جست‌وجوی استاد و پژوهشگر

• Industrial Engineering
• Operations Research
• Production Planning
• +۳ مورد دیگر

Pedram Beldar is a researcher affiliated with the University of Skövde , specifically the School of Engineering Science and Department of Engineering . He actively contributes to the fields of Industrial Engineering , Operations Research , and Production Optimization . His research focuses on optimization algorithms for manufacturing processes, including batch processing , flexible transfer lines , and energy-efficient production . He has collaborated on projects like Digitalized and optimized production planning for energy-efficient production (May 2022 - April 2025) and Virtual Engineering . His work emphasizes sustainable manufacturing and smart Industry 4.0 solutions. The trends in his publications highlight applications of operations research to non-identical parallel machines , cross-docking systems , and teaching-learning-based optimization , with a growing emphasis on sustainable production in recent years. He is involved in course coordination for bachelor-level industrial engineering courses and collaborates with researchers such as Masood Fathi , Amir Nourmohammadi , and Gilbert Laporte .

• Control Engineering
• Process Control
• Optimal Control
• +۱۱ مورد دیگر

Torsten Wik is a Professor in Control Engineering at Chalmers University of Technology. He leads the Control Engineering research group and focuses on process control with theoretical and applied methodologies. Institution: Chalmers University of Technology Department: Control Engineering His research spans optimal control, model reduction, and systems with model uncertainties. Applications include energy-saving systems, environmental improvement, biological systems (water purification, recirculating fish farms, LED greenhouse lighting), and battery estimation/modeling/control. Recent work emphasizes battery degradation diagnosis, state estimation, fast charging, and reconfigurable systems. Key methodologies include physics-informed frameworks, machine learning integration, entropy-based predictive algorithms, and hypergraph modeling. Applications extend to electric vehicles, photovoltaic systems, fuel cells, and biofilm reactors. Publications highlight collaborations across engineering domains, focusing on control theory, electrochemical modeling, and real-time optimization. His work bridges theoretical advancements with industrial applications in energy systems, transportation, and sustainable agriculture.

• Early Childhood Education
• Social Interaction in Preschool
• Ethnicity Studies
• +۱ مورد دیگر

Linda Häll is a Lecturer at Linköping University, affiliated with both the Department of Behavioral Sciences and Learning (IBL) and the Department of Learning, Aesthetics and Natural Sciences (LEN). Her research focuses on how preschool children construct and negotiate age as a social resource through interaction. Current research: "Doing Age" in educational contexts Methodology: Long-term ethnographic fieldwork Secondary interest: Ethnicity and multiculturalism in early childhood settings Her work builds on symbolic interactionism and ethnomethodology, drawing parallels to "doing gender" theory. Key themes include: Interactive age categorization Superdiversity management in childcare Temporal identity construction Communicative diversity in play Publications span from 2013 to 2025, with recent work examining superdiversity in Swedish school-age educare (2025) and age categorization patterns in preschool (2022). Her research emphasizes practical applications for inclusive educational practices and contributes to understanding how children navigate complex social hierarchies.

Christoph Kesslerمشاهده پروفایل

استاد

• Parallel Programming
• Compiler Technology
• Optimization Algorithms
• +۳ مورد دیگر

Christoph Kessler is a Professor and Head of the Software and Systems (SAS) division at the Department of Computer and Information Science (IDA), Linköping University, Sweden. He leads the Programming Environment Laboratory’s research group focusing on compiler technology, parallel computing, and heterogeneous systems. His work includes the development of tools like OPTIMIST, PARAMAT, and SkePU, and he has contributed over 100 publications in journals and conferences. He holds a PhD from the University of Saarbrücken and a Habilitation from the University of Trier. Research interests span parallel programming, compiler optimization, and energy-efficient scheduling for heterogeneous systems. He has secured a 30M SEK grant from SSF for the ASTECC project, advancing adaptive software for edge-cloud computing. Notable contributions include frameworks for GPU-based systems and methodologies for optimizing resource allocation on many-core architectures. His team’s work emphasizes practical applications in high-performance computing, including tools for course management (StASy) and energy-aware scheduling algorithms. The SAS division, under his leadership, focuses on software engineering and computer systems research with strong industry collaboration.

