Find Academic Supervisors

• Composite Materials
• Structural Mechanics
• Lightweight Structures
• +3 more

Stefan Hallström is an Associate Professor in Lightweight Structures at KTH Royal Institute of Technology's Aeronautical and Vehicle Engineering School, affiliated with the MATERIAL AND STRUCTURAL MECHANICS department. He specializes in composite materials, structural mechanics, and lightweight design, focusing on aerospace and automotive applications. His research explores advanced composites, sandwich structures, and material behavior under various loading conditions. Hallström teaches courses including Lightweight Design (SD2432), Lightweight Structures and FEM (SD2411), and supervises degree projects in Lightweight Structures and Solid Mechanics. He has published extensively on topics like 3D-woven composites, damage tolerance, and mechanical reinforcement strategies, with over 90 peer-reviewed articles. His work emphasizes material characterization, finite element modeling, and practical applications in structural engineering. Key research trends include optimizing composite joint performance using metal inserts, analyzing moisture effects on composite laminates, and developing frameworks for modeling 3D textile architectures. His contributions address challenges in aerospace materials, energy absorption in beams, and improving simulation accuracy for molded composites. Hallström collaborates on projects involving novel instrumented test rigs for polymer composites and advanced manufacturing techniques for structural reliability. His expertise bridges theoretical mechanics with practical engineering solutions, influencing both academic research and industrial applications.

Morteza Haghir ChehreghaniView profile

Professor

• Machine Learning
• Decision Making
• Reinforcement Learning
• +17 more

Morteza Haghir Chehreghani is a Professor of Artificial Intelligence and Machine Learning at the Data Science and AI Division of Chalmers University of Technology , Sweden. He leads the Machine Learning and Decision Making Lab and is affiliated with WASP , CHAIR , and ELLIS . Education : PhD in Computer Science (2014) from ETH Zurich under Prof. Dr. Joachim M. Buhmann Prior Roles : Staff Research Scientist at Naver Labs Europe (2014-2018) Research spans Interactive Machine Learning , Sequential Decision Making , Federated Learning , Efficient Deep Learning , and Graph-Based Learning . Key application areas include Transport , Autonomous Systems , Energy , Drug Discovery , and Computational Biology . Selected Publications (2020-2025) demonstrate expertise in Reinforcement Learning for drug design, Minimax Distance Measures for clustering, and Graph Neural Networks for trajectory analysis. Current work focuses on Combinatorial Bandits and Human-in-the-loop AI . Teaching includes graduate courses like Advanced Topics in Machine Learning (DAT441/DIT41), Algorithms for Machine Learning (TDA233/DIT382), and PhD-level Advanced Reinforcement Learning . He has also taught Statistical Methods for Data Science and Theoretical Foundations of ML . Patents include systems for Autonomous Vehicle Motion Control , K-NN Search via Minimax Distances , and Trip Prediction Algorithms . Collaborative projects involve Nature Communications (2022) and multiple ICML / CVPR publications.

• Semiconductor Physics
• Microwave Engineering
• Cryogenic Electronics
• +3 more

Niklas Rorsman is a Research Professor at the Microwave Electronics group, part of the Department of Microtechnology and Nanoscience at Chalmers University of Technology . His work focuses on advanced semiconductor devices, particularly gallium nitride (GaN) and silicon carbide (SiC) high-electron-mobility transistors (HEMTs) for microwave and cryogenic applications. Expertise : Semiconductor device physics, microwave electronics, cryogenic transistor characterization Key Technologies : GaN HEMTs, SiC MESFETs, graphene FETs Rorsman's research investigates trapping effects, thermal management, and material optimization in GaN/SiC devices. Recent studies explore field plates for cryogenic stability, recessed ohmic contacts, and high-κ dielectric interfaces. His publications demonstrate a focus on improving device linearity, noise performance, and reliability through structural and process innovations. Selected trends in his work include: Cryogenic GaN HEMTs with superconducting Nb gates Buffer-free AlGaN/GaN heterostructures for high breakdown voltage Graphene integration for millimeter-wave communication systems Advanced SiNx passivation and gate stack engineering Contact: niklas.rorsman@chalmers.se

