جست‌وجوی استاد و پژوهشگر

• Nanomaterials
• Energy Conversion
• Energy Storage
• +۵ مورد دیگر

Jonas Örtegren is an Associate Professor and Senior Lecturer in the Department of Engineering, Mathematics and Subject Didactics at Mid Sweden University. He serves as the subject representative for Engineering Physics and program manager for both the Master of Science program in Engineering Physics (years 4-5) and the project-based Master by Research in Engineering Physics program. His research focuses on nanomaterials and functional surfaces for energy applications. Örtegren's research explores nanomaterials, functional materials, and surface science with applications in energy conversion (nanogenerators) and energy storage (batteries). His work spans triboelectric energy harvesting, plasmonic devices, battery electrode design, and sustainable energy solutions. Current projects include IMPHET (Innovation Environment for Advanced Materials and Processes with Sustainable Energy Applications) and aluminum-graphite dual-ion battery development. Analysis of his recent publications reveals strong focus on: Advanced battery technologies including silicon anodes and aluminum-ion systems Triboelectric nanogenerators using sustainable materials like wastepaper Plasmonic devices for optical applications Surface engineering and nanomaterial synthesis techniques Primary research trends show integration of energy harvesting with materials science and nanotechnology. Örtegren manages multiple research projects: Flexibla och hållbara fastfasbatterier (Flexible solid-state batteries) ALGCC (Graphene-coated aluminum current collectors) IMPHET innovation environment Aluminum-graphite dual-ion battery development He is affiliated with the FSCN Research Centre and supervises research in nanomaterials and energy systems. No specific students or awards are mentioned in the source material.

Musard Balliuمشاهده پروفایل

دانشیار

• Computer Security
• Programming Languages
• Formal Methods
• +۹ مورد دیگر

Musard Balliu is an Associate Professor at the School of Electrical Engineering and Computer Science at KTH Royal Institute of Technology in Stockholm, Sweden. He works in the Division of Theoretical Computer Science and leads the LangSec (Language-Based Security) research group. His research interests span multiple aspects of computer security, including: Information flow control Web and mobile application security IoT security Low-level security Program analysis and verification Logics in security contexts His recent publications focus on cutting-edge security challenges, with particular emphasis on JavaScript security (prototype pollution vulnerabilities), IoT platform security, database security, and formal methods for security verification. His work often bridges theoretical foundations with practical security solutions, addressing real-world security concerns in emerging technologies like IoT and modern web applications. His notable awards include: Best Reviewer Award at CCS 2022 Google Research Scholar Award in 2022 Facebook Award in Privacy-Enhancing Technologies in 2021 Dr. Balliu actively mentors students in the LangSec group, supervising both current students and recently graduated PhD candidates. He serves as Principal or Co-Principal Investigator on multiple research projects funded by prestigious organizations including Digital Futures, WASP, VR, and SSF, with a focus on next-generation security solutions for IoT, software supply chains, and cloud computing. He is also involved in various cybersecurity initiatives including the Swedish National Hacking Team (as co-founder and SC representative for Sweden), CDIS Cybercampus Sverige, and Digital Futures, demonstrating his commitment to advancing cybersecurity education and practice beyond academic research.

Seif Haridiمشاهده پروفایل

استاد

• Parallel Computing
• Distributed Computing
• Cloud Computing
• +۴ مورد دیگر

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.