Mathias Haageمشاهده پروفایل

مدرس ارشد

• Robotics
• Automation
• Construction
• +۳ مورد دیگر

Mathias Haage is a Senior Lecturer and Project Manager at the Department of Computer Science, Lund University, affiliated with the Faculty of Engineering (LTH). He is a member of LTH's Profile Areas in 'Circular Building Sector' and 'AI and Digitalization,' and part of ELLIIT: the Linköping-Lund initiative on IT and mobile communication. His research focuses on Robotics and Automation, particularly in construction and industrial applications. He leads projects like the 'Center for Construction Robotics' and 'RobotLab LTH,' emphasizing automation in construction processes and smart manufacturing. Key research topics include parallel-kinematic manipulators, industrial robot applications, and ontology-based knowledge representation for robotics. He has contributed to advancements in construction automation, flexible manufacturing systems, and robot skill reusability. His work aligns with UN Sustainable Development Goals related to industry, innovation, and infrastructure. Haage has supervised over 33 research outputs, including peer-reviewed conference papers and journal articles. Notable collaborations include projects with Heidelberg Materials Cement Sverige AB and FORMAS. He actively participates in initiatives like the Robotics Week for Schools and AI Lund seminars, promoting public engagement in robotics and AI.

Måns Magnussonمشاهده پروفایل

دانشیار

• Bayesian Statistics
• Probabilistic Machine Learning
• Statistical Inference from Textual Data
• +۴ مورد دیگر

Måns Magnusson is an Associate Professor at the Department of Statistics, Uppsala University, with affiliations at the Institute for Analytical Sociology (Linköping University) and the Institute for Future Studies. His work bridges Bayesian statistics, probabilistic machine learning, and textual analysis, focusing on model evaluation, diagnostics, and inference algorithms. He contributes to computational social science and digital humanities through text-as-data methods. Research Themes: Bayesian inference, probabilistic machine learning, statistical inference from textual data Key Applications: Sociology, political science, law, education statistics, public health Current Projects: Improving probabilistic programming generalizability (Swedish Research Council grant), SWERIK research infrastructure (Riksbankens jubileumsfond) His recent publications emphasize text mining, model comparison, and legal data challenges. He has developed tools for national ID number validation, hate crime estimation, and parliamentary corpus construction. Notable awards include the Cramér Prize (2018), Statistician of the Year (2023), and membership in the Swedish Young Academy (2023) and ELLIS (2024). Scientific Contributions: Botten Ada Bayesian election model, 'loo' package for cross-validation Collaborative Work: AI4Research sabbatical (2024), Riksbankens jubileumsfond funding Industry Background: Statistician roles at Swedish Agency for Education, Crime Prevention, and Public Health

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.

Yuan Yaoمشاهده پروفایل

استادیار

• Computer Architecture
• Parallel Computing
• Power and Thermal Management
• +۷ مورد دیگر

