Jens Edlund is a Professor at KTH Royal Institute of Technology's Division of Speech, Music and Hearing. His research focuses on speech technology, dialogue systems, prosody, and evolutionary phonetics. He has contributed to foundational work on speech synthesis, conversational interaction, and multimodal corpora like the D64 corpus. Key projects include the MonAMI Reminder system and analysis of primate vocalizations to understand speech evolution. Edlund has collaborated extensively with global researchers, producing over 150 peer-reviewed works. His work integrates computational methods with linguistic and biological insights, emphasizing human-like dialogue systems and cross-species vocal analysis. Education: Ph.D. in Speech Technology (2011, KTH) Grants: Multiple EU and Swedish Research Council grants for speech technology and interdisciplinary studies Research labs include the KTH Speech, Music and Hearing Lab and collaborations with institutions like Max Planck Institute for Evolutionary Anthropology. Current work explores evolutionary origins of speech biomechanics and AI-driven speech synthesis evaluation.
Danica Kragic is a Professor of Computer Science at the School of Electrical Engineering and Computer Science at the Royal Institute of Technology (KTH) in Stockholm, Sweden. She serves as the Director of the Centre for Autonomous Systems and leads the Robotics, Perception and Learning Lab at KTH. Her research focuses on advancing robotics capabilities through computer vision and machine learning approaches. MSc in Mechanical Engineering from the Technical University of Rijeka, Croatia (1995) PhD in Computer Science from KTH (2001) Professor Kragic's research primarily centers on robotics, computer vision, and machine learning, with particular emphasis on robotic manipulation, grasp planning, and human-robot interaction. Her work bridges theoretical foundations with practical applications, exploring how robots can understand and interact with objects in complex environments. She investigates how visual and tactile sensing can be integrated to improve robotic perception and manipulation capabilities, with applications ranging from industrial automation to assistive robotics. Her recent publications demonstrate a strong focus on advanced grasp planning techniques, tactile sensing for manipulation, and mathematical representations for robotic control. Kragic's research shows increasing integration of machine learning approaches with traditional robotics frameworks, particularly in the areas of grasp synthesis, object recognition, and human-robot collaboration. Her work spans theoretical contributions in mathematical representations of grasps to practical implementations of robotic systems capable of adapting to novel objects and situations. 2007 IEEE Robotics and Automation Society Early Academic Career Award IEEE Fellow ERC Starting Grant (2012) Member of The Royal Swedish Academy of Sciences Member of The Royal Swedish Academy of Engineering Sciences Honorary Doctorate from Lappeenranta University of Technology Professor Kragic's research has been supported by major funding bodies including the EU, Knut and Alice Wallenberg Foundation, Swedish Foundation for Strategic Research, and Swedish Research Council. While specific student names aren't listed in the provided information, her publication record suggests extensive mentorship of PhD students and postdoctoral researchers in robotics and computer vision. Her lab, the Robotics, Perception and Learning Lab, serves as a hub for interdisciplinary research connecting computer science, engineering, and cognitive science perspectives on robotic systems. As Director of the Centre for Autonomous Systems at KTH, Kragic oversees a major research initiative focused on advancing autonomous technologies. Her Robotics, Perception and Learning Lab brings together researchers working on visual perception, machine learning, and robotic manipulation, with particular emphasis on developing systems that can understand and interact with objects in unstructured environments. The lab's work spans theoretical foundations of robotic manipulation to practical implementations of systems capable of learning from experience.
Adam Wickberg is a researcher in the Division of History of Science, Technology and Environment at KTH Royal Institute of Technology in Stockholm. He serves as co-director of the VR Excellence Centre for Anthropocene History and deputy director of the KTH Environmental Humanities Lab . His work critically examines the intersections of digitalization, sustainability , and the Anthropocene , focusing on their social, political, and historical dimensions. He leads the research project The Mediated Planet: Claiming data for environmental SDGs and has held visiting positions at the Max Planck Institute for the History of Science in Berlin. Education : Not explicitly stated His research spans media studies, environmental history, critical data studies , and postcolonial science and technology studies . Key themes include: Digital twins and marine futures AI ethics for climate justice Colonial histories of environmental data Temporal dimensions of Anthropocene governance Environing media as epistemological tools Planetary datafication systems Recent publications explore how data infrastructures shape environmental governance and how historical media practices inform contemporary sustainability challenges. He has contributed to journals like New Media and Society , Nature , and Critical Inquiry , while engaging in public debates through op-eds in Dagens Nyheter and Aftonbladet . Teaching : Courses include Artificial Intelligence and Sustainable Development (AK122V), Environmental History (AK2210), and The Anthropocene (AK126V). Labs/Teams : Leads the Environmental Humanities Lab and collaborates with the WASP-HS Community .