• Building Physics
• Numerical Modeling
• Heat and Mass Transfer
• +6 more

Angela Sasic Kalagasidis is a Professor and Department Head at Chalmers University of Technology , leading the Building Physics research group. She serves as a board member of the Moisture Center at Lund University of Technology , contributing to interdisciplinary research in building science. Building Physics Heat and Mass Transfer Energy Efficiency Moisture Safety Indoor VOC Emissions Climate Change Adaptation Her recent publications focus on aerogel-based materials for insulation, urban heat island mitigation , and thermal energy storage systems . Key methodologies include CFD simulations , field testing , and life cycle assessment frameworks . Research trends show emphasis on: Advanced computational tools for hygrothermal analysis Integration of phase change materials in building systems Climate resilience in building envelopes Optimization of ventilation and moisture control

• Process Technology
• Device Design
• Silicon Carbide (SiC) Electronics
• +3 more

Carl-Mikael Zetterling is a Professor and Head of Department at Kungliga Tekniska Högskolan (KTH) in Stockholm, Sweden, affiliated with the School of Electrical Engineering and Computer Science (ICT) and the Electronics and Embedded Systems department. His research focuses on process technology and device design for high-temperature, high-power silicon carbide (SiC) electronics, expanding into SiC-based analog and integrated circuits. He has authored over 300 publications, including books on SiC process technology and plagiarism prevention. Dr. Zetterling has held leadership roles such as Vice Dean of the School of ICT (2013–2017) and teacher representative on KTH's faculty board. He has collaborated internationally at Stanford University, Kyoto University, and Kyoto Institute of Technology. His work addresses applications in extreme environments, including Venus exploration and fusion reactor monitoring, with a focus on radiation tolerance and thermal resilience. The 15 most recent publications highlight trends in wide bandgap semiconductors, gamma irradiation effects on SiC devices, and high-temperature integrated circuits. His articles span structural health monitoring with machine learning, novel SiC diode designs, and radiation-hardened electronics. Key contributions include advancements in self-aligned contacts, trench MOSFETs, and compact modeling for extreme conditions. While no formal awards are listed, his roles in technical program committees (TMS Electronic Materials Conference, IEEE SISC Conference) and editorial work demonstrate significant academic service. He teaches courses ranging from digital design to high-temperature electronics, overseeing degree projects in embedded systems, communication, and nanotechnology.

Erik PrytzView profile

Academic

• Human Factors
• Emergency Response Systems
• Stress Management
• +3 more

Erik Prytz is a Senior Associate Professor in Cognitive Science at the Department of Computer and Information Science (IDA) at Linköping University. His research focuses on applying human factors principles to improve safety-critical systems, particularly in emergency response domains such as first aid, disaster medicine, and prehospital care. He holds a PhD in Human Factors Psychology and has served in roles including Director of the Forum Securitatis graduate school and Program Chair for the Cognitive Science BSc program. Education: PhD in Human Factors Psychology (Old Dominion University, 2014), MSc in Cognitive Science (LiU, 2010). Research Interests: Simulation-based training, stress and mental workload, emergency responder teamwork, and human-system interaction in crisis scenarios. His work emphasizes interdisciplinary collaboration, combining cognitive science, computer science, and medicine to enhance emergency response systems. Recent projects explore driver behavior toward emergency vehicles, ad-hoc responder group dynamics, and optimal placement of bleeding control kits in public spaces. He contributes to initiatives like the Center for Advanced Research in Emergency Response (CARER) and the Forum Securitatis graduate school. Erik’s teaching includes courses on human factors, distributed cognition, and emergency response systems. He actively participates in curriculum development and quality assurance committees within the Faculty of Arts and Sciences.

