جست‌وجوی استاد و پژوهشگر

• Dermatology
• MicroRNA Research
• Psoriasis
• +۴ مورد دیگر

Enikö Sonkoly is an active Senior Lecturer (Docent) and research group leader at the Department of Medicine, Solna, Karolinska Institutet, Stockholm, Sweden. Her work centers on molecular mechanisms in inflammatory skin diseases and skin cancer, with primary affiliations to the Division of Dermatology and Venereology and ongoing collaborations across European and international institutions. Her research interests include: Dermatology (psoriasis, atopic dermatitis, skin cancer) Non-coding RNA biology (microRNAs, long non-coding RNAs) Epidermal barrier function and dysregulation Keratinocyte-immune system interactions Wound healing and inflammation Transcriptomic analysis of skin diseases She has pioneered studies on RNA signatures in psoriasis keratinocytes, identified tumor-suppressive miRNAs in cutaneous squamous cell carcinoma, and explored chromatin dynamics in skin inflammation. Recent work leverages single-cell sequencing to map cellular interactions in psoriasis while investigating clinical implications of biologics through trials like VOYAGE 2. Publication trends (2022-2025) highlight three key directions: (1) Functional characterization of specific non-coding RNAs (e.g., CYDAER, LINC00958) in epidermal dysregulation, (2) Clinical translation of RNA findings through biologics trials and registry studies, and (3) Integration of single-cell genomics with inflammation pathways. Her group consistently bridges molecular mechanisms and clinical dermatology. Scientific awards: No awards, prizes, or fellowships are documented in the provided text. Advising and grants: Dr. Sonkoly supervises doctoral students Jan Cedric Freisenhausen (thesis 2025) and Longlong Luo (thesis 2023), with Luo also listed as affiliated staff. Her group includes Lars Norlen (Docent) and international collaborators. The text provides no grant details, funding sources, or project-specific financial information. Labs and teams: She heads the Research group Enikö Sonkoly at Karolinska Institutet, focusing on RNA mechanisms in skin diseases. The group utilizes next-generation sequencing, single-cell analysis, and functional assays to study keratinocyte biology within a multidisciplinary framework that includes clinical dermatology, immunology, and molecular oncology components.

• Cell Cycle Regulation
• Mitotic Entry Signaling
• DNA-damage Checkpoints
• +۳ مورد دیگر

Arne Lindqvist is a Principal Researcher and Docent at the Department of Cell and Molecular Biology, Karolinska Institutet, where he leads the research group focusing on cell cycle, mitotic entry, and DNA-damage checkpoints. His work investigates how human cells decide to divide through signaling networks regulating mitotic entry and their interaction with DNA-damage checkpoints. Education: Docent, Karolinska Institutet (2016) PhD in Cell and Molecular Biology, Karolinska Institutet (2005) Dr. Lindqvist's research employs two complementary approaches: investigation of individual protein functions in mitotic regulation, and development of biophysical models to understand system-level behaviors. His group specializes in advanced microscopy techniques to study these processes. Primary research areas include CDK1/PLK1 activation dynamics, DNA replication-checkpoint interactions, and cell cycle exit mechanisms. His publication record (2015-2025) demonstrates consistent focus on cell cycle regulation, with recent work emphasizing CDK1 activation mechanisms, topoisomerase functions during mitosis, and metabolic regulation of cell division. Research consistently integrates molecular biology, biophysics, and advanced imaging approaches. Research Group: Karen Akopyan (Research Specialist) Zhiyu Hao (PhD Student) Funding: Awarded Swedish Cancer Society grant (2025-2027) as part of departmental SEK 40 million funding initiative.