Cyrille Artho is an Associate Professor in the Division of Theoretical Computer Science at KTH Royal Institute of Technology, actively contributing to research in formal methods, software testing, and cybersecurity. His work spans model checking, smart contract security, and concurrent systems verification, with significant contributions to tools like Java Pathfinder and Modbat. PhD from ETH Zurich (2005) with dissertation on multi-threading fault detection Teaches Software Safety and Security, Software Engineering Fundamentals, and supervises degree projects His research focuses on developing formal techniques for safety-critical systems, particularly in blockchain security and distributed applications. Recent work emphasizes smart contract verification, anomaly detection in microservices, and trusted execution environments for secure cloud analytics. The 15 most recent publications reveal a strong trend toward blockchain security (6 articles), formal verification of distributed systems (5), and novel testing methodologies (4), with increasing integration of machine learning for vulnerability detection. As chair of the FTSCS workshop series and contributor to major conferences like ASE and ICST, Artho has significantly shaped the formal methods community. His leadership in organizing workshops demonstrates commitment to advancing safety-critical systems research. Principal investigator for C3.ai DTI Cyber Safety Cage for Networks project Develops Modbat framework for model-based API testing Active in Digital Futures research initiative at KTH
Matteo Magnani is a Professor in the Division of Computing Science at the Department of Information Technology, Uppsala University. He leads the Uppsala University Information Laboratory and is a founding member of the Uppsala University Computational Social Science Lab. His research spans network science, artificial intelligence, data science, and computational social science, with a focus on social data mining and multilayer networks. PhD in Computer Science, University of Bologna, 2006 Graduated with honours in Information Sciences, University of Bologna, 2002 Studies in Computer Science at University of Marne la Vallée and Imperial College London Matteo Magnani's research interests include social network analysis, multilayer and probabilistic networks, community detection, visual analytics, and the application of AI to digital media and climate communication. His work bridges computer science and social sciences, particularly in analyzing online discourse and digital intermediaries. He has contributed significantly to the understanding of network structures, uncertainty in networks, and the ethical dimensions of algorithmic analysis. His recent publications highlight trends in fairness in community detection, visual saliency in network layouts, emotional reactions to climate visuals online, and deep learning applications in social media. Topics frequently involve YouTube, Twitter, and online public debates, using advanced network and machine learning methods. Rotary Prize for best student of the Science Faculty Best Paper Award Funniest Presentation Award Best Poster Award Pedagogical Prize from UTN Distinguished University Teacher (Sweden) Docent title (Sweden) Magnani has supervised numerous students and collaborated widely, particularly with Luca Rossi, Alexandra Segerberg, and Davide Vega. He has secured funding from major sources including VR, H2020, STINT, and MIUR. He leads active research labs focused on information systems and computational social science, fostering interdisciplinary collaboration and innovation in network-based research.
Michael Felsberg is a Professor and Head of Division at the Department of Electrical Engineering (ISY) at Linköping University, leading the Computer Vision Laboratory (CVL). His research focuses on artificial visual systems (AVS), including 3D computer vision, computational imaging, object tracking, and autonomous systems. He emphasizes HVS-inspired approaches to bridge the gap between human and machine vision capabilities. Notable achievements include over 20,000 citations (h-index 47), leadership roles in the Wallenberg AI, Autonomous Systems and Software Program (WASP), and recognition as Sweden’s top AI researcher by Vinnova. His work spans academic contributions, industry collaborations, and interdisciplinary projects like climate science applications of machine learning. Positions : WASP Executive Committee Member, WASP Area Cluster Leader for Machine Learning, and Vice-Head of Department (Electrical Engineering). Education : Extensive academic background in electrical engineering and computer vision (details not explicitly stated). Research trends in his articles reflect advancements in autonomous systems, multimodal AI, and robust vision models. His teams address challenges like object tracking, generative models for 3D simulation, and culturally diverse AI systems. Awards : Tracking Challenge Winner (OpenCV, 2015) Best Paper Awards (ICPR 2016, VISAPP 2021) Vinnova’s Highest-Ranked Swedish AI Researcher (2018) He advises numerous PhD students and oversees grants in WASP-funded initiatives. CVL collaborates on projects like disaster-response robotics and Berzelius supercomputer utilization for AI.
Brinton Seashore-Ludlow is an Associate Professor at the Department of Oncology-Pathology, Karolinska Institute (KI), where he serves as team leader in Olli Kallioniemi's research group and group leader of the biology team at Chemical Biology Consortium Sweden (CBCS), SciLifeLab's national infrastructure. PhD in Biochemistry, KTH Royal Institute of Technology (2012) MSc in Chemical Biology, California Institute of Technology (2007) BA in Biochemistry, Macalester College (2001) His research bridges precision medicine and cancer biology through: Developing ex vivo patient-derived models for drug response prediction Molecular determinants of therapeutic efficacy Integration of high-content imaging with translational studies Focus on ovarian, breast, and pediatric cancers AI-driven analysis of drug sensitivity data Recent articles demonstrate: 3D tumor spheroid platforms for drug testing Epigenetic regulators in neuroblastoma Microfluidics for high-throughput assays Cancer-stroma interactions in treatment resistance Clinical validation of precision diagnostics He co-organizes the Overview Course in Cancer Drug Discovery at KI and leads projects funded by the Swedish Childhood Cancer Foundation.
Jennifer Ryan is a Professor of Numerical Analysis and Division Head of Numerical Analysis, Optimization, and Systems Theory at the Department of Mathematics, KTH Royal Institute of Technology. Her research focuses on designing and developing numerical schemes to extract accuracy from simulations, particularly through superconvergence properties and computational efficiency improvements. She applies these techniques to applications such as imaging, fluid visualization, and plasma dynamics. Education: PhD in Applied Mathematics, Brown University; MS in Mathematics, Courant Institute; BA in Applied Mathematics, Rutgers University. Professional Activities: Member of editorial boards for BIT Numerical Mathematics, ESAIM:M2AN, and Communications on Applied Mathematics and Computation; Steering committee member of AWM's Women in Numerical Analysis and Scientific Computing (WINASc). Her publications emphasize discontinuous Galerkin methods, SIAC filtering, and applications in fluid dynamics. She has served on multiple grant review panels and received awards for diversity and inclusion initiatives. Grants: Principal Investigator for projects funded by the Swedish Research Council, NSF, and US Air Force Office of Scientific Research. Awards: Fellow of UK Higher Education Academy, DAAD Fellowship, and Householder Fellowship.
Ulrich Vogt is a Professor in Applied Physics at Kungliga Tekniska Högskolan (KTH) and leads the X-ray Optics and Nanoimaging group within the Bio-Opto-Nano unit. He serves as Vice-head of the Applied Physics department for undergraduate education. His research focuses on developing advanced X-ray microscopy techniques, particularly at synchrotron facilities like MAX IV’s NanoMAX beamline. He specializes in X-ray optics, nanoimaging, and diffractive optical elements for applications in materials science, biology, and medicine. Key contributions include the design of the NanoMAX beamline, optimization of X-ray zone plates via metal-assisted chemical etching, and advancements in multi-beam ptychography. Vogt has pioneered compact X-ray microscopy systems using laser-plasma sources and liquid-jet targets. His work integrates nanofabrication, computational imaging, and synchrotron instrumentation to achieve sub-100 nm resolution in hard and soft X-ray regimes. Teaching responsibilities include courses on experimental physics, photonics, and X-ray applications. His lab collaborates internationally on projects like the European XFEL, emphasizing high-brightness sources and radiation-resistant optics. Recent innovations include adaptive multi-beam ptychography and stereo X-ray imaging for 3D nanoscale visualization. Research highlights span over 100 peer-reviewed articles, with a focus on coherence characterization, beamline instrumentation, and nanostructured materials. Vogt’s grants include a Röntgen-Ångström Cluster award supporting multi-beam ptychography and cryo-microscopy advancements.
Jim Dowling is a distributed systems researcher at KTH Royal Institute of Technology, focusing on large-scale distributed systems, machine learning, and big data. His work emphasizes improving system dependability, performance, security, and scalability through middleware, peer-to-peer systems, and cloud-native solutions. He leads courses such as Advanced Course in Large Scale Machine Learning and Deep Learning and Scalable Machine Learning and Deep Learning , demonstrating his commitment to education in AI and distributed computing. His research spans topics like feature stores, Kubernetes integration, and AI-driven environmental analytics (e.g., ANIARA project for edge infrastructure automation and ExtremeEarth for Copernicus data analysis). He has contributed to scalable ML pipelines, cloud storage systems (HopsFS-S3), and hyperparameter optimization tools like Maggy. Key projects include the Hopsworks platform for machine learning operations and the development of cloud-native tools for big data analytics. His work bridges theoretical distributed systems research with practical applications in AI, healthcare, and environmental science. He has advised on numerous collaborative initiatives but no formal students are listed. His grants and lab activities are centered around Hopsworks and the ANIARA project, reflecting his focus on scalable, self-managing systems.
Mario Romero is an Associate Professor in Visualization at the Department of Computational Science and Technology (CST), KTH Royal Institute of Technology. He leads the InfraVis national research infrastructure for data visualization and is a Digital Futures Faculty member. His roles include national technical manager of InfraVis, member of the Executive Committee of Digital Futures, and Associate Director for Seminars & Workshops. Education: PhD in Computer Science (Georgia Tech, 2009), MSc in Computer Science (UIUC, 2001), and dual BSc degrees in Industrial Engineering and Construction Engineering (Universidad San Francisco de Quito, 1996). He is a Fulbright Scholar from Ecuador and holds postdoctoral experience at Uppsala University. Research focuses on Human-Computer Interaction, Visualization, and Ubiquitous Computing. Key projects include: TENT: Technology-Enhanced Neurosurgical Training VisBac: Visualizing airborne bacteria in ORs PSP: Platform for Smart People (autism support) SMART: Predictive maintenance in pharmaceuticals Homo Colossus: Energy footprint visualization Awards: Selected for IVA's 100 research2business projects (2021). Co-founded BrailleTouch (blind-friendly keyboard) and Anymaker (3D sketching app). Supervised students in C-Awards-winning projects (e.g., Yue Liu's thesis defense in 2024). Teaching: Responsible for courses like Information Visualization (DH2321) and Advanced Graphics & Interaction (DH2413). Active in organizing conferences (e.g., Eurographics 2020 Education Track Chair).
Sven Bölte is a Professor at Karolinska Institutet where he leads the research group focused on Autism, ADHD and other developmental neurological conditions as part of the Center for Neurodevelopmental Disorders (KIND). His work bridges clinical research, education, and practical implementation of evidence-based approaches for neurodevelopmental conditions. Professor Bölte's research spans multiple domains within neurodevelopmental disorders, with particular emphasis on implementing the International Classification of Functioning, Disability and Health (ICF) Core Sets for autism and ADHD using digital solutions. His group has developed and evaluated social skills training programs (KONTAKT, SKOLKONTAKT, iKONTAKT) for autistic children and adolescents, conducted twin research through the Roots of Autism and ADHD Twin Study in Sweden (RATSS), and advanced diagnostic instruments for autism, ADHD, social cognition, and adaptive behavior. His recent publications reveal a strong focus on translating research into practice, with significant work on strengths-based approaches, social inclusion, neurodiversity-affirmative assessment, and the development of practical tools for clinicians and educators. The research demonstrates increasing attention to adult experiences of autism, cross-cultural validation of interventions, and the integration of digital technology in assessment and intervention. Bölte's group also delivers extensive educational components for professionals through KI-Utbildning (Assignment Education), making it one of the largest providers of training on diagnosis and support for individuals with developmental neurological conditions within Karolinska Institutet. His work frequently addresses policy implications, as evidenced by participation in Swedish parliamentary discussions about autism and ADHD.
Danielle Wilde is a Professor at the Umeå Institute of Design (UMU), where she explores the intersections of design, sustainability, and participatory methodologies . She also holds a professorship at the University of Southern Denmark . Her work spans scales from the microbial to the planetary , focusing on how food practices and Indigenous knowledges can foster Environmental Citizenship and systemic change. Head, Sympoietic Research Collaboratory Arctic Six Chair of Arctic Food Citizenship Research interests include more-than-human design , embodied methodologies , and co-creative practices . She challenges conventional design paradigms by positioning designers as facilitators of relationships rather than product creators. Her methodological development emphasizes participatory research through design , particularly in Arctic contexts and with microbiomes. Current projects include: FlavourFerm (2024-2028): Fermentation-based food innovation Px7 (2024-2027): Experimental design for societal transitions Remaking Gut Relations (2024): Human-microbiome engagement Digesting Data : Data physicalization for environmental awareness Her publications highlight food as a methodological tool , multisensory design , and decolonial approaches to sustainability. She collaborates with interdisciplinary teams across Europe, bridging design, ecology, and policy.
Stefano Markidis is a Professor of Computer Science at KTH Royal Institute of Technology, affiliated with the School of Electrical Engineering and Computer Science and the Digital Futures Faculty. He holds a Ph.D. from the University of Illinois at Urbana-Champaign and an MS from Politecnico di Torino. His research focuses on high-performance computing systems, including supercomputers and quantum computers, with expertise in plasma simulations, quantum algorithms, and scalable computational frameworks. Markidis leads the development of the Neko framework for high-fidelity computational fluid dynamics and the iPIC3D particle-in-cell code for plasma physics. He teaches courses such as Quantum Computing for Computer Scientists, High-Performance Computing, and Applied GPU Programming. His work addresses exascale computing challenges, including optimizing algorithms for GPUs, quantum systems, and distributed architectures. Key research interests include: Parallel Programming Models and HPC Frameworks Quantum Computing Applications in Scientific Simulations Physics-Informed Machine Learning Exascale System Optimization Turbulence Modeling and Plasma Dynamics His publications span over 100 articles in journals like Journal of Computational Physics and Scientific Reports , focusing on topics such as scalable CFD, quantum neural networks, and plasma simulation techniques. He has advised numerous students in these areas. Markidis collaborates with institutions like Los Alamos National Laboratory and RISE Research Institutes of Sweden through the Digital Futures initiative, aiming to solve societal challenges via digital technologies.
Daniel Pettersson is a Professor at University of Gävle specializing in educational science with a particular focus on international knowledge measurements, comparative education, and curriculum studies. His work critically examines the hegemony of comparisons in education, particularly through large-scale assessments like PISA, and explores how these influence educational policy and practice. Professor Pettersson's research spans several interconnected domains within educational science. He investigates how international comparisons shape educational discourse and policy, examining the historical development of assessment practices and their impact on national education systems. His work frequently analyzes the production of educational knowledge through data visualization and quantification, revealing how numbers become authoritative in educational decision-making. A significant portion of his research focuses on Swedish education within international contexts, exploring how global educational trends are adopted, adapted, and contested in national settings. His extensive publication record reveals several key trends in his scholarly work. Over the past two decades, Pettersson has traced the evolution of international large-scale assessments from marginal research tools to central policy instruments. His recent work increasingly examines data visualization techniques in educational research and the historical construction of educational knowledge through quantification. He also explores the intersection of teacher education with international assessment frameworks, revealing tensions between global educational discourses and local teaching practices. Professor Pettersson has made significant contributions to understanding how educational policy is shaped by international comparisons. His research demonstrates how assessment data becomes transformed into policy narratives that influence educational reform. He has documented the historical trajectory of international assessment research, showing how it evolved from marginal academic interest to central policy instrument. His collaborative work with scholars like Sverker Lindblad, Thomas Popkewitz, and Tatiana Mikhaylova has been particularly influential in critically examining the political dimensions of educational measurement. His research activities include extensive work with international research teams, participation in major conferences including the Nordic Education Research Association (NERA) and the International Standing Conference for the History of Education (ISCHE), and contributions to systematic reviews of international comparative research. Professor Pettersson's work bridges historical analysis, policy studies, and critical examination of educational measurement practices, providing valuable insights into how global educational knowledge is produced and circulated.