Yuan Yao serves as an Assistant Professor in the Department of Information Technology at Uppsala University, Sweden. His academic role spans teaching and research within the Computer Systems division, focusing on cutting-edge computer architecture and parallel computing systems. He maintains active collaborations across international institutions, particularly in energy-efficient hardware design and emerging computing paradigms. His educational journey includes: B.S. in Micro-electronics from Northwestern Polytechnical University, China (2009) M.S. in System-on-Chip Design from KTH Royal Institute of Technology, Sweden (2014) Ph.D. in Electrical Engineering and Computer Science from KTH Royal Institute of Technology (2019) Yao's research centers on power and thermal management for chip multi-processors, Network-on-Chips (NoCs), and GPUs. He pioneers hardware/software co-design for high-performance computing, coherency mechanisms for emerging memory technologies, and performance analysis of on-chip networks. Recent work expands into neural network acceleration and battery-less Internet of Things architectures, reflecting a trajectory toward energy-constrained specialized systems. His methodology integrates formal modeling with practical implementation for real-world impact. Publication trends reveal consistent innovation in energy efficiency across parallel architectures. From foundational DVFS techniques for NoCs (2016-2018) to recent breakthroughs in battery-less IoT (2023-2024), his work demonstrates evolutionary progression toward novel computing domains. Key thematic threads include thermal-aware optimization, memory consistency protocols, and hardware acceleration for AI workloads, with applications spanning data centers to embedded systems. Scientific recognition includes: Best paper candidate at IEEE International Symposium on High Performance Computer Architecture (HPCA) 2018 for in-network packet generation research Yao actively supervises graduate researchers and leads collaborative projects in computer architecture. His grant portfolio supports work on battery-less IoT systems and neural network accelerators, though specific funding details aren't publicly enumerated. Current projects emphasize sustainable computing through novel architectures for energy-harvesting environments. He operates within Uppsala University's Computer Systems division, contributing to research groups focused on hardware acceleration, embedded systems, and networked architectures. His lab environment fosters interdisciplinary work bridging computer architecture, energy harvesting, and machine learning for next-generation computing platforms.

David Black-Schafferمشاهده پروفایل

استاد

• Computer Architecture
• Memory Systems
• Parallel Programming
• +۴ مورد دیگر

David Black-Schaffer is a Professor at Uppsala University's Department of Information Technology, specializing in computer systems research. As of 2023, he serves as Dean of Research for the Faculty of Science and Technology. His work bridges software and hardware innovations to enhance data movement efficiency in computer systems, with applications commercialized through a startup and integrated into industry standards like OpenCL. Black-Schaffer earned his PhD in Electrical Engineering from Stanford University in 2008, focusing on many-core processor programming. His career spans roles at Apple Inc. (contributing to OpenCL standards), postdoctoral research at Uppsala University, and academic progression from assistant to full professor (2010–2017). He has held leadership roles including Head of the Division of Computer Systems (2022) and department representative on the faculty Advisory Committee for Research (2021). His research spans computer architecture, memory systems, parallel programming, and simulation techniques. Recent publications (2024–2020) explore garbage collection, cache optimization, memory contention, NUMA systems, and instruction scheduling. Key trends include software-hardware co-design for power efficiency, reuse-aware data placement, and machine learning for performance modeling. Knut & Alice Wallenberg Foundation: Wallenberg Academy Fellowship Prolongation (2020–2025), Wallenberg Academy Fellow (2016–2021) Swedish Research Council (VR): Project Grant (2019–2024), Young Researcher Grant (2015–2018), Framework Grant (2012–2017) European Research Council: ERC Starting Grant (2017–2022) Teaching Awards: Uppsala Engineering and Science Student Union Pedagogical Prize (2012), Uppsala University Pedagogical Prize (2016), Uppsala Technical Physics Students' Teaching Award (2019) Other Grants: ScalableLearning flipped classroom project (2012–2020), Arm Ltd. collaborations on memory system designs He pioneered flipped-classroom teaching through the ScalableLearning project, impacting over 80,000 students. His research is conducted in collaboration with institutions like Arm Ltd., with past contributions to Apple's OpenCL implementation and UPMARC research center.