Yi Wangمشاهده پروفایل

استاد

• Embedded Systems
• Real-Time Systems
• Real-Time Scheduling
• +۷ مورد دیگر

Yi Wang is a Professor of Embedded Systems at the Department of Information Technology, Uppsala University , Sweden. He leads research in real-time and embedded systems with a focus on modeling, analysis, and implementation of safety-critical applications. He is affiliated with the Embedded Systems Group and serves as a Principal Investigator (PI) in major research centers such as UPMARC and projects like CUSTOMER (ERC Advanced Grant), CoDeR-MP, and CERTAINTY. Research Interests: Yi Wang’s work centers on Embedded Systems Design, Real-Time Scheduling, Multicore Programming, and Model-Checking of Real-Time Systems . His research addresses fundamental challenges in timing predictability, schedulability analysis, and the verification of complex real-time systems. He has made significant contributions to the digraph real-time task model, mixed-criticality systems, and timing analysis of ROS 2 systems. His work bridges theory and practice, often resulting in deployable tools and formal methods for industrial applications. Recent Research Trends: His most recent publications (2023–2025) focus on optimizing real-time performance in ROS 2, managing parallel task graphs with resource contention, improving GPU-based inference on embedded platforms, and enhancing timing predictability in multithreaded executors. These works reflect a strong trend toward applying formal real-time theory to modern robotics, AI integration, and multicore embedded architectures. Scientific Tools and Leadership: He is a key contributor to foundational tools in real-time systems: UPPAAL – Model checking for timed automata TIMES – Schedulability analysis and code generation CATS – Compositional analysis of timed systems TIMES-Pro – Based on the digraph real-time task model Advising and Research Funding: Yi Wang has supervised numerous PhD students and postdocs. He has led or participated in multiple large-scale funded projects supported by the Swedish Research Council (VR), the Swedish Foundation for Strategic Research (SSF), and the European Commission (FP7, ERC). These include UPMARC (10-year Linnaeus center), CoDeR-MP (with ABB and SAAB), SAVE++ (with VOLVO), and CREDO. Laboratories and Research Groups: He is a core member of the Embedded Systems Group at Uppsala University and leads research within the UPMARC center, which focuses on programming models and analysis techniques for multicore architectures. His lab develops formal methods and tools to ensure correctness and timing guarantees in embedded and cyber-physical systems.

Vedrana Bolic Baricمشاهده پروفایل

مدرس

• Inclusive learning environments
• Occupational therapy
• Child development
• +۴ مورد دیگر

Vedrana Bolic Baric is a Lecturer at Linköping University's Faculty of Medicine, specializing in inclusive learning environments and transition processes for youth with neuropsychiatric disabilities. Her research focuses on universal design for learning, digital health interventions, and occupational therapy applications for educational and health equity. Doctor of Medicine (2016) Master's in Occupational Therapy (2010) Licensed Occupational Therapist (2007) Her research investigates how inclusive pedagogical frameworks and technological interventions (like weighted blankets and digital coaching tools) can improve educational outcomes and life transitions for neurodiverse populations. Current projects include international implementation of Partnering for Change (P4C) and welfare technology studies in elder care. Recent scientific recognition includes: Educator of the Year 2024 by Consensus Principal investigator for RemindMe digital planning tool development Collaborations through ERASMUS+ and Joint Innovation Partnership for Learning (JIP4L) networks

Josef Bigunمشاهده پروفایل

استاد

• Computer Vision
• Artificial Intelligence
• Biometric Signal Analysis
• +۳ مورد دیگر

Josef Bigun is a Professor at the School of Information Technology, Halmstad University , Sweden, since 1998. His research focuses on Computer Vision, Biometric Signal Analysis, and Artificial Intelligence , with emphasis on periocular recognition, iris biometrics, and motion analysis . He has been recognized as a Fellow of the IAPR (2000) and Fellow of the IEEE (2003) , becoming Sweden's first IEEE Fellow in image analysis. Education : M.Sc. and Ph.D. from Linköping University (1983, 1988) Key Projects : EU projects (BBfor2, BIOSECURE, ACTS-M2VTS), Swedish VR/SSF projects, Swiss Fonds National projects His recent publications focus on CNN optimization, periocular biometrics, and cross-spectral recognition . He has developed innovative Continuous Examination systems using spiral codes for educational assessment and contributed to biometric standards for the European Association for Biometrics . Scientific Awards : Fellow of the IAPR (2000) Fellow of the IEEE (2003) Top 10 Scientist in Sweden (Scopus AI & Image Processing, 2024 Stanford study) Listed on research.com's top Computer Science researchers (Sweden) He has served on organizing committees for ICPR, ICIP, ICB conferences and co-founded the Audio and Video Based Person Authentication conference (now ICB). His work appears in journals like Pattern Recognition Letters and IEEE Image Processing .

