جستجوی استاد راهنمای دانشگاهی

Rebekka Wohlrabمشاهده پروفایل

استادیار

• Requirements Engineering
• Software Architecture
• Self-Adaptive Systems
• +۴ مورد دیگر

Rebekka Wohlrab is a tenure-track Assistant Professor in Software Engineering at Chalmers University of Technology (Gothenburg, Sweden) and an adjunct faculty member at Carnegie Mellon University’s Software and Societal Systems Department (S3D). Her research focuses on requirements engineering, self-adaptive systems, and robotics. She leads a research group supported by the Wallenberg AI, Autonomous Systems and Software Program (WASP). Education: PhD in Computer Science and Engineering (Chalmers, 2020), MSc/BSc in Computer Science (Paderborn University, 2016). Postdoc at Carnegie Mellon University (2020-2022). Research interests include requirements conflicts resolution, quality attribute trade-offs, and ethical monitoring in cyber-physical systems. She has published extensively on adaptive systems, architectural tactics, and agile development practices. Notable contributions include frameworks for robot mission planning, security assurance cases, and traceability management in automotive systems. Recent awards include a pedagogical prize from students at Chalmers. She advises PhD students on topics like self-adaptive robotics and WASP-funded projects. Her work spans theoretical research and industry collaboration (e.g., Volvo Cars). Active in conferences like ICSE, RE, and ICSA as a program committee member. Labs/Teams: Leads the Self-Adaptive Systems Research Group at Chalmers, collaborating with WASP and automotive industry partners.

• Fluid Dynamics
• Nanocellulose Materials
• Biopolymer Assembly
• +۴ مورد دیگر

Fredrik Lundell is Professor of Fluid Mechanics at KTH Royal Institute of Technology, where he leads research in fluid physics, biopolymer assembly, and experimental mechanics. His work bridges fundamental fluid dynamics with applications in sustainable materials, utilizing techniques including synchrotron imaging, microfluidics, and optical coherence tomography. Research encompasses nanocellulose processing, protein nanofibril assembly, turbulence modulation, and multiphase flows. Recent work emphasizes flow-directed assembly of hierarchical biomaterials and energy-efficient fabrication methods. Experimental approaches combine advanced imaging with microfluidic platforms to study complex fluid-structure interactions. Publications demonstrate innovations in nanofiber alignment control, sustainable material design, and multiphase flow characterization. Recent articles focus on microfluidic assembly strategies, interfacial phenomena, and non-Newtonian fluid dynamics. Advises doctoral students investigating diverse topics from turbulent suspensions to biopolymer physics. Directs laboratory facilities for flow measurements and materials characterization, collaborating extensively through the Wallenberg Wood Science Center.

Chao Renمشاهده پروفایل

پژوهشگر

• Quantum Federated Learning
• Federated Learning
• Quantum Computing
• +۳ مورد دیگر

Chao Ren is a Wallenberg-NTU Presidential Principal Researcher (Forskare) at KTH Royal Institute of Technology's Department of Intelligent Systems. He holds a Ph.D. from Nanyang Technological University (NTU), Singapore, where he received the prestigious Graduate College Research Excellence Award. His research focuses on Quantum Federated Learning, Power Engineering, and Big Data Analytics for smart grid stability assessment. Ren has held postdoctoral fellowships at NTU and KTH, collaborating with leading experts like Prof. Mikael Skoglund (IEEE Fellow). Education: Ph.D. in Interdisciplinary Graduate Programme, NTU (2017–2022) B.E. in Computer Science, Nanjing University of Aeronautics and Astronautics (2013–2017) Research Interests: Combining quantum computing with federated learning to enhance cybersecurity and efficiency in power systems. Key areas include dynamic security assessment, adversarial robustness, and battery degradation prediction. His work bridges theoretical advancements and practical applications in smart grids and distributed systems. Awards & Grants: Winner of Graduate College Research Excellence Award (NTU, 2022) Wallenberg AI, Autonomous Systems & Software Program (WASP) grant (SEK 300,000) NTU grant for 'Modern Smart Grid Stability Assessment' (S$100,000) Professional Activities: Guest Lecturer at KTH, Editorial Board member for IET AI for Engineering, and reviewer for top conferences like NeurIPS and AAAI. Active in organizing workshops on federated learning and quantum computing. Labs & Teams: Leads the Trustworthy Federated Ubiquitous Learning Research Lab (AI Singapore-TrustFUL) and collaborates with the Singapore Power Group-NTU Joint Lab. Focuses on interdisciplinary projects involving energy systems, AI, and quantum technologies.

