جست‌وجوی استاد و پژوهشگر

Gerardo Schneiderمشاهده پروفایل

استاد

• Formal Specification and Analysis of Contracts
• Formalization of Privacy Policies
• Model Checking
• +۵ مورد دیگر

Gerardo Schneider is a Full Professor in Computer Science at the University of Gothenburg, Sweden, and holds a joint appointment at Chalmers University of Technology. He serves as Head of the Data Science and Artificial Intelligence (DSAI) Division and has previously led the Formal Methods Division and acted as Director of Graduate Studies. University of Gothenburg: 2009–present Chalmers University of Technology: 2009–present Uppsala University: 2002–2003 University of Oslo: 2005–2009 His research focuses on formal methods for software engineering, including contract specification and analysis , privacy policy formalization , model checking , and runtime verification . He works on verification of real-time systems, embedded systems (e.g., smart Java cards), and blockchain-based smart contracts. Key projects include: X-LEGAL (2020–2023): Smart Legal Contracts (Swedish Research Council) PolUser (2016–2019): User-Controlled Privacy Policies (Swedish Research Council) ARVI (2014–2018): Runtime Verification Beyond Monitoring (ICT COST Action) ReMU (2013–2017): Reliable Multilingual Digital Communication (Swedish Research Council) He has supervised numerous PhD and Master’s students in formal methods, blockchain security, and privacy compliance. His tools include SPeeDI (Polygonal Hybrid Systems Verification), CLAN (Contract Normative Conflict Detection), and AnaCon (Controlled Natural Language Analysis).

Tran Duc Muoiمشاهده پروفایل

استادیار

• Network Security
• Blockchain Security
• Internet Routing
• +۲ مورد دیگر

Muoi Tran is an Assistant Professor at Chalmers University of Technology and leads the Secura Lab , affiliated with the Department of Computer Science and Engineering. His research focuses on network security , blockchain security , and Internet routing , particularly addressing vulnerabilities in cryptocurrency systems and distributed networks. He earned a Ph.D. in Computer Science from the National University of Singapore (2022), supervised by Zhenkai Liang and Min Suk Kang, and completed a postdoc at ETH Zurich under Laurent Vanbever. His work spans novel attacks on network infrastructure, blockchain peer-to-peer networks, and countermeasures for secure Internet routing. Recent publications highlight his expertise in Automated analysis of proxy smart contracts (ICDCS '25) Differential fuzzing for blockchain consensus (ICSE '25) Privacy attacks in the Lightning Network (IEEE SP '24) Partitioning attacks on Bitcoin (EuroS&P '23) His research has been recognized by grants such as the WASP Academic Doctoral Student Projects funding . Secura Lab collaborates with institutions like ETH Zurich and NTU (Taiwan), focusing on network security for AI systems, proxy contract vulnerabilities, and distributed resilience. Muoi actively mentors and recruits students for projects at the intersection of AI and network security.

• Software Security
• IoT Security
• Software Supply Chains
• +۲ مورد دیگر

Mojtaba Moazen is a PhD student and researcher at the Division of Theoretical Computer Science , part of KTH Royal Institute of Technology in Sweden. He is actively involved in the WASP – Wallenberg AI, Autonomous Systems and Software Program and the NEST CyberSecIT project, focusing on securing IoT applications and software supply chains. His work bridges academic research with critical real-world cybersecurity challenges. Education: PhD (ongoing) in Theoretical Computer Science, KTH Royal Institute of Technology Master of Science in Information Technology, Sharif University of Technology Bachelor of Science in Computer Engineering, K. N. Toosi University of Technology Research Interests: Mojtaba specializes in software security , IoT security , and software supply chains , with a focus on developing robust security mechanisms for emerging technologies. His recent publications highlight advancements in Android malware detection and continuous integration testing. Courses Assisted: Applied Cryptography (DD2520) Computer Security (DD2395) Internet Programming (DD1386) Language-Based Security (DD2525) Programming Techniques (DD1310)

• Architecture
• Digital Fabrication
• Sustainable Design
• +۵ مورد دیگر

Malgorzata Zboinska is an Associate Professor at Chalmers University of Technology within the Department of Architecture and Civil Engineering . She is a licensed architect and member of the Swedish Association of Architects and National Chamber of Architects of Poland . Hybrid architecture-technology-art research Focus on bio-based materials , digital fabrication , and creative robotics Development Leader of Chalmers' Robotic Fabrication Laboratory Editorial board member of TAD | Technology, Architecture + Design journal Research Themes bridge architecture , digital technology , and art , with expertise in: Sustainable and circular architectural practices 3D printing and robotic construction Material bioinnovation and upcycling Interactive and kinetic architectural solutions Her publications demonstrate strong output in digital fabrication , bio-material applications , and environmental architecture , with international exhibitions at Tempe Center for the Arts (USA) , Dutch Design Week (NL) , and Färgfabriken (Sweden) .

• Program Verification
• Proof Engineering
• Formal Methods
• +۴ مورد دیگر

Karl Palmskog is a Lecturer at KTH Royal Institute of Technology in the Division of Theoretical Computer Science and the STEP research group. His work focuses on program verification and proof engineering, with particular emphasis on developing techniques and tools based on proof assistants for constructing functionally correct and secure software systems. Palmskog received his Ph.D. in Computer Science in 2014 from KTH, advised by Mads Dam, and his M.Sc. in Computer Science and Engineering from KTH in 2007. Prior to his current position, he was a postdoc at The University of Texas at Austin and University of Illinois at Urbana-Champaign. His research interests span programming languages, software engineering, and formal verification, with a particular focus on developing techniques and tools based on proof assistants. He is an avid user of the Coq proof assistant for both proving and programming, often complemented by OCaml, and also utilizes HOL4 and other ML family dialects. His work bridges theoretical foundations with practical applications, particularly in the domains of blockchain systems, distributed systems, and automotive software verification. Analysis of his recent publications reveals a strong focus on Coq-based verification, with significant contributions to proof engineering tools and methodologies. His work includes developing tools for regression proving, change impact analysis, mutation testing for Coq projects, and lemma name suggestion using deep learning. There's also a growing trend toward applying formal methods to real-world systems like blockchain protocols and automotive software. Palmskog has been involved in several research projects, including Coq-community Proof Engineering and Distributed Components. His past projects include Trustfull (SSF), Model-based Event Driven Scalable Programming for the Mobile Cloud (NSF), Highly Adaptable and Trustworthy Software (EU FP7), and 4WARD Future Internet (EU FP7). As an educator, Palmskog has served as examiner, course responsible, teacher, and assistant for various courses including Algorithms, Data Structures and Complexity; Degree Projects; Game Theory; Parallel and Distributed Computing; and Programming Paradigms. His work on Chip, a Coq formalization of change impact analysis, demonstrates his commitment to creating practical, certified tools that bridge formal methods with software engineering practice.

• Renewable Energy
• Fluid-Structure Interaction (FSI)
• Aeroacoustics
• +۵ مورد دیگر

Huadong Yao is an Assistant Professor at the Department of Marine Engineering, Chalmers University of Technology. His research spans renewable energy , fluid-structure interaction (FSI) , and transportation systems , with a focus on offshore wind farms, wave energy, and aero/hydroacoustics. Multi-University Collaboration : Guest professorships at international institutions Leadership Roles : Coordinator of Horizon 2020 projects (e.g., IVANHOE) and guest editor for journals Key Organizations : Member of AIAA, SAE International, RINA, ICNMT, and ICES Working Group on Offshore Renewable Energy His research integrates CFD and FSI coding (OpenFOAM, in-house codes) with turbulence modeling (LES, SNGR) to address problems in marine hydrodynamics (e.g., rim-driven thrusters, wind-powered ship propulsion) and terrestrial transportation (high-speed train aerodynamics, urban air mobility). Recent work explores biomechanics (whiplash injury hydrodynamics) and battery cooling systems for electric vehicles. Current projects focus on: Optimization of wave energy converter farms (hexagon layouts, mooring fatigue) Hubless rim-driven thruster design (gap geometry, concave cavities) Hydrographic impacts of offshore wind turbines on marine environments Urban air mobility (UAM) aerodynamics Multidisciplinary Design Optimization (MDO) using machine learning He collaborates with institutions like AIAA, SAE, and ICES, and has received funding from Horizon 2020 and Swedish national agencies.

Pontus Ekbergمشاهده پروفایل

دانشیار

• Algorithms
• Real-Time Scheduling Theory
• Computational Complexity
• +۳ مورد دیگر

Pontus Ekberg is an Associate Professor at Uppsala University's Department of Information Technology. His email address is pontus.ekberg@it.uu.se , and he can be reached at +46 18 471 73 41. He is affiliated with the Division of Computer Systems and holds the academic merit 'Docent' in real-time scheduling theory. Ekberg's research focuses on algorithms and computational problems in real-time scheduling theory. His work addresses NP-hardness in scheduling, fixed-priority algorithms, and formal verification of task feasibility. Current projects include applying pseudo-polynomial time analysis, combating butterfly attacks, and integrating deep learning for schedulability verification in safety-critical systems. His recent publications span topics like pseudo-polynomial time analysis (2025), optimistic period predictions (2024), and explainability in real-time schedulability (2023). He collaborates frequently with Sanjoy Baruah and others on uniprocessor and multiprocessor scheduling models. Although no formal awards are listed, his contributions to real-time scheduling theory are evident through 15+ publications in top conferences like RTSS and ECRTS.

Alejandro Russoمشاهده پروفایل

استاد

• Computer Science
• Information Security
• Functional Programming
• +۳ مورد دیگر

Alejandro Russo is a Professor at Chalmers University of Technology , specializing in Information Flow Control (IFC) , Secure Programming Languages , and Functional Programming . His research bridges theoretical foundations and practical implementations, focusing on mitigating timing channels , covert channels , and data leakage in concurrent systems. Developed novel frameworks for Differential Privacy with provable accuracy bounds Pioneered COWL integration for browser security and instruction-based scheduling to prevent cache timing attacks Led major projects like HIPSTER (hybrid static/dynamic IFC) and AppFlow (practical IFC deployment) His publications reveal expertise in security libraries for Haskell and Python , with a focus on faceted execution , label manipulation , and mechanized security proofs . Students under his supervision have explored topics ranging from secure eDSLs to privacy-preserving compilation techniques . Scientific awards : Google Research Award (2011) for Python taint analysis Advising and grants : Principal Investigator for VR , STINT , and Google Research Award Supervised 12+ PhD and Master’s students in security and functional programming research

• Chemical Risk Assessment
• Science-Policy Interface
• Environmental Toxicology
• +۴ مورد دیگر

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.

Marc Hellmuthمشاهده پروفایل

دانشیار

• Discrete Mathematics
• Combinatorics
• Graph Theory
• +۱۰ مورد دیگر

Marc Hellmuth is an Associate Professor of Computational Mathematics at the Department of Mathematics, Stockholm University, Sweden. His academic career includes previous positions as Junior Professor for Biomathematics and Computer Science at University of Greifswald, Germany (2015-2020), Lecturer at School of Computing, University of Leeds, UK (2020), and PostDoc positions at Saarland University and Max-Planck Institutes. Dr. Hellmuth earned his PhD in Computer Science from University of Leipzig, Germany (2007-2010, summa cum laude), supervised by Peter F. Stadler, and completed his Venia Legendi (habilitation) at Saarland University, Germany (2016). His research spans the interface of discrete mathematics, computer science, and life sciences with emphasis on: Discrete Mathematics including Graph Theory, Combinatorics, and Optimization Algorithm Design and Complexity Theory Mathematical and Computational Biology Phylogenomics and Evolutionary Analysis Computational Chemistry and Atom Tracking His publication record demonstrates a consistent focus on developing mathematical frameworks and efficient algorithms for biological problems, particularly in phylogenomics, orthology detection, and evolutionary analysis. His work bridges theoretical computer science with practical applications in biology and chemistry, often resulting in open-source software tools. Dr. Hellmuth has developed numerous software tools including AsymmeTree for phylogenetic simulation, tralda for tree algorithms, and specialized tools for phylogenomics, atom tracking, and graph analysis. His collaborative work extends internationally with research visits to institutions including Yale University, University of Leoben, Vienna University of Economics, University of Southern Denmark, Université de Montréal, and institutions in China.