Jonatan Schytzerمشاهده پروفایل

مدرس ارشد

• Insolvency Law
• Bankruptcy Law
• Civil Law
• +۴ مورد دیگر

Jonatan Schytzer is a Senior Lecturer in Civil Law at the Department of Law, Uppsala University. He earned his Doctor of Law degree in 2021 and has been recognized as Teacher of the Year (2021). His primary affiliation is with Uppsala University, where he conducts research on insolvency law frameworks and corporate restructuring mechanisms. His research interests span: Insolvency and bankruptcy law, focusing on claim origination and debt prioritization Environmental liabilities in bankruptcy, particularly remediation costs for mining and industrial sites EU directive implementation in Swedish restructuring laws Taxation aspects in insolvency proceedings Corporate viability assessment methodologies Schytzer's publications (2021-2025) demonstrate evolving focus areas: Early work (2021-2022) established foundations in claim origination and VAT/taxation frameworks Recent studies (2023-2025) emphasize environmental liabilities, mining bankruptcies, and EU harmonization Emerging themes include corporate restructuring viability tests and judicial efficiency Honors include: Teacher of the Year (2021) Insolvency Law Forum Award for doctoral thesis (2022) Research projects and grants: Corporate Reconstruction: Towards an Improved Viability Test (2024-2026) - Funded by Jan Wallander & Tom Hedelius Foundation and Tore Browaldhs Foundation The Environment in Bankruptcy (2022-2024) - Funded by Torsten Söderberg's Foundation World Bank collaboration on climate change and insolvency law (2024) He coordinates international networks as board member of Younger Academics Network of Insolvency Law (YANIL) and leads interdisciplinary collaborations with business economists.

Moa Johanssonمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Automated Reasoning
• Neuro-Symbolic Methods
• +۴ مورد دیگر

Moa Johansson is an Associate Professor (Docent) at the Department of Computer Science and Engineering, Chalmers University, Sweden. She serves as Co-Director of Chalmers' Area of Advance in Information and Communication Technology, driving interdisciplinary AI research. PhD in Automated Theorem Proving (University of Edinburgh, 2009) Postdoc at University of Verona (2009-2011) Her research spans neuro-symbolic AI methods , combining neural networks with symbolic reasoning for applications in mathematics, sports science, and political science. Current projects include: NeSSy (2023-): Neuro-symbolic synthesis via reinforcement learning Neurodynamic Programming (2023-): Agent communication learning Countering Bias in AI (2023-): NLP applications in social sciences Bias in Political Analysis (2020-2025): WASP-HS funded Recent publications focus on theory exploration , neuro-symbolic methods , and AI applications across disciplines. Scientific achievements include a VINNMER Marie Curie Fellowship and Best Paper Award at CICM 2014. Led TRACKS project course on sports digitalization Developed HipSpec automated inductive prover

• Information Theory
• Network Communication
• Empirical Coordination
• +۴ مورد دیگر

Michail Mylonakis is a researcher at KTH Royal Institute of Technology's School of Electrical Engineering and Computer Science, specifically within the Department of Information Science and Engineering. He completed his doctoral studies in 2023 with a dissertation focusing on empirical coordination frameworks in network communication systems. His research interests center on information theory with particular emphasis on empirical coordination over networks, statistical coordination frameworks, and interference management in communication channels. Mylonakis has developed novel approaches to coordination problems subject to fidelity criteria, extending traditional frameworks to handle practical constraints in network communication. His publication record shows a consistent focus on theoretical aspects of network information theory, with particular attention to multi-agent coordination, interference control, and communication constraints. His work demonstrates strong mathematical foundations in probability theory and information-theoretic analysis. Mylonakis has collaborated extensively with researchers including Fotios/Photios Stavrou and Mikael Skoglund, producing significant contributions to the field of empirical coordination theory through multiple conference publications and his doctoral dissertation.

Gregorio Marchesiniمشاهده پروفایل

پژوهشگر

• Multi-Agent Systems
• Robotics
• Control Systems
• +۷ مورد دیگر

Gregorio Marchesini is a doctoral student at KTH Royal Institute of Technology, affiliated with the Department of Intelligent Systems under the School of Electrical Engineering and Computer Science. His research focuses on networked systems control under spatio-temporal and communication constraints, with an emphasis on formal methods for multi-agent systems in mixed autonomy environments. He is associated with the EU project SymAware , which develops situational awareness frameworks for autonomous systems. His research interests include Signal Temporal Logic (STL) for task specification Multi-agent planning and control Graph theory and predictive control Formal methods in robotics The articles he has co-authored address topics such as temporal logic planning , decentralized control , and communication-constrained optimization for multi-agent systems. These works often intersect with robotics , control theory , and autonomous navigation in complex environments. Gregorio actively mentors students, encouraging collaboration on MSc thesis projects related to his research. His software contributions and technical insights, such as optimizing Model Predictive Control (MPC) using CasADi's to_function() and warm-starting techniques, are shared on platforms like GitHub and personal blogs. He is involved in the Decision and Control Systems (DCS) division, contributing to both theoretical and applied aspects of autonomous systems.