• Materials Science
• Metallurgy
• Materials Engineering
• +۳ مورد دیگر

Alexander Dahlström is a Lecturer at the KTH Royal Institute of Technology, where he serves as a teacher and course coordinator for 'Material Design I (MH1030)'. His research focuses on advanced materials science, particularly in metallurgical systems, nanostructure evolution, and high-performance alloys. Key areas include microstructural analysis under thermal and mechanical loads, phase transformations in metallic alloys, and computational modeling of material behavior. His work integrates experimental techniques such as atom probe tomography and thermal treatments to investigate fundamental material properties. Notable research themes include high-entropy alloys, embrittlement mechanisms in stainless steels, and wear behavior of austenitic stainless steels. Dahlström contributes to bridging computational thermodynamics with practical material design, emphasizing real-world applications in engineering systems. Although no scientific awards or grants are explicitly mentioned, his active publication record highlights sustained contributions to metallurgy and materials engineering. No lab affiliations or student advisees are listed in the provided information.

• Materials Science
• Metallurgy
• Mechanical Engineering
• +۳ مورد دیگر

Mohammad Hoseini Athar is a Researcher at the Department of Materials Science and Engineering (MSE) at KTH Royal Institute of Technology, affiliated with the Hultgren Laboratory for Materials Characterization. He earned his PhD in Materials Science and Engineering from the University of Tehran in 2019 and has since held postdoctoral and researcher roles at KTH. His work focuses on understanding microstructure-mechanical property correlations in engineering materials, combining experimental mechanical testing with advanced materials modeling. Current projects include leading EU-funded initiatives such as REPAM (powder production/recycling optimization), Steel4Fatigue (high-strength steels for mobility), and NEXT (neutron/synchrotron-based materials innovation), as well as Vinnova-funded projects like RECaSt (durable cast steel design). His research emphasizes fatigue behavior, residual stress analysis, and alloy development for industrial applications. He leads a team of postdoctoral researchers and doctoral students, specializing in experimental and computational analysis of materials under extreme conditions. His interdisciplinary approach bridges materials characterization, mechanical behavior modeling, and sustainable manufacturing processes.

• Energy Materials
• Solid-State Batteries
• Materials Science
• +۳ مورد دیگر

Raquel Lizarraga Jurado is an Associate Professor (Docent) in Energy Materials at Kungliga Tekniska Högskolan (KTH). She holds a PhD in Physics from Uppsala University and completed postdoctoral research at Los Alamos National Laboratory. Her research focuses on atomistic modeling and first-principles methods applied to energy materials, particularly solid-state Li/Na-ion batteries, glassy electrolytes, and non-collinear magnetism in transition metals. She contributes to sustainable energy systems aligned with UN SDGs 7 (Affordable Energy) and 13 (Climate Action). Education: PhD in Physics, Uppsala University Postdoctoral Research, Los Alamos National Laboratory Docent in Energy Materials, KTH (2023) Research interests include computational materials modeling, electrochemical stability of battery materials, and phase transitions in alloys. Her work bridges fundamental physics with industrial applications in hardmetals and energy storage. She teaches Additive Manufacturing (MG2044) . Research trends: Recent publications address 2D heterostructures for photovoltaics, cemented carbide mechanics, and high-entropy alloy design. These studies emphasize computational approaches to predict material performance and guide sustainable innovation. Labs/Teams: Active within KTH's Unit of Properties, focusing on experimental/theoretical synergy in materials development.

• Fluid Mechanics
• Mechanical Engineering
• Aerospace Engineering

Diego Ignacio Diaz Diaz is a Postdoctoral fellow at the FLOW MECHANICS division of KTH Royal Institute of Technology. He is affiliated with the university's research and collaboration initiatives, and his work address is located at Osquars Backe 18 in Stockholm, Sweden. His research interests are centered around flow mechanics and related disciplines, including fluid dynamics and computational methods in engineering. While specific projects are not detailed here, his affiliation with the FLOW MECHANICS group suggests a focus on theoretical or applied fluid systems.

• Fluid Mechanics
• Shock Wave Dynamics
• High Energy Density Physics
• +۳ مورد دیگر

