He also explores urban circularity through waste stream management and landfill site identification using GIS-AHP frameworks. His work spans technical-economic analyses of energy systems, battery degradation modeling, and symbiotic food-energy systems (e.g., biogas from manure for greenhouses). Recent studies emphasize climate policy implications and long-term sustainability in urban environments like Stockholm and Curitiba, Brazil. Advising and grants details are not explicitly provided in the text. He collaborates with institutions like RISE Research Institutes of Sweden and Stockholm University through Digital Futures. His lab/center, Digital Futures, is based at Osquars Backe 5, Stockholm.

• Corpus Linguistics
• English Grammar
• Phraseology
• +4 more

Magnus Levin is a Professor at the Department of Languages, Faculty of Arts and Humanities, Linnaeus University. His primary teaching role is within the Non-fiction Translation Master Programme, and he is actively involved in interdisciplinary research initiatives such as the Linnaeus University Centre for Data Intensive Sciences & Applications (DISA) and the Linnaeus University English-German-Swedish Corpus (LEGS). His research spans two core areas: (1) language change and variation in English grammar and phraseology, including studies on tense formation, progressive aspect, collective noun agreement, and phraseological patterns like echoic binomials; and (2) corpus-based translation analysis , focusing on light verb constructions, complex modifiers, and punctuation across English, German, and Swedish. He has pioneered the use of virtual reality for corpus visualization and real-time social media data analysis through the Nordic Tweet Stream project. Recent publications highlight his expertise in cross-linguistic complexity (2024), acronym translation (2021), non-fiction translation (2019), and discourse markers in digital contexts (2016-2021). His work often intersects with Nordic English variation Multilingual corpus design Translation of phraseological units Language change in real-time data Levin collaborates extensively with researchers like Johan Ström Herold, Mirja Laitinen, and Joseph Tyrkkö, contributing to scientific publications in venues such as Languages in Contrast , World Englishes , and Corpus Linguistics and Changing Society . He has also co-edited volumes on contrastive linguistics and sports language analysis.

Eleonora RosatiView profile

Professor

• Intellectual Property Law
• EU Copyright Law
• Fashion Law
• +4 more

Eleonora Rosati is a Professor of Intellectual Property Law at the Department of Law, Stockholm University. She co-directs the LLM in European Intellectual Property Law and teaches modules including Copyright and Transborder Litigation and Fashion and Intellectual Property Law . Her research focuses on EU copyright harmonization, online intermediary liability, AI-related challenges, and fashion industry IP. Education: PhD in EU Copyright Law (European University Institute, 2012) LLM (University of Cambridge, 2009) Laurea Specialistica in Giurisprudenza (University of Florence, 2008) Laurea in Scienze Giuridiche (University of Florence, 2006) Her recent publications analyze AI training data licensing , DSM Directive implementation , and metaverse IP enforcement . She has contributed to policy debates at the European Parliament , WIPO , and EUIPO . Notable awards include the 2022 Adepi Award and recognition as an Influential Woman in IP (2020, 2025) and one of the 50 Most Influential People in IP (2018). She serves as Of Counsel at Bird & Bird and co-edits the Journal of Intellectual Property Law & Practice . As a permanent member of The IPKat team since 2012 and author of over 1,000 posts, she shapes global IP discourse. Her work spans online intermediary responsibilities , text and data mining , and international jurisdiction in digital copyright cases. She has advised on Belgian additional remuneration rights and Italian Supreme Court decisions regarding store layout design protection.

Daniel SkogView profile

Assistant Professor

• Digital Transformation
• Digital Innovation
• Organizational Theory
• +5 more

Daniel Skog is an Assistant Professor at the Department of Informatics , Umeå University, and a key researcher at the Swedish Center for Digital Innovation (SCDI). His work focuses on digital transformation, organizational dynamics, and digital innovation ecosystems. University: Umeå University Department: Department of Informatics Research Center: Swedish Center for Digital Innovation (SCDI) Contact: daniel.a.skog@umu.se Research Focus spans digital transformation drivers, process studies of organizational change, AI platform evolution, and sustainable digital innovation. He coordinates the master's program in IT management and teaches courses on digital innovation, data-driven value creation, and research methods. Recent Publications analyze: Public sector digital transformation Low-code AI platform challenges Data network effects in AI IoT-enabled operational agility XR technology diffusion Platform governance strategies Current Projects include Systematic digital service innovation in the public sector for sustainable development (2023-2027), emphasizing public sector innovation and sustainability.

• Sustainable Manufacturing
• Production Systems
• Virtual Reality
• +7 more

Björn Johansson is a Professor at Chalmers University of Technology, specializing in Production Systems. His research focuses on sustainability aspects of manufacturing through virtual tools, aiming to minimize environmental, social, and economic impacts. Key methodologies include flow simulation, dynamic environmental assessments, 3D visualization, and layout optimization. Primary research areas: Sustainable Manufacturing, Digital Twins, Environmental Impact Assessment Collaborations: Mélanie Despeisse, Henrik Söderlund, and others in automotive, battery production, and maritime industries His work emphasizes integrating digital technologies (e.g., VR, IoT) with sustainable practices, addressing challenges in supply chain resilience, human-robot collaboration, and circular economy models. Recent studies explore VR training environments, 5G-enabled manufacturing, and extended reality (XR) frameworks. Current projects involve 44 initiatives across battery systems, servitization, and digitalization for sustainability. Publications span 179 articles, including topics like digital twin implementation, ergonomic VR assessments, and hybrid simulation models for environmental analysis.