Karl-Ludwig Besserمشاهده پروفایل

استادیار

• Ultra-reliable communications
• Resilience of communication systems
• Copulas
• +۲ مورد دیگر

Karl-Ludwig Besser serves as Assistant Professor in the Division of Communication Systems within Linköping University's Department of Electrical Engineering since January 2025. Previously, he completed a postdoctoral fellowship at Princeton University's Department of Electrical and Computer Engineering (March 2023–December 2024), following his 2022 PhD from Technische Universität Braunschweig. His academic foundation includes: Dipl.-Ing. in Electrical Engineering, Technische Universität Dresden (2018) PhD in Electrical Engineering, Technische Universität Braunschweig (January 2022) Dr. Besser's research centers on ultra-reliable communication systems , physical layer security under resource constraints , and copula-based modeling of channel dependencies . His work bridges theoretical information theory with practical machine learning applications, particularly in reconfigurable intelligent surfaces (RIS) and integrated sensing-communication (ISAC) systems. Recent publications demonstrate expertise in secret-key budget management for resilient networks and UAV swarm coordination using 3D beamforming techniques. Analysis of his 15 most recent publications (2024–2025) reveals three dominant themes: (1) RIS optimization using physics-informed neural networks addressing mutual coupling challenges, (2) fundamental limits of physical layer security in dependent fading channels with secret-key budgets, and (3) machine learning solutions for UAV mobility management and mmWave resource allocation. His work consistently targets ultra-reliable low-latency communication (URLLC) requirements for next-generation networks. As part of Linköping University's Communication Systems division, Dr. Besser contributes to research initiatives including Wireless Communications for Distributed Intelligence and Integrated Sensing and Communications (ISAC) . While specific grant details aren't documented in source materials, his research aligns with European 6G initiatives and national security-focused wireless projects. The division actively supervises 25+ PhD students across topics including drone swarm communication, energy-efficient signal processing, and smart city sensor networks, where Dr. Besser likely participates in student mentorship.

• Information and Communication Theory
• Convolutional Codes
• Digital Subscriber Lines
• +۶ مورد دیگر

Stefan Höst is a Senior Lecturer and Head of Department at the Department of Electrical and Information Technology , part of Lund University's Faculty of Engineering (LTH). He is also affiliated with ELLIIT (Linköping-Lund initiative on IT and mobile communication) and the LTH Profile Area focusing on AI and Digitalization. Academic Role: Senior Lecturer Key Affiliations: Secure and Networked Systems, ELLIIT, AI and Digitalization Profile Area Research Focus: Information and communication theory, convolutional coding, OFDM system optimization, and latency-critical network services. Research Trends: His work bridges theoretical and applied aspects of communication systems, focusing on signal compression, network architecture for 5G, and cross-layer optimization in OFDM environments. Projects emphasize practical deployment challenges in optical networks and residential 5G services. Projects: Principal Investigator for DIGITHUBSE (Digital Europe Programme) and FU5ION (Future 5G networks). Collaborated extensively in initiatives like A5GARD and GOLD, addressing legacy infrastructure modernization.

Sune Bechmann Pedersenمشاهده پروفایل

دانشیار

• digital history
• Contemporary history
• Media history
• +۷ مورد دیگر

Sune Bechmann Pedersen serves as Associate Professor in the Department of History within Lund University's Faculty of Humanities and Theology, with additional affiliation as Senior Lecturer in digital history at Stockholm University. His work bridges traditional historical scholarship with digital methodologies through initiatives like DigitalHistory@Lund. His research focuses on digital history , contemporary history , and media history , with particular expertise in tourism history , Cold War studies , and historical GIS . His approach integrates computational methods with historical analysis to examine topics like Czechoslovak tourist attractions and European tourism governance. Recent publications reveal strong thematic clusters in media history (evident in 2023's 'Expanding Media Histories'), digital methodologies (particularly Historical GIS applications), and Cold War tourism (including state-controlled travel systems). His work consistently examines how historical narratives are constructed through material and digital media. Bechmann Pedersen leads significant research initiatives including the SVÄRDH project on Swedish digital history development and EUROPAST focusing on public history for European cohesion. He coordinates the DigitalHistory@Lund network and participates in the Entangled Media Histories project. As an active academic organizer, he has chaired the 5th Digital History in Sweden Conference and developed workshops like 'Knit and Code' that merge material practices with digital scholarship. His research profile shows extensive collaboration across Nordic institutions and European networks.

• Telecommunications
• Compressive Sensing
• Cognitive Radio
• +۴ مورد دیگر

Ricardo Blasco-Serrano is a researcher affiliated with KTH Royal Institute of Technology , specifically within the School of Electrical Engineering (EES) and the Communication Theory department. His work focuses on telecommunications , with emphasis on compressive sensing , cognitive radio , and network coordination . He has contributed to theoretical frameworks for interference management and sparse signal recovery. Education : Doctorate in Telecommunications from KTH Royal Institute of Technology (2013). His research explores the tradeoff between measurement rates and estimation accuracy in compressive sensing, interference coordination in cognitive radio channels, and polar codes for network compression. Key collaborations include work with Ragnar Thobaben, Mikael Skoglund, and Eduard Jorswieck, supported by EU FP7 grant 257626. Notable publications include work on vehicle-to-everything (V2X) communication , partial support recovery , and MISO cognitive channel strategies . His methods have implications for machine-to-machine communication and network densification .

• Distributed Machine Learning
• Federated Learning
• Decentralized Optimization
• +۳ مورد دیگر

Hao Chen is a researcher at KTH Royal Institute of Technology, affiliated with the School of Electrical Engineering and Computer Science (EECS), specifically within the Computer Science department focusing on Communication Systems and the Optical Network Laboratory (ON Lab). He also contributes to research in Intelligent systems and Information Science and Engineering. Chen completed his doctoral dissertation titled 'Reliable and Efficient Distributed Machine Learning' in 2022, establishing himself as an emerging expert in distributed machine learning systems. Chen's research interests center around distributed and federated machine learning architectures, with particular emphasis on optimizing communication efficiency in decentralized systems. His work addresses critical challenges in distributed learning including communication bottlenecks, straggler nodes (devices with slow responses), and privacy preservation. His research spans applications in wireless IoT networks, satellite communications, and edge computing environments. His publication record shows a clear trajectory of increasingly sophisticated approaches to distributed machine learning. Starting with foundational work on coded stochastic ADMM methods in 2021, he progressed to developing asynchronous parallel algorithms (2023) and exploring applications in specialized domains like speech fatigue recognition (2024). A consistent theme across his work is the optimization of communication resources while maintaining learning performance, with particular attention to real-world constraints in wireless and satellite networks. Chen has collaborated extensively with researchers including Ming Xiao, Mikael Skoglund, Yu Ye, and others across multiple publications. His research has been supported by funding sources including the EU Horizon 2020 program (grant 825272) and the Swedish Foundation for Strategic Research (APR20-0023). His work appears in high-impact journals including IEEE Transactions on Big Data, IEEE Internet of Things Journal, and IEEE Wireless Communications. As a researcher at KTH, Chen contributes to cutting-edge work at the intersection of machine learning and communication systems, developing techniques that enable efficient distributed intelligence across networked devices while addressing practical constraints of real-world deployment.

• Computer Science
• Concurrency
• Programming Languages
• +۷ مورد دیگر

Konstantinos Sagonas is a Senior Lecturer/Associate Professor at Uppsala University's Department of Information Technology. His work bridges theoretical and practical aspects of computer science, focusing on concurrency, formal verification, and functional programming in Erlang. Despite his self-identification as a "terrible e-mail responder," he encourages phone contact for direct communication. University: Uppsala University Department: Department of Information Technology Academic Rank: Senior Lecturer/Associate Professor His research spans from stateless model checking and dynamic partial order reduction for concurrent systems to static analysis and type systems in functional programming. Recent work explores IoT protocol testing via fuzzing and symbolic execution, fine-grain memory coherence for security, and automated detection of state machine bugs in network protocols. Key publication trends include formal methods (2024: "Testing IoT Protocol Requirements"; 2023: "Tailoring Stateless Model Checking for Event-Driven Programs") and concurrent data structures (2021: "Lock-free Contention Adapting Search Trees"). Earlier contributions focus on Erlang optimization (2002-2018) and logic programming tabling (1999-2006).