Michael Liverts is an Associate Professor in the Department of Fluid Mechanics at KTH Royal Institute of Technology. He specializes in shock wave dynamics, fluid mechanics, and high-energy density physics. His work focuses on experimental and computational studies of shock wave interactions, blast mitigation using foams, and advanced measurement techniques for dynamic pressures and temperatures. Liverts teaches courses such as Compressible Flow, Sustainable Development Methodology in Mechanics, and Mechanics I/II. He coordinates and examines multiple advanced-level degree projects in fluid mechanics and mechanics. Research interests include shock wave convergence, real gas effects, underwater electrical explosions, and multiphase flow dynamics. His recent studies explore cylindrical shock wave behavior, supersonic jet generation via blast focusing, and the critical parameters governing wire explosion dynamics. Liverts has developed novel calibration methods for sensors measuring extreme pressures and temperatures (up to 3000°C) with sub-millisecond response times. Publications span over two decades, with a focus on shock wave phenomena, thermal inhomogeneity effects, and foam-based blast mitigation strategies. His work bridges fundamental fluid mechanics with applied engineering solutions, particularly in safety systems and energy research. Liverts collaborates on European metrology projects (e.g., DynPT) and has contributed to high-current generator design for high-energy-density matter studies. Teaching responsibilities include course coordination for core mechanics courses and advanced compressible flow modules. His pedagogical approach integrates research insights into curriculum design, emphasizing sustainable development principles in engineering education.

• Fluid Dynamics
• Mechanical Engineering
• Computational Fluid Dynamics
• +۳ مورد دیگر

Federica Tonti is a Research Fellow at the Department of FLOW MECHANICS within KTH Royal Institute of Technology in Stockholm, Sweden. Her work focuses on fluid dynamics and related computational methodologies. While no specific educational background is detailed in the provided text, her affiliation with KTH—a leading technical university—suggests a strong academic foundation in engineering or applied physics. Her current role as a postdoctoral fellow implies ongoing research contributions to flow mechanics. No awards, grants, or specific advising activities are mentioned in the available data. Her affiliation with the FLOW MECHANICS group suggests involvement in collaborative research projects related to fluid dynamics applications.

• Fluid Mechanics
• Turbulence
• Aerodynamics
• +۴ مورد دیگر

Ramis Örlü is a Full Professor of Fluid Mechanics at OsloMet – Oslo Metropolitan University (since 2024). Previously, he held roles including Associate Professor at OsloMet (2023–2024), Adjunct Professor at the University of Bologna (2017–2023), and Docent at KTH Royal Institute of Technology (2015–2023). He obtained his Ph.D. in engineering mechanics from KTH in 2009 and an engineering degree from Ruhr University Bochum in 2003. His research focuses on turbulent flows, skin-friction and drag reduction, experimental fluid dynamics, and high-fidelity simulations. He has extensive experience with wind tunnel facilities and advanced measurement techniques. He serves as editor of Experimental Thermal and Fluid Science and on editorial boards of Flow, Turbulence and Combustion and Advances in Aerodynamics . His recent work includes studies on turbulent boundary layers around airfoils, adverse pressure gradient effects, and plasma actuator efficiency. He has collaborated with institutions like KIT, FAU Erlangen, and Turkish-German University through guest professorships and fellowships. Örlü’s research bridges fundamental fluid mechanics with industrial applications, emphasizing turbulence control and flow characterization. His experimental and simulation datasets are publicly accessible for select cases, furthering collaborative research efforts.

• Machine Learning
• Combinatorial Optimization
• Network Resource Management
• +۳ مورد دیگر

Daniel Felipe Perez Ramirez is an industry doctoral student at KTH Royal Institute of Technology, affiliated with the Division of Software and Computer Systems within the School of Electrical Engineering and Computer Science . His research focuses on applying machine learning to solve combinatorial optimization problems in networked systems, emphasizing scalability and generalization. He is involved in the SSF project 'Instant Cloud Elasticity' and the Horizon 2020 AI@Edge project. Education: B.Sc. in Mechanical Engineering (Technical University of Munich) M.Sc. in Robotics, Cognition, Intelligence (Technical University of Munich) His research interests span machine learning applications in combinatorial optimization, resource management for networked systems, and scalability challenges in AI. Prior to joining KTH, he worked at RISE Research Institutes of Sweden AB as a research engineer, focusing on applied machine learning for automotive industries, robotics sensor integration, and agile product development methods. Advisors: Prof. Dejan Kostic and Prof. Magnus Boman. Labs/Teams: Collaborates with RISE and KTH’s research divisions in networked systems.

• Nuclear Safety Engineering
• Severe Accident Management
• Thermal Hydraulics
• +۳ مورد دیگر

Sevostian Bechta is a Professor in the Department of Nuclear Science & Engineering at KTH Royal Institute of Technology. His research focuses on severe accident management, corium behavior, and thermal-hydraulic phenomena in nuclear reactors. He has contributed to international projects like SAFEST, investigating corium interactions and in-vessel retention strategies. Key roles include examiner and course leader for nuclear safety courses such as Nuclear Safety (SH2612) and Nuclear Power Safety Engineering Project (FSH3001) . His work spans experimental and computational studies of melt behavior, steam explosions, and debris bed coolability. Collaborations include OECD/ROSAU and QUENCH-20 experiments, with publications in journals like Annals of Nuclear Energy and Nuclear Engineering and Design . Research highlights include developing numerical methods (MPS, MELCOR coupling) for simulating severe accident progression and validating safety guidelines. His team explores material interactions, oxidation effects, and ex-vessel core catcher designs.

