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Martin ServinView profile

Associate Professor

• Digital Physics
• Computational Modelling
• Robotics
• +3 more

Martin Servin is an Associate Professor at the Department of Physics, Umeå University, and leads the Digital Physics research group within the UMIT Research Lab. His work focuses on computational modeling and simulation of granular materials, robots, and vehicles, with applications in AI-based control and perception. He holds a doctoral degree from Umeå University (2003) and has pioneered research in real-time physics simulation, particularly in the context of autonomous machinery and off-road robotics. Research Interests : Digital physics, granular materials simulation, autonomous systems, reinforcement learning, and simulation-to-reality transfer. His group develops advanced simulation tools for industries like forestry, mining, and construction. Key Projects : Mistra Digital Forest (2019–2026) AILUR (Digital Twin for AI-controlled Lunar Robotics) XSCAVE (Explainable, Safe Control for Heavy Machinery) Publications emphasize simulation methodologies, AI integration, and real-world validation across robotics, vehicle dynamics, and granular mechanics. Notable contributions include work on wheel loader dynamics, deep reinforcement learning for control systems, and terrain modeling. Awards include the Spin-off award for industry-grade physics in Unreal Engine (2018) , recognizing his role in Algoryx Simulations, a spin-off company commercializing his research. Labs/Teams : UMIT Research Lab, Digital Physics Group, and collaborations with Algoryx Simulations.

Kivanc TatarView profile

Assistant Professor

• Musical Artificial Intelligence
• Machine Learning
• Interactive Arts
• +4 more

Kıvanç Tatar is an Assistant Professor in Interactive AI at Chalmers University of Technology, Sweden. His work bridges Music, Artificial Intelligence, Interactive Arts, and Virtual Reality, creating multimodal AI systems for performances, immersive environments, and generative art. Exhibited globally at events like Ars Electronica (2017, 2020) and Rio Olympics 2016 Founder of the AI in Computational Arts, Music, and Games research group Projects integrate AI with movement computation, VR, and livecoding His research focuses on musical AI , interactive systems , and creative algorithms , with applications in real-time performance, environmental art, and robotics. Recent projects include Koami 2025 (upcoming livecoding), Latent Timbre Synthesis (2021), and Brush of AI (2020 NFT series). Key Collaborations : A.I.D (Istanbul), Gold Saucer (Vancouver) Exhibition Highlights : CHI 2018, Mutek Montreal 2018, Contemporary Istanbul PlugIn 2019

• Automation Systems
• Control Engineering
• Robotics
• +5 more

Petter Falkman is an Associate Professor in Systems and Control Engineering at Chalmers University of Technology, where he leads research in the Automation research group. With 68 publications spanning over two decades, his work bridges theoretical control systems with practical industrial applications, particularly in manufacturing and robotics. His research has been supported by major funding bodies including VINNOVA and European Commission projects. Falkman's research primarily focuses on intelligent automation systems, with key contributions in sequence planning, virtual commissioning, and human-robot interaction. His work integrates formal methods with practical industrial applications, developing frameworks like the Sequence Planner for control of intelligent automation systems. His recent publications demonstrate a strong emphasis on data-driven approaches, digital twin technologies, and the application of virtual reality for industrial applications. The research shows a clear trajectory toward increasingly sophisticated integration of human factors with automation systems, particularly through eye tracking and movement prediction technologies. Falkman has led or participated in 10 major research projects from 2011-2025, including CLOUDS (2022-2025) on circular solutions for sustainable production systems, UNICORN (2017-2021) on robotic refuse handling, and several VINNOVA-funded projects on virtual preparation and industrial automation. His collaborative network includes researchers across Chalmers and industry partners like Volvo Group, demonstrating strong industry-academia connections. Falkman has established himself as a key contributor to the development of frameworks for intelligent automation, with particular expertise in translating theoretical control concepts into practical industrial applications. His work on the Sequence Planner framework represents a significant contribution to the field, enabling more efficient preparation and commissioning of automation systems.