• Ergonomics
• Musculoskeletal Disorders Prevention
• Biomechanical Exposure Measurement
• +۷ مورد دیگر

Mikael Forsman serves as Professor and Head of the Division of Ergonomics at KTH Royal Institute of Technology's School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH). With a PhD in Medical Electronics from Chalmers University (1995), he has specialized in ergonomics research since 1994, developing both advanced research methods and practical tools for practitioners. His work spans laboratory experiments, field studies, and participative interventions at individual and organizational levels. M.Sc. (E. Eng.) from Chalmers University of Technology, Göteborg (1987) Ph.D. in Medical Electronics from Chalmers University of Technology (1995) Docent of Ergonomics, Department of Human Factors Engineering (1999) Forsman's research centers on reliable measurement methods for ergonomic risk assessment and prevention of musculoskeletal disorders. Key areas include: Development of inexpensive, user-friendly systems using microelectronics for biomechanical exposure measurement Field studies of physical and psychosocial exposures across various occupations Creation of questionnaires and investigation of correlations between work ability, musculoskeletal pain, and workload Work accident prevention and analysis Participative ergonomic interventions at multiple organizational levels Analysis of his recent publications (2023-2025) reveals three dominant research trends: (1) Development and validation of wearable sensor technologies for real-time ergonomic assessment; (2) Application of ergonomic principles in specialized fields like surgery, construction, and waste management; (3) Integration of human factors with digital technologies such as BIM. His work consistently bridges theoretical biomechanics with practical workplace solutions, emphasizing accessible methods for practitioners. Forsman has supervised approximately 20 master's theses and served as main supervisor for 3 doctoral theses with 8 additional co-supervised theses. Currently, he supervises 3 PhD students as main supervisor and 4 others as co-supervisor. He has led approximately 12 research projects and participated as co-applicant in about 20 projects funded by research councils. His educational contributions include responsibility for numerous master's level courses in ergonomics and work environment. As leader of KTH's Division of Ergonomics, Forsman directs research on biomechanical exposure measurement and practical ergonomic interventions. He actively promotes Nordic collaboration in ergonomics research, noting similarities in work life and research traditions across the region. Current projects include the Smart Workwear Consortium developing systems with real-time vibrotactile feedback for reducing postural exposure in industrial settings, and research on leadership aspects associated with digital technology adoption in construction.

• High-Dimensional Statistics
• Portfolio Optimization
• Bayesian Analysis
• +۳ مورد دیگر

Taras Bodnar is a Professor at the Department of Management and Engineering, Linköping University. His research focuses on high-dimensional statistical methodologies with applications in finance, portfolio optimization, and econometrics. He specializes in developing and analyzing advanced statistical models for asset allocation, risk management, and multivariate meta-analysis. Bodnar's work often involves Bayesian methods, shrinkage estimation techniques, and copula modeling to address challenges in financial data analysis. His recent contributions include the HDShOP package for portfolio selection and advancements in nonlinear shrinkage tests for large-dimensional covariance matrices. His research bridges theoretical statistics with practical financial applications, addressing issues such as dark uncertainty and efficient frontier estimation in high-dimensional settings. Key research interests include: High-Dimensional Portfolio Optimization Bayesian Analysis in Financial Contexts Covariance Matrix Estimation and Testing Uncertainty Quantification in Multivariate Analyses Statistical Software Development for Finance Recent publications (2024-2025) emphasize methodological innovations in portfolio selection, copula modeling, and robust statistical inference. His work has implications for both academic theory and practical investment strategies, particularly in managing large and complex financial datasets.

Luis Velez Quinteroمشاهده پروفایل

استادیار

• Data Science
• Extended Reality (XR)
• Machine Learning
• +۴ مورد دیگر

Luis Velez Quintero is an Assistant Professor at Stockholm University within the Department of Computer and Systems Sciences (DSV) . He is affiliated with the Data Science Research Group and the Stockholm Technology & Interaction Research (STIR) group, focusing on Human–Computer Interaction. His research spans adaptive immersive systems, affective computing, and physiological signal analysis in extended reality (XR) environments. Education & Background : Holds a PhD in Computer and Systems Sciences from Stockholm University (2023), MSc in Health Informatics from Karolinska Institutet (2019), and BSc in Electronics Engineering from the National University of Colombia (2015). He has led the startup PortalSense since 2018, developing VR solutions for real estate visualization. Research Interests : Combines data science and ML with XR technologies to create context-aware systems for healthcare, education, and professional training. Key themes include: Adaptive VR/AR systems using real-time physiological and behavioral signals Biosignal integration for personalized user experiences Immersive technologies for cognitive assessment and skill development Publications : Over 20 peer-reviewed articles, including work on affective databases (AVDOS-VR), biosignal frameworks (Excite-O-Meter), and XR applications in cybersecurity education. Recent efforts explore third-person locomotion in VR and early-stage Alzheimer’s detection via spatial navigation tasks. Awards & Grants : Wallenberg Foundation Grant (2023-2025): Analyzing non-verbal communication in psychotherapy Swedish Institute Scholarship (2017-2019): Fully funded Master’s and PhD studies Seed funding for PortalSense from Fondo Emprender SENA Colombia (2022-2023) Advising & Projects : Lead researcher in projects like AVDOS-VR and CS:NO . Co-designed the Excite-O-Meter open-source plugin for real-time physiological analysis in VR. Active in industry collaborations for scalable health interventions and immersive training systems. Labs & Teams : Collaborates with multidisciplinary teams at STIR and DSV, advancing human-centered AI and adaptive XR technologies.

Saad Mubeenمشاهده پروفایل

استاد

• Embedded Systems
• Real-Time Communication
• Predictable Software Development
• +۵ مورد دیگر

Saad Mubeen is a Full Professor of Computer Science at Mälardalen University, Sweden, affiliated with the School of Innovation, Design and Engineering and the Division of Networked and Embedded Systems. He holds a Master's in Electrical Engineering (Embedded Systems) and a PhD in Computer Science and Engineering from Mälardalen University (2014), with a Docent title (2018) focused on vehicular embedded systems. His research emphasizes predictable embedded systems, timing analysis for real-time communication, and component-based software design. Key areas include model-driven development for automotive systems, integration of TSN/5G networks, and fault-tolerant industrial architectures. He has led projects on end-to-end timing analysis in distributed systems, ROS 2 verification, and cognitive edge-cloud scheduling. Publications span 2021–2025, focusing on real-time systems, network protocols (TSN, AVB, 5G), and industrial automation. Notable work includes frameworks for TSN configuration, fault diagnosis tools using NETCONF, and scheduling algorithms for heterogeneous edge-cloud environments. His contributions address critical challenges in timing predictability, security, and resource optimization for cyber-physical systems. Education contributions include problem-based learning modules for vehicular software engineering. He is actively involved in bridging academia and industry through collaborative research on next-generation automotive and industrial systems.

Bestoun S. Ahmed Al-Beywaneeمشاهده پروفایل

استاد

• Quality Assurance of Machine Learning Systems
• Software Testing
• Trustworthy AI Systems
• +۵ مورد دیگر

Bestoun S. Ahmed Al-Beywanee is a Professor in AI and Software Engineering at the Department of Mathematics and Computer Science, Karlstad University, Sweden. He joined the university as a Senior Lecturer in 2019, was promoted to Associate Professor in 2020, and to Professor in 2023. His roles include teaching advanced courses such as AI Engineering, Automated Software Engineering, and Software Testing Fundamentals. His research focuses on software quality assurance, trustworthy AI systems, and MLOps, with a strong emphasis on combinatorial testing, IoT systems, and applied optimization techniques. Education: BSc (Electrical and Electronic Engineering, University of Salahaddin-Erbil, 2004); MSc (University Putra Malaysia, 2009); PhD (Software Engineering, University Sains Malaysia, 2012). Postdoctoral research at the Swiss AI Lab IDSIA (2015) and positions at Salahaddin University and Czech Technical University further enriched his expertise. Research interests span Quality Assurance of machine learning systems, software testing methodologies, trustworthy AI, IoT system reliability, and optimization algorithms. He has pioneered frameworks like PatrIoT for IoT testing and contributed to MLOps robustness. His work integrates machine learning with anomaly detection, adaptive systems, and industrial applications. Recent articles highlight advancements in data-driven heat pump management, MLOps robustness, and edge-cloud AR/VR optimization. Collaborations include projects on digital twins, smart manufacturing, and industrial IoT. His contributions bridge theoretical research with practical industrial solutions, emphasizing system reliability and AI ethics.