Ahmed HemaniView profile

Professor

• Computer Engineering
• Embedded Systems
• Hardware Acceleration
• +5 more

Professor Ahmed Hemani is a faculty member at the Division of Electronics and Embedded Systems, KTH Royal Institute of Technology, affiliated with the Digital Futures Faculty. He holds the role of PI for the project 'New Chip Architectures for Industrial Vision' and leads research in reconfigurable computing, memristor-based systems, and hardware acceleration for AI and edge computing. His work bridges theoretical computer science with practical VLSI design and embedded systems development. He actively contributes to cross-disciplinary initiatives at Digital Futures, a joint center with Stockholm University and RISE Research Institutes of Sweden focused on digital innovation. His research emphasizes scalable FPGA/HPC architectures, low-power neuromorphic systems, and optimization techniques for custom silicon solutions. Current projects include a Lego-inspired edge AI framework and memristor-driven MIMO acceleration. Teaching responsibilities span advanced courses in SOC design, digital system verification, and embedded systems. He supervises advanced-level degree projects across computer engineering and ICT innovation specializations, emphasizing hands-on hardware-software co-design methodologies. Recent publications highlight innovations in memristor applications, FPGA-based acceleration, and reconfigurable architectures for neural networks and bioinformatics. His work addresses challenges in dark silicon utilization, energy-efficient computation, and high-performance embedded systems.

Martin NorgrenView profile

Professor

• Electromagnetic Inverse Problems
• Material Characterization
• Biomedical Imaging
• +3 more

Martin Norgren is a Professor at KTH Royal Institute of Technology, leading the Department of Electromagnetic Fusion Physics. His research focuses on electromagnetic inverse problems, including material characterization, biomedical imaging (e.g., brain current sources), environmental monitoring (e.g., snow and avalanche prediction), and smart grid technologies. He specializes in reconstructing object properties using electromagnetic measurements and has contributed to applications in healthcare, energy systems, and environmental science. His work involves advanced analytical and numerical methods such as mode-matching techniques, perturbation theory, and convex optimization. Notable projects include noncontact current measurement in power grids and transformer diagnostics using microwave radiation. Norgren teaches courses in electromagnetic field theory and electrical engineering design, emphasizing practical applications and interdisciplinary collaboration. Recent research trends highlight advancements in glide/twist symmetry-based metamaterial design, waveguide analysis, and inverse scattering techniques. His studies bridge fundamental physics with applied engineering, addressing challenges in energy infrastructure and medical diagnostics. As a department head, he oversees educational and research programs at KTH, fostering innovation in electromagnetism and fusion physics. His contributions to curriculum development include project-based courses integrating theory and hands-on design.

Anna-Karin TornbergView profile

Professor

• Numerical Analysis
• Fluid Dynamics
• Boundary Integral Methods
• +3 more

Anna-Karin Tornberg is a Professor in Numerical Analysis at the Department of Mathematics, KTH Royal Institute of Technology. She holds positions as Vice Chair of the Department of Mathematics and previously served as Head of the Numerical Analysis division (2011–2023). Her research focuses on numerical methods for PDEs, particularly boundary integral methods for fluid flows involving particles and drops. She is active in the Linne FLOW Centre and Swedish e-Science Research Center (SeRC). Key roles include membership in the Royal Swedish Academy of Engineering Sciences (IVA), Royal Academy of Sciences, and receipt of awards like the Göran Gustafsson Prize (Mathematics, 2014). She has advised numerous PhD students and postdocs, including current supervisees Anna Broms, David Krantz, and Emanuel Ström. Her work spans theoretical, computational, and applied fluid dynamics with emphasis on microfluidics and high-accuracy numerical techniques. Education includes a PhD in Numerical Analysis from KTH (2000) followed by postdoctoral positions at NYU’s Courant Institute. Promoted to Full Professor at KTH in 2012. Service roles include membership in KTH’s University Board, Faculty Council, and editorial roles at Advances in Computational Mathematics and BIT Numerical Mathematics . Active in international conferences, delivering plenary/invited lectures at ICIAM, ECM, and ICM. Research group projects include development of fast numerical methods for microfluidics and molecular dynamics simulations. Current openings for PhD candidates in numerical methods for non-elliptic PDEs in time-dependent domains. Her lab collaborates on high-performance computing and fluid-structure interaction problems.