• Formal Logic
• Cybersecurity
• Social Engineering
• +۷ مورد دیگر

Andreas Brännström is a postdoctoral fellow at the Department of Computing Science , Umeå University, Sweden. His research focuses on formal logic-based methods for modeling and verifying manipulation, deception, and influence in communication , with applications in cybersecurity and social engineering. He employs frameworks such as Answer Set Programming, Formal Argumentation, and Description Logic to analyze mental states, belief change, and dialogue strategies in autonomous systems. His work intersects artificial intelligence , computational ethics , and human-agent interaction . Key research themes include: Formal verification of deceptive communication Computational empathy modeling Trust-based argumentation systems Behavior change interventions for autism Human-aware planning in hybrid AI Cross-cultural affective knowledge representation Recent publications analyze manipulation dialogues , critical friend agents , and emotion-aware planning using formal methods. The research contributes to responsible AI and trustworthy human-agent collaboration . Current projects include strategic argumentation frameworks (2020-2024) and collaborative mixed-reality tools for autism support. He is affiliated with the Formal Methods for Trustworthy Hybrid Intelligence research group and contributes to Responsible Artificial Intelligence initiatives.

Mohamed Faouzi Atigمشاهده پروفایل

استاد

• Model Checking
• Program Verification
• Concurrency
• +۷ مورد دیگر

Mohamed Faouzi Atig is a Professor in Computer Systems at the Department of Information Technology, Uppsala University. His career spans roles as Senior Lecturer (2018-2021), Associate Senior Lecturer (2014-2018), and Researcher (2012-2018) at the same institution. He obtained his Doctoral Degree in Computer Science from the University of Paris Diderot-Paris 7 (2010) and a Master in Engineering from Tunisia Polytechnic School (2005). Current Role: Professor in Computer Systems Institution: Uppsala University Research Focus: Model checking, verification of infinite-state systems, weak memory models, automata theory, string constraints, concurrent program analysis His research explores formal methods for concurrent programs, weak memory models (TSO/PSO/POWER), automata theory for verification, and SMT solvers for string constraints. Recent work integrates graph neural networks with word equation solving and advances stateless model checking techniques. Key article trends include Weak Memory Model Verification (TSO, PSO, POWER) Stateless Model Checking Algorithms String Constraint Solvers (TRAU, Norn) Timed Automata and Multi-Pushdown Systems Mohamed Faouzi Atig has led collaborations on fence insertion procedures, timed pushdown automata, and database-driven system verification. His contributions are recognized through publications in top-tier conferences and journals.

Farnaz Adib Yaghmaieمشاهده پروفایل

استادیار

• Control Theory
• Reinforcement Learning
• Machine Learning for Control Systems
• +۵ مورد دیگر

Farnaz Adib Yaghmaie serves as an Assistant Professor and Docent at Linköping University's Department of Electrical Engineering (ISY), specializing in the Automatic Control division. Her research bridges control theory and machine learning, with significant contributions to reinforcement learning applications in complex systems. Education: Ph.D. in Electronic and Electrical Engineering, Nanyang Technological University (NTU), Singapore (2017, Best Thesis Award) Master's Degree in Electrical Engineering (Control), K. N. Toosi University of Technology, Tehran, Iran (2011) Bachelor's Degree in Electrical Engineering (Control), K. N. Toosi University of Technology, Tehran, Iran (2009) Her research focuses on redefining machine learning paradigms for control problems , particularly through reinforcement learning applications. Current projects include Foundation Models and RL for General-Purpose Control (2025-present), Online Control with Adversarial Noise (2022-present), and RL for Partially Observable Systems (2021-present). She explores how foundation models can enable control systems to generalize across diverse tasks and adapt to unseen scenarios, with applications in robotics and autonomous systems. Her work integrates large language models and generative AI into control frameworks, addressing fundamental challenges in sequential decision-making under uncertainty. Scientific Recognition: Best Thesis Award at Nanyang Technological University (2017) CENIIT research grant (2020) Co-founded SEDDIT competence centre (2024) As an educator, she teaches Ph.D.-level courses including Reinforcement Learning (2021-2024) and Advanced Robotics (2025), with her WASP course ranking as the second-best Ph.D. course in the program (3.9/5 evaluation). She actively mentors Ph.D. students including Abbas Pasdar, who is working on Foundation Models for General-Purpose Control. Her research is supported by grants including CENIIT and collaborations through the SEDDIT competence centre. She contributes to the academic community through workshops like the LINK-SIC Core Competence Workshops on Reinforcement Learning and by chairing sessions at major conferences including ECC 2025.

• Cybersecurity
• Formal Verification
• Cyber-Physical Systems
• +۷ مورد دیگر

Marjan Sirjani is a Professor at Mälardalen University, affiliated with the School of Innovation, Design and Engineering, and the Division of Computer Science and Software Engineering. Her research focuses on cybersecurity, formal verification, and cyber-physical systems, with notable contributions to actor-based modeling (e.g., Timed Rebeca) and tools like AFRA for model analysis. She specializes in integrating formal methods into safety-critical systems, including automotive cybersecurity, ROS2 robotics, and blockchain-based IoT systems. Her work emphasizes rigorous analysis of protocols, concurrency, and real-time constraints. Recent projects include the CRYSTAL framework for CPS assurance, Tiny Twins for runtime attack detection, and applying LLMs for automated test generation. She also explores semantic segmentation in construction and compositional analysis of distributed systems. Publications highlight advancements in protocol learning, controller synthesis for safety, and model-driven development. Her research bridges theoretical foundations (e.g., automata theory, temporal logics) with practical applications in autonomous systems, medical device interoperability, and smart mobility. Labs/Teams: Involved in the Rebeca tool development (AFRA) and collaborative projects on CPS security. Grants: Not explicitly listed but implied through project involvement.

Alireza Mohammadinodooshanمشاهده پروفایل

پژوهشگر ارشد

• Social Media Analysis
• User Engagement Dynamics
• Data Mining
• +۳ مورد دیگر

Alireza Mohammadinodooshan is a Postdoctoral Fellow at Linköping University's Department of Computer Science (IDA), Sweden, working within the Database and Information Technology (ADIT) research group. He contributes to the Wallenberg AI, Autonomous Systems and Software Program (WASP) – Sweden's largest individual research initiative – focusing on data-driven analysis of social media engagement dynamics across Twitter, Facebook, and Instagram platforms. His research centers on quantifying how political bias, news reliability, and content-agnostic factors shape temporal user engagement patterns. Key interests include social media analysis, user engagement dynamics, data mining, information systems, network science, and artificial intelligence, with emphasis on cross-platform comparative studies and algorithmic amplification effects in news consumption. Analysis of his 15 most recent publications reveals consistent focus on temporal modeling of engagement decay, multi-format content interaction (photos/videos/albums), and the interplay between news source characteristics and user behavior. His methodological approach combines large-scale dataset analysis with network theory to identify virality predictors and platform-specific engagement mechanics. No scientific awards were documented in available sources. No advising roles or research grants were referenced in the provided materials. He operates within the ADIT research group at Linköping University, which specializes in advanced database and information systems for the digital society. This group forms part of IDA's broader WASP-affiliated ecosystem focused on AI-driven autonomous systems, enabling interdisciplinary collaboration on large-scale data challenges in social computing.

• Randomized algorithms
• Machine learning
• Big Data
• +۳ مورد دیگر

Devdatt Dubhashi is a Professor at the Data Science and AI 3 department at Chalmers University of Technology. His research spans multiple domains within computer science and data science, with a focus on theoretical foundations and practical applications of algorithms and machine learning. Professor Dubhashi's primary research interests include the design and analysis of randomized algorithms, machine learning for Big Data, and computational biology. His work demonstrates a strong interdisciplinary approach, connecting theoretical computer science with practical applications in diverse fields such as quantum computing, transportation modeling, genomics, and social sciences. His research often bridges the gap between theoretical foundations and real-world implementations, as evidenced by his numerous collaborations across different domains. Dubhashi's recent publications reveal a consistent research trajectory focusing on algorithmic foundations of machine learning, with increasing emphasis on interdisciplinary applications. His work shows significant contributions to bandit algorithms, kernel methods, graph-based learning, and the theoretical understanding of deep learning models. There's also a growing focus on societal implications of AI, as seen in his publications addressing responsible AI development and policy considerations. Among his notable scientific contributions are publications in prestigious venues including ACM, IEEE, and Nature journals, covering topics from fundamental algorithm design to applications in computational biology and social sciences. His work has been cited extensively across multiple disciplines, reflecting its broad impact. Professor Dubhashi actively supervises PhD students and collaborates with researchers across Chalmers and internationally. His research group appears to focus on the intersection of theoretical computer science and practical machine learning applications, with projects spanning quantum computing, transportation modeling, and biological applications.

Diego Calvaneseمشاهده پروفایل

استاد مهمان

• Artificial Intelligence for Data Management
• Knowledge Representation and Reasoning
• Virtual Knowledge Graphs
• +۵ مورد دیگر

Diego Calvanese is a Visiting Professor at Umeå University's Department of Computing Science and holds a full professorship at the Free University of Bozen-Bolzano, Italy. His research focuses on AI for data management, including virtual knowledge graphs (VKG), ontology-based data access (OBDA), and formal methods like description logics. He is part-time at Umeå, balancing roles with his primary position in Italy. Calvanese has received prestigious awards including the AAAI Classic Paper Award (2021), EurAI Fellow (2015), and ACM Fellow (2019). He supervises three doctoral students at Umeå and has authored over 350 publications, with an h-index of 71. His work emphasizes data integration, geospatial systems, and ethical AI applications. Key Roles: Associate Programme Chair (IJCAI 2025), Programme Chair (IJCAI-ECAI 2026), Head of AI for Data Management Research Group Research Interests: Knowledge representation, graph data management, explainable AI, and telemonitoring systems like reCOVeryaID. His research group develops tools like Ontop, a VKG system enabling seamless data access across heterogeneous sources. Current projects include geospatial data integration and temporal OBDA frameworks. Calvanese has served on over 150 program committees and editorial boards, including Artificial Intelligence and JAIR. His work bridges technical advancements with societal impacts, addressing AI's role in healthcare, climate, and democracy.

Simin Nadjm-Tehraniمشاهده پروفایل

استاد

• Cybersecurity
• Real-Time Systems
• Formal Verification
• +۴ مورد دیگر

Simin Nadjm-Tehrani is a Professor and Head of Unit at Linköping University's Department of Computer and Information Science (IDA), leading the Real-time Systems Laboratory (RTSLAB) since 2000. She holds a PhD in Computer Science from Linköping University (1994) and previously served as a full professor at the University of Luxembourg (2006–2008). Her research focuses on cybersecurity, dependability in distributed systems, and formal methods for safety-critical applications. Key research areas include adaptive anomaly detection in critical infrastructures, energy-efficient protocols, and formal analysis of safety protocols. She leads the NEST-project on AI for cyber attack identification and contributes to the Wallenberg AI, Autonomous Systems and Software Program (WASP). Her work addresses challenges in smart grids, edge computing, and secure communication protocols. Publications emphasize practical applications of formal verification in tree ensembles, SCADA systems, and avionics. She organized the 2019 CRITIS conference and collaborates with industry on edge computing benchmarks and secure IoT architectures. Her educational contributions include curriculum design for problem-based learning (PBL) and gender equity initiatives in computer science. Professional roles include leadership in the Software and Systems (SAS) division at IDA, where she oversees interdisciplinary projects combining safety and security constraints. Current efforts target resilient information systems for societal functions like energy and transportation.

Jutta Haiderمشاهده پروفایل

استاد

• Information Practices
• Digital Cultures
• Environmental Communication
• +۵ مورد دیگر

Jutta Haider is a Professor at the Department of Library and Information Science , University of Borås, specializing in understanding information practices within digital cultures. Her work bridges the production, use, and distribution of knowledge with a focus on environmental communication, media and information literacy, and knowledge institutions like search engines and scholarly communication systems. Currently affiliated with the Mistra Environmental Communication research program Leads the research group Information Practices and Digital Cultures at University of Borås Supervises doctoral students in collaboration with Umeå University and University of Oulu Her research explores the paradoxes of media and information literacy, algorithmic recommendations, and their societal impacts, particularly in climate and environmental contexts. She has received multiple awards for her work in source criticism and humanistic research. Recent publications highlight algorithmic emissions, climate denialism, and infrastructural meaning-making in digital societies. She actively investigates how platforms shape knowledge production and environmental awareness. Scientific Awards Source Criticism Award (2023) Inga and John Hain Scholarship for Humanistic Research (2019) Einar Hansen Endowment for Distinguished Humanistic Research (2016) Haider supervises doctoral students Emma Roman and Fereshta Westin at University of Borås, and external students Zakayo Kjellström and Ville Jylhä.

• Blockchain Technology
• Smart Contract Security
• Renewable Energy Systems
• +۳ مورد دیگر

Sundas Munir is a Lecturer at the School of Information Technology, Halmstad University. Her research focuses on blockchain technology, smart contract security, and renewable energy systems. University: Halmstad University School: School of Information Technology Rank: Lecturer Email: sundas.munir@hh.se Her recent publications highlight expertise in: Static analysis of smart contracts Transaction ordering dependencies in Ethereum Blockchain-based energy marketplaces Security validation frameworks Formal verification techniques Her work bridges theoretical research with practical applications in decentralized systems and cybersecurity. She is active in publishing conference papers and technical surveys related to blockchain integrity and energy innovation.

• Formal Verification
• Model Checking
• Concurrent Systems
• +۶ مورد دیگر

Parosh Abdulla is a Professor in the Division of Computer Systems within the Department of Information Technology at Uppsala University, Sweden. His research focuses on formal methods and program verification with emphasis on concurrent systems, memory models, and verification techniques. With an extensive publication record spanning over three decades, he has established himself as a leading researcher in his field. His primary research interests include formal verification, model checking, concurrent systems analysis, memory models (particularly TSO and PSO), string constraints, timed automata, parameterized verification, and program analysis. His work addresses fundamental challenges in verifying complex software systems, especially those involving concurrency and weak memory models. In recent years, he has expanded his research to include quantum systems verification and the application of machine learning techniques to formal methods. Analysis of his recent publications (2023-2025) reveals a continued focus on advancing verification techniques for concurrent systems, with growing interest in quantum computing verification and the integration of graph neural networks with traditional formal methods. His work demonstrates consistent innovation in reducing the state space explosion problem while maintaining verification completeness. Professor Abdulla has established significant collaborations with researchers including Mohamed Faouzi Atig, Bengt Jonsson, and others, resulting in numerous high-impact publications in top-tier venues. His research has practical implications for developing reliable concurrent software systems and advancing formal verification methodologies. While specific details about his advising activities and grants aren't explicitly mentioned in the available information, his extensive publication record suggests active supervision of graduate students and involvement in multiple research projects. His work likely contributes to formal methods research groups at Uppsala University, focusing on verification tools and theoretical foundations of program analysis.

Sarbojit Dasمشاهده پروفایل

پژوهشگر

• Computer Science
• Software Verification
• Concurrency
• +۳ مورد دیگر

Sarbojit Das is a Researcher at the Department of Information Technology; Division of Computer Systems , Uppsala University . His work focuses on improving verification techniques for concurrent systems, particularly in stateless model checking and dynamic partial order reduction. Email: sarbojit.das@it.uu.se Location: Uppsala, Sweden Research Interests: Prioritizing rigorous analysis of concurrent and multi-threaded systems, Sarbojit Das investigates methods to reduce computational complexity in software verification. His work bridges theoretical computer science with practical applications in formal methods and algorithm optimization. Publication Trends: Recent publications emphasize advancements in stateless model checking, dynamic partial order reduction, and event-driven architectures. Topics include thread scheduling, memory optimization, and scalable verification for distributed systems.