• Nuclear Power Safety
• Multiphase Flow and Heat Transfer
• Nuclear Reactor Safety Analysis
• +۴ مورد دیگر

Weimin Ma is a Professor in Nuclear Power Safety at the Department of Physics at KTH Royal Institute of Technology, and Deputy Head of the Division of Nuclear Science and Engineering. His work focuses on nuclear safety across existing and future reactor designs, addressing challenges in accident prevention and mitigation. Research Interests: Nuclear power safety, multiphase/multi-physics accident analysis, severe accident management, reactor pressure vessel integrity under core melt attack, and safety of advanced reactor technologies like lead-cooled fast reactors (LFRs) and small modular reactors (SMRs). His group develops experimental methods (e.g., simulant melt studies) and computational tools (e.g., MELCOR coupling) to improve accident modeling and risk assessment. Key Research Areas: Melt coolant interactions, steam explosions, debris bed coolability, thermal-hydraulic phenomena, and best-estimate plus uncertainty (BEPU) methods. Recent studies include turbulence modeling in melt pools, surrogate models for safety analysis, and experimental validation of severe accident scenarios. Publications highlight contributions to understanding core meltdown accidents, coolant interaction dynamics, and safety analyses for both current and next-generation reactors. Collaborations include international projects like OECD/ROSAU and SARNET networks. Teaching: Courses on nuclear safety, thermal-hydraulics, and sustainable energy engineering, emphasizing practical skills through compact reactor simulators and project-based learning.

Malin Wohlertمشاهده پروفایل

دانشیار

• Molecular Modeling
• Biomaterials Science
• Materials Science
• +۳ مورد دیگر

Malin Wohlert is an Associate Professor at Uppsala University's Department of Materials Science and Engineering; Applied Mechanics. Her research focuses on molecular modeling of biomaterials, particularly wood's structural and hygroscopic properties. She investigates lignin behavior, hygroexpansion mechanisms, and wood mechanics using molecular dynamics simulations and experimental methods. Wohlert is a member of the Biophysics Network and contributes to pedagogical initiatives, including teaching Solid Mechanics and supervising the Supplemental Instruction program at the Construction Engineering Bachelor's program. She also supports educational development through the faculty's Council for Educational Development. Research Focus: Wohlert's work bridges molecular-level phenomena with macroscopic material behavior, emphasizing lignin hydration, wood anisotropy, and hygroelastic properties. Her studies employ advanced techniques like microscopic computed tomography and finite element modeling to analyze wood's structural responses under environmental stresses. Recent projects explore compression/ opposite wood in conifer branches and lignin's role in material degradation processes. Teaching & Pedagogy: She teaches Solid Mechanics courses and mentors students in practical engineering education. Her contributions to educational development include curriculum design and pedagogical strategy implementation. Labs & Collaborations: Active within the Biophysics Network, she collaborates on interdisciplinary projects involving material characterization and biomaterials innovation. Her research group integrates computational modeling with experimental validation to advance understanding of natural materials' complex behaviors.

• Federated Learning
• Wireless Communication Systems
• Machine Learning
• +۳ مورد دیگر

Dr. Mairton Barros is an Assistant Professor in the Division of Computer Systems at Uppsala University, Sweden. Previously, he held a Marie Skłodowska-Curie Postdoctoral Fellowship at Princeton University and KTH Royal Institute of Technology. His research focuses on federated learning, wireless communications, and optimization algorithms. He received his PhD from KTH in 2019, with earlier degrees from the Federal University of Ceará, Brazil. Education: PhD in Electrical Engineering, KTH Royal Institute of Technology (2019) MSc in Telecommunications Engineering, Federal University of Ceará (2014) BSc in Telecommunications Engineering, Federal University of Ceará (2012) Affiliations: Postdoctoral Researcher, KTH (2019-2022) Visiting Researcher, Princeton University (2022) Research Interests: His work bridges machine learning and wireless communications, emphasizing federated learning, full-duplex systems, and mmWave technologies. Key contributions include optimizing communication efficiency in distributed learning frameworks and advancing smart antenna techniques for full-duplex networks. Professional Activities: He has organized conferences (e.g., IEEE SECON 2022, IEEE GLOBECOM workshops) and delivered tutorials on wireless machine learning at major IEEE events. Recent grants include funding from Ericsson Research (2022). Lab/Team: Leads research initiatives in distributed intelligence and edge computing within Uppsala’s computer systems division.