• Biomaterials
• Biomechanics
• Materials Science
• +4 more

Cecilia Persson is a Professor at Uppsala University in the Department of Materials Science and Engineering; Biomedical Engineering. She leads the BioMaterial Systems (BMS) research group within the Division of Biomedical Engineering, focusing on the development of new biomaterials through additive manufacturing. She also directs a Competence Centre in Additive Manufacturing for the Life Sciences and the national Research Technology Platform WISE Additive. 2018, Professor in Materials Science, Uppsala University 2015, Docent (Assoc. Prof.) in Engineering Science with Specialization in Materials Science, Uppsala University 2009, PhD in Mechanical Engineering, University of Leeds 2004, MSc in Materials Engineering, European degree (EEIGM) with triple diploma Persson's research focuses on biomaterials, biomechanics, materials science, and additive manufacturing. Her work takes an integrated approach to solving clinical and sustainability problems, combining materials science, mechanical and biological engineering with new technologies like 3D printing and machine learning. Key research areas include magnesium-based alloys for bone substitutes, titanium-based alloys for permanent implants, and machine learning methods to enhance manufacturing efficiency. Analysis of her recent publications shows a strong emphasis on additive manufacturing of biomaterials, particularly magnesium and titanium alloys. Her work explores microstructure control, mechanical properties optimization, antibacterial properties, and patient-specific implant design. The research demonstrates a clear trajectory toward more sustainable, patient-adapted medical solutions using advanced manufacturing techniques. Persson has received funding from prestigious organizations including the Swedish Research Council (VR), the Knut and Alice Wallenberg Foundation (KAW), the Swedish Foundation for Strategic Research (SSF), Sweden's Innovation Agency (VINNOVA), and the EU. As an academic leader, Persson has served as Section Dean of Engineering (2020-2023), President of the Scandinavian Society of Biomaterials (2019-2023), and Coordinator of EU Innovative Training Network NU-SPINE (2019-2023). Her BioMaterial Systems research group takes an integrated approach to solving clinical and sustainability problems, bridging fundamental scientific mechanisms with high societal relevance.

Franziska KlüglView profile

Professor

• Multi-Agent Systems
• Agent-Based Simulation
• Artificial Intelligence
• +4 more

Franziska Klügl is a Professor in Computer Science at Örebro University's Faculty of Business, Science and Engineering, affiliated with the Center for Applied Autonomous Sensor Systems (AASS). She currently leads the KKS-funded TeamRob project on Human-Robot Teamwork and serves as Deputy Dean of the faculty since January 2023, chairing the academic appointment committee. Previously, she headed the Computer Science department (2020-2022) and served on the faculty board (2019-2022). Her research focuses on: Multi-agent systems : Development of languages, processes, and tools for agent-based simulation Interdisciplinary applications : Transportation, economics, epidemics, production, and mining simulations Simulation engineering : Integrating AI, machine learning, and formal methods to create accessible modeling tools for domain experts She created SeSAm , a visual programming tool for agent-based simulation that enables rapid prototyping of complex models. Analysis of her recent publications reveals three dominant themes: Human-robot collaboration frameworks and intention recognition systems Economic impacts of automation on labor markets and engineering services Advanced simulation methodologies using affordance theory and reinforcement learning She teaches software engineering, multi-agent systems, and agent-based modeling across multiple programs, including the WASP AI&ML PhD course. She leads research groups at the Machine Perception and Interaction Lab and oversees the TeamRob human-robot teamwork project.

Jens CarlssonView profile

Professor

• G protein-coupled receptors (GPCRs)
• Structure-based drug design
• Molecular docking
• +7 more

Jens Carlsson is a Professor at Uppsala University, affiliated with the Department of Cell and Molecular Biology and the Science for Life Laboratory (SciLifeLab) . His research focuses on computational biochemistry , particularly G protein-coupled receptors (GPCRs) , using physics-based modeling to advance structure-based drug design . Academic rank: Full Professor (since 2022) Key methodologies: Molecular dynamics simulations, docking, free energy calculations Research themes: GPCR ligand interactions, virtual chemical space screening, allosteric modulators Recent work (2025) highlights AI-driven discovery of brain disease therapeutics and DNA repair inhibitors , while 2024 projects explore AlphaFold applications in TAAR1 agonist design . His group has received Swedish Research Council grants (3.6M SEK, 6M SEK) and industry collaborations . Scientific awards include the Göran Gustafsson Prize (2016), Excellence Prize in Molecular Design (2022), and Ingvar Carlsson Award (2012). Key students include PhD candidates Mariama Jaiteh and Pierre Matricon , with postdocs like Nicolas Panel and Duy Duc Vo .

• Turbulence Modeling
• Computational Fluid Dynamics (CFD)
• Large Eddy Simulation (LES)
• +7 more

Lars Davidson is a Professor in the Department of Fluid Dynamics at Chalmers University of Technology. His research focuses on numerical simulations of fluid flow and heat transfer, with an emphasis on turbulence modeling for Large Eddy Simulation (LES) and hybrid LES/RANS methods. He has developed computational codes CALC-BFC and CALC-LES based on finite-volume techniques, and recently integrated machine learning to enhance wall functions and turbulence models. Key projects include Hybrid LES/RANS for wall-bounded flows Machine learning applications in fluid dynamics Aeroacoustic noise reduction in automotive and aerospace systems Wind turbine load analysis in forested regions . His publications span 302 articles in journals and conferences, with recent work on Neural networks for turbulence closure Plasma actuators for drag reduction Lattice Boltzmann wall-modeled LES . Collaborations include teams at Volvo, Siemens, and international research groups.

• Offshore Renewable Energy Systems
• Wave Power Farm Modeling
• Extreme Weather Resilience
• +3 more

Malin Göteman is an Associate Professor at the Department of Electrical Engineering, Uppsala University. Her research focuses on offshore renewable energy systems, particularly modeling and optimizing large-scale wave power farms and analyzing their resilience to extreme weather conditions. Deputy Director, Center for Natural Disaster Studies (CNDS), Sweden Specialized in wave energy converter dynamics and hybrid offshore energy systems Collaborates on SPH-based numerical wave-current tanks and CFD validation Research Interests: She investigates wave energy farm interactions, hydrodynamic performance of floating platforms, extreme wave load modeling, and survivability strategies using machine learning. Her work spans renewable energy integration, coastal protection, and power system stability under extreme conditions. Recent Publications: Her 2025 articles address resilience of offshore energy systems to metocean extremes and reduced-order modeling via Bayesian design. Earlier works (2023-2024) cover SPH validations for floating wind-wave systems, neural network survivability approaches, and hybrid energy-water supply solutions. Collaborations: She works with international teams on projects like Lysekil wave energy test sites and DeepCwind floating platforms. Key areas include grid-connected wave parks, multi-fidelity surrogate modeling, and comparative studies on offshore wind dependencies.

• Computer Architecture
• Reconfigurable Computing
• Network-on-Chip (NoC)
• +7 more

Ioannis Sourdis is a Full Professor at the Department of Computer Engineering, Chalmers University of Technology, Sweden. His research focuses on computer architecture, reconfigurable computing, network-on-chip (NoC) design, memory systems, and fault-tolerant embedded systems, with applications in biomedical informatics and hardware security. Current projects include EUMMSS (Efficient Uncore Mechanisms for Multicore Space Systems, funded by the Swedish National Space Board) and eProcessor (European Processor Ecosystem, funded by the European Commission). Past initiatives include the DeSyRe project (on-demand system reliability), ECOSCALE (exascale reconfigurable computing), and SHARCS (secure hardware-software architectures). His work spans NoC router design (e.g., FastTrackNoC, DDRNoC), memory compression (MemSZ, L2C), and biomedical security applications (heartbeat-based protocols). He has published extensively in venues like DATE, ICS, PACT, and IEEE Transactions on Networking. Key research areas: Chiplet-based systems , hybrid memory architectures , FPGA acceleration , and real-time stream aggregation .