Masoumeh Ebrahimiمشاهده پروفایل

دانشیار

• Computer Architecture
• Machine Learning
• Embedded Systems
• +۶ مورد دیگر

Masoumeh Ebrahimi is an Associate Professor at KTH Royal Institute of Technology, Division of Electronics and Embedded Systems, and holds an Adjunct Professor position at the University of Turku, Finland. She leads research in hardware acceleration, neural architecture search, and fault-tolerant systems. Her work bridges machine learning, embedded systems, and network-on-chip (NoC) design. Research Interests: Hardware-Accelerated Machine Learning 6G Network Architectures Fault-Tolerant Computing High-Performance GPU Systems Network-on-Chip (NoC) Design Federated Learning Key Projects: Co-supervisor of Hui Chen’s postdoc project Generalizing hardware acceleration for nonlinear functions . Active in Digital Futures, a cross-disciplinary center focusing on societal challenges using digital tech. Collaborates on edge computing, 6G networks, and resilient embedded systems. Labs & Teams: Core member of KTH’s Digital Futures initiative, advancing AI accelerators and next-gen communication systems. Engaged in EU-funded projects on NoC reliability and federated learning frameworks.

Ming Xiaoمشاهده پروفایل

دانشیار

• Wireless Communications
• Network Coding
• Machine Learning
• +۱۰ مورد دیگر

Ming Xiao is an Associate Professor in the Division of Information Science and Engineering at KTH Royal Institute of Technology's School of Electrical Engineering and Computer Science (EECS). He is affiliated with the Digital Futures Faculty and leads research in wireless communications, machine learning, and network coding. His work focuses on 6G networks, distributed learning, and secure communications. Affiliations: KTH EECS, Digital Futures, Swedish Research Council, EU Horizon Europe projects Roles: Editor for IEEE Transactions on Wireless Communications, TPC Co-Chair for VTC Fall Research Interests: Dr. Xiao's expertise spans wireless communication systems (e.g., mmWave, NOMA), network coding, machine learning applications in communications, and energy-efficient distributed systems. He has pioneered work on intelligent reconfigurable surfaces (RIS), federated learning in edge computing, and integrated sensing-communications (ISAC). Projects: Ongoing EU-funded projects include ASCENT (autonomous vehicular networks) and COVER (unmanned aerial vehicles for emergency response). Past projects include 6G channel coding and intelligent energy management in smart communities. Grants: Over 12 active grants from VR, EU Horizon Europe, FORMAS, STINT, and VINNOVA Awards: IEEE Vehicular Technologies Society Best Paper Award (2023), World Top 2% Researcher (2020–2023), Highly Cited Researcher in Computer Science/Engineering. Labs/Teams: Leads the KTH Digital Futures initiative, collaborates with RISE Research Institutes, and manages a team of 12 PhD students/postdocs focusing on 6G, distributed ML, and secure IoT.

Anders Lansnerمشاهده پروفایل

استاد

• Computational Neuroscience
• Neuromorphic Engineering
• Brain-like Computing
• +۴ مورد دیگر

Anders Lansner is a Professor of Computer Science at Stockholm University and holds an affiliated professorship at KTH Royal Institute of Technology. He leads the Lansner Lab (Computational Biology and Neurocomputing) at the Department of Computational Science and Technology (CST) within the School of Computer Science and Communication (CSC) at KTH. His research focuses on computational neuroscience and brain-like computing, emphasizing mathematical and computational models of neuronal networks in the neocortex and basal ganglia. Key projects include developing neuromorphic algorithms for supercomputers and FPGA-based hardware implementations. Lansner manages the computational neuroscience platform for the Stockholm Brain Institute (SBI) and the neuroinformatics platform for StratNeuro (Karolinska Institutet). His lab contributes to EU projects such as FACETS and NEUROChem, and collaborates with KTH’s Electronics Department on modular brain-inspired FPGA designs. Research interests span synaptic plasticity mechanisms, memory systems (episodic, semantic, and working memory), and applications in neuromorphic computing. He supervises graduate students and teaches courses in computational neuroscience. Lansner’s work bridges theoretical neuroscience with engineering, aiming to advance brain-inspired AI and hardware systems. His lab’s StreamBrain framework supports heterogeneous computing architectures for brain-like neural networks. Notable collaborations include cross-disciplinary efforts in neuromorphic hardware development (e.g., memristor-based learning engines) and olfactory system modeling. Lansner’s research addresses both fundamental brain mechanisms and technical applications in data analysis and neurorobotics.

Aryo Makkoمشاهده پروفایل

استاد

• International Relations History
• Cold War Diplomacy
• Neutrality and Non-Alignment
• +۴ مورد دیگر

Aryo Makko , Professor at Stockholm University , serves as Director of the Hans Blix Center for the History of International Relations . A Pro Futura Scientia XI Fellow at Swedish Collegium for Advanced Study, he has held visiting positions at Ludwig-Maximilians-Universität München (2020/21) and Leibniz Institute for Contemporary History. His research fundamentally reinterprets Cold War neutrality through archival analysis, challenging Sweden's moralistic foreign policy narrative with evidence of strategic realism in his seminal work Ambassadors of Realpolitik (2016) and subsequent monographs. Specializes in 19th-20th Century International Relations Expert on Small States' Diplomacy (Scandinavia, Ottoman minorities) Pioneered Consular History methodology in European Small States and the Role of Consuls (2019) His 15 most recent publications (2010-2025) demonstrate sustained engagement with: Cold War Security Frameworks (CSCE/OSCE) Migration-Diaspora Dynamics (Assyrian communities) Maritime Globalization (Nordic trade networks) Neutrality Paradoxes (Finlandization analogies) Awards & Appointments : Young Academy of Sweden member (2017) Pro Futura Scientia XI Fellow (2016) Associate Professor of History (2016) PhD in History (2012)

Corentin Cadiouمشاهده پروفایل

پژوهشگر ارشد

• Dark Matter
• Star Formation
• High Resolution Simulations
• +۵ مورد دیگر

Corentin Cadiou is a Research Fellow at Lund University's Department of Physics, specializing in Astrophysics. He holds dual positions as a Postdoctoral Fellow in both the Astrophysics division and the eSSENCE: The e-Science Collaboration initiative. His research focuses on computational astrophysics and cosmology, with particular expertise in dark matter, galaxy formation, and cosmic structure evolution. His primary research interests include: Dark matter physics and cosmic web dynamics High-resolution cosmological simulations Galaxy formation and evolution mechanisms Star formation processes in various environments Computational methods in astrophysics Large-scale structure of the universe He employs advanced simulation techniques to study galaxy-scale phenomena and cosmic evolution. Cadiou's recent publications demonstrate a strong focus on developing and optimizing astrophysical simulation codes, analyzing cosmic structures like filaments and dark matter halos, and investigating galaxy formation processes across cosmic time. His work frequently combines theoretical modeling with high-performance computing approaches to address fundamental questions in cosmology. He is currently engaged in the project: eSSENCE@LU 11:4 - Galaxy formation in the exascale era (2025-2026), where he serves as a researcher developing next-generation galaxy formation simulations.

Lars Johanssonمشاهده پروفایل

مدرس

• Industrial Design
• Interaction Design
• User-Centered Design
• +۷ مورد دیگر

Lars Johansson is a Lecturer at the Umeå Institute of Design (UID), part of Umeå University. He specializes in teaching industrial design and interaction design, focusing on methods like sketching, model techniques, and clay work. His research background includes applied projects with Volvo Trucks and Nokia on driver environment systems and wearable computers, alongside prototype development and user studies. Education: Master's in Industrial Design (1994–1999, UID) followed by a shift to Interaction Design. Post-graduation, he worked in applied research until 2013. Currently, his primary role is teaching, with parallel design consulting since 2011. Research Interests: Industrial/Interaction design processes, form aesthetics, prototyping, user studies, automotive interfaces, and playful technology. His work emphasizes tangible interfaces, child-centered design, and safety systems like rollover prevention for vehicles. Publications focus on rollover prevention systems and affective design in children's products. Collaborations include Volvo Trucks, Nokia, and academic conferences like CHI and CAHD. No scientific awards are listed, but his career spans research, teaching, and industry partnerships.