Rickard PetterssonView profile

Senior Lecturer

• Glaciology
• Ice sheet dynamics
• Glacier mass balance
• +5 more

Rickard Pettersson is a Senior Lecturer in Physical Geography at Uppsala University's Department of Earth Sciences, where he works within the Program for Air, Water and Landscape Sciences. His research focuses on glaciology and the dynamics of ice sheets, with particular emphasis on the flow dynamics, stability, and climatic response of glaciers. Dr. Pettersson's research interests center on glacier mass balance, thermodynamics, and the coupling between dynamical and hydrological processes on glaciers and ice sheets. He specializes in collecting, processing, and interpreting geophysical and remote sensing data, and assimilating these data into glaciological models. His work spans multiple geographical regions including Svalbard, Greenland, Antarctica, and Sweden, with particular focus on Storglaciären in Sweden. Analysis of his recent publications reveals a strong focus on Arctic and Antarctic glacial systems, with particular attention to Svalbard. His research examines ice sheet hydrology (particularly firn aquifers), glacier mass balance, subglacial processes, and the impacts of climate change on glacial systems. Methodologically, his work combines field measurements, remote sensing techniques (especially ground-penetrating radar), and numerical modeling approaches. Dr. Pettersson maintains an active research profile with numerous collaborations across international institutions. His work appears in leading journals in glaciology and earth sciences including The Cryosphere, Journal of Glaciology, and Geophysical Research Letters. While specific grant information isn't provided in the available text, his extensive publication record spanning multiple continents suggests participation in significant research projects and collaborations. His research group appears to focus on physical geography with emphasis on glaciological fieldwork and data analysis. The Program for Air, Water and Landscape Sciences at Uppsala University likely provides the institutional framework for his research activities, facilitating studies of cryospheric processes in both Arctic and Antarctic environments.

Sonia-Florina HorchidanView profile

Researcher

• Graph Databases
• Machine Learning on Graphs
• Stream Processing
• +3 more

Sonia-Florina Horchidan is a doctoral researcher at the KTH Royal Institute of Technology in Stockholm, Sweden. She is affiliated with the Division of Software and Computer Systems within the School of Electrical Engineering and Computer Science (EECS), working under the supervision of Associate Professor Paris Carbone in the Data Systems Lab . Her academic activities include teaching assistant roles for courses in distributed systems and data storage paradigms. Research Focus: Graph Databases Machine Learning on Graphs Stream Processing Federated Learning with Privacy Guarantees Approximate Query Processing via ML Serverless Streaming Graph Analytics Scientific Contributions: Her recent publications at venues like EDBT, VLDB, and AI4DB explore intersections between graph data management and machine learning. Key themes include ML inference optimization in streaming systems, privacy-preserving health data forecasting, and innovative graph query execution models. Honors & Service: Co-authored Best Paper at DEEM 2022 Best Paper Award at VLDB 2023 PhD Workshop Program Committee Member, aiDM 2024 Reproducibility Committee Member, ACM SIGMOD/PODS

• Artificial Intelligence
• Machine Learning
• Anomaly Detection
• +6 more

Yuantao Fan is an Associate Senior Lecturer at Halmstad University's School of Information Technology, specializing in artificial intelligence and machine learning applications for industrial systems. His academic work bridges theoretical research with practical implementations in predictive maintenance and equipment monitoring. Dr. Fan's research focuses on Artificial Intelligence, Machine Learning, Anomaly Detection, and Data Mining , with particular emphasis on streaming data from real-world applications. His work spans equipment diagnosis and prognosis, predictive maintenance (PdM), and condition-based monitoring systems. His research integrates self-organizing models with expert knowledge to create robust diagnostic frameworks applicable to transportation systems and industrial equipment. Analysis of Dr. Fan's publication record from 2013-2025 reveals consistent specialization in predictive maintenance for transportation systems , particularly bus fleets and heavy vehicles. His work demonstrates progression from basic fault detection methods to sophisticated hybrid approaches combining physics-based models with deep learning. Recent publications increasingly address explainability in predictive maintenance systems and applications in healthcare analytics. Dr. Fan actively contributes to academic instruction as course responsible and examiner for Databases, Introduction to Linux and Python, and Linux administration system courses. He also teaches Artificial Intelligence, Data Mining, Perspectives on Computer Science and Engineering, Machine Learning for Predictive Maintenance, and AI Implementation courses. His technical expertise spans multiple domains including automotive systems diagnostics, battery health monitoring, acoustic signal processing, and healthcare prediction models. Dr. Fan's work demonstrates strong industry collaboration, particularly with Volvo and city bus fleet operators, translating academic research into practical industrial applications.

• Dynamical systems
• Discrete mathematics
• Machine learning
• +8 more

Jonas Nordqvist is an Assistant Professor at the Department of Mathematics, Faculty of Technology, Linnaeus University. His research spans dynamical systems , discrete mathematics , and machine learning , with a focus on reinforcement learning and interdisciplinary applications.