• Experimental Fluid Dynamics
• Turbomachinery Aerodynamics
• Bearing Lubrication
• +5 more

Valery Chernoray is a Research Professor at the Division of Fluid Dynamics, Chalmers University of Technology. Since 1996, he has specialized in experimental fluid dynamics with extensive expertise in modern flow analysis and measurement techniques. He currently leads the Chalmers Laboratory of Fluid and Thermal Science, a university-wide research infrastructure facility that provides equal access to flow, temperature, and motion measurement capabilities for researchers across all engineering disciplines at Chalmers. Professor Chernoray's research encompasses several key areas in fluid dynamics: Experimental validation of computational models using Particle Image Velocimetry (PIV) Turbomachinery aerodynamics, particularly turbine rear structures and outlet guide vanes Bearing lubrication systems and multiphase flow in mechanical components Active flow control applications for automotive and marine systems Wind engineering for urban and marine environments Heat transfer analysis in complex engineering systems His recent publications (2022-2024) reveal a strong emphasis on experimental validation of computational models, with particular focus on lubrication systems in bearings and gearboxes, turbine aerodynamics, and active flow control. His work consistently bridges theoretical fluid dynamics with practical engineering applications, demonstrating expertise in both fundamental research and industrial problem-solving. As head of the Chalmers Laboratory of Fluid and Thermal Science, Professor Chernoray oversees comprehensive experimental facilities supporting research across multiple engineering disciplines. The laboratory provides critical infrastructure for experimental work in air, water, and solid object measurements, serving as a hub for interdisciplinary collaboration at Chalmers University.

• Critical Algorithm Studies
• Digital Cultures
• Platform Studies
• +5 more

Tanja Wiehn is an Assistant Professor in Digital Cultures at the Department of Arts and Cultural Sciences, Lund University. Her research bridges critical algorithm studies , digital culture , and platform studies , with a focus on gendered, racial, and class-based dimensions of algorithmic systems. She teaches in the bachelor’s program in Digital Cultures and the ALM master’s program. Education : PhD in Digital Cultures (2021) from the University of Copenhagen. Her work interrogates the synthetic turn in AI data production , addressing socio-political challenges and aesthetic expressions. Current projects include studying synthetic data’s role in privacy preservation and its cultural implications. Recent publications explore themes like datafication of homes , privacy politics , and machine vision aesthetics . She collaborates internationally on initiatives like the Follow Me project (Danish Independent Research Fund) and Digital Culture Research Cluster .

Alice HaynesView profile

Researcher

• Human-Computer Interaction
• Soft Robotics
• E-Textiles
• +6 more

Alice Haynes is a Digital Futures Postdoctoral Fellow at KTH Royal Institute of Technology, working on the Felt Connections project under the Division of Media Technology and Interaction Design . She collaborates with Prof. Kristina Höök and Associate Prof. Iolanda Leite to create shape-changing textile interfaces that foster meaningful bodily interactions for children and adults. Education PhD in Engineering Mathematics, University of Bristol (2022) Specialization in Soft Robotics and Haptic Interfaces Her research blends soft robotics, e-textiles, and soma design to develop tactile technologies that prioritize bodily engagement over traditional visual/auditory interfaces. Current work explores: first-person design for scoliosis, symmetry-asymmetry dynamics in bodily interactions, and soma-driven methods that emphasize felt experiences. Key article trends include shape-changing textiles (SMA-actuated smocking, machine embroidery), emotional/therapeutic applications (anxiety relief, social touch), and multisensory integration (audio-tactile mappings, biosignal interaction). Scientific Contributions Recipient of Digital Futures Postdoctoral Fellowship Co-design methodologies for child-centered technology Material-driven evaluation frameworks for e-textiles Embodied interaction paradigms through haptic cushions Alice teaches Human-Computer Interaction Research Seminars (DH2632) and Media Technology and Interaction Design (DM2601) , while actively seeking Master's students for collaborative thesis work.

Marjan FirouzniaView profile

Researcher

• Medical Imaging
• Machine Learning
• Deep Learning
• +3 more

Marjan Firouznia is a Principal Research Engineer at Linköping University , affiliated with the Division of Diagnostics and Specialist Medicine (DISP) under the Faculty of Medicine and Health Sciences . With a PhD in Electrical Engineering from Amirkabir University of Technology and postdoctoral experience at institutions like Case Western Reserve University, she specializes in advancing machine learning models for precise segmentation of cardiac structures including the left atrium , epicardial fat , and fibrosis using CT and MRI scans. Her work aims to improve diagnostic accuracy and treatment planning in cardiovascular care. Marjan's research focuses on medical imaging , deep learning , and computational anatomy , with recent publications on FractalRG , FK-means , and Poincare-guided UNet for cardiac structure segmentation. Her academic contributions span 15 recent publications , emphasizing fractal geometry , chaos theory , and optimization algorithms in biomedical applications. She actively develops open-source datasets and tools, such as the FK-means codebase , to support reproducibility in medical AI research.

• Digital Humanities
• Text Mining
• Artificial Intelligence in Education
• +3 more

Dr. Ahmed Taiye Mohammed holds a Postdoctoral research fellowship at Linnaeus University's Department of Cultural Sciences, Faculty of Arts and Humanities in Växjö, Sweden. He earned his Master's and PhD from Northern University of Malaysia (UUM) with a thesis on text anomaly detection. His research focuses on Digital Humanities (DH), AI applications in education, and computational thinking for non-engineers. He teaches courses like Digital Humanities Research Methods, Programming for DH, and AI in Healthcare. Key research projects include InKuiS (innovative cultural entrepreneurship) and AI for ISP (supporting academic writing via ChatGPT). He collaborates with Linnaeus University Centre for Data Intensive Sciences (DISA) on e-health initiatives. Recent publications explore AI in K-12 education, automated library classification, and text mining for archaeology. His work spans AI ethics, DH methodologies, and interdisciplinary applications of computational tools. Teaching responsibilities include over 10 courses at undergraduate/master's levels, emphasizing practical skills in DH technologies. Active in developing AI-based educational tools like CHAT4ISP-AI and exploring generative AI for academic writing support. Research also involves social media ecosystems, data mining practices, and satellite image classification using SVM techniques.

Dan HedlinView profile

Professor

• Survey methodology
• Official statistics
• Sampling design
• +9 more

Dan Hedlin is a Professor of Statistics at Stockholm University's Department of Statistics, specializing in official statistics production. He holds a PhD in Statistics from the University of Southampton (2003) and maintains an office at Room A4625, Albanovägen 12, Building 4, floor 6. His contact information includes email dan.hedlin@stat.su.se and phone +46 8 16 2975. Hedlin's primary research focuses on survey methodology and official statistics, with expertise in sampling design and estimation, nonresponse issues, analysis of survey data, statistical editing, response burden, reporting delays, experiments embedded in surveys, cut-off sample designs, and opinion polls. His work bridges theoretical statistical methods with practical applications in government and public policy contexts. His publications and media contributions demonstrate a strong emphasis on statistical literacy and proper interpretation of survey data, particularly regarding opinion polls. Hedlin frequently engages with the public through Swedish media, addressing common misinterpretations of statistical data and promoting better understanding of survey methodology among journalists and the general public. Hedlin serves on the Scientific Councils of both the Swedish National Council for Crime Prevention and Transport Analysis, applying his statistical expertise to inform policy decisions. His teaching portfolio includes advanced courses in Machine Learning, Statistics and Data Analysis III, and supervising independent student work.

• Maritime Navigation
• Marine Engineering
• Human Factors in Maritime Systems
• +3 more

Reto Weber is a Lecturer in Technology at Chalmers University of Technology, specializing in Maritime Studies . With a professional background as a sea captain and pilot on the Swedish west coast, he brings practical maritime expertise to his academic work in bridge simulators and e-navigation systems. Education : Sea Captain's Degree, Master's from World Maritime University (Switzerland, England, Sweden) Affiliations : Chalmers University, Lighthouse - Swedish Maritime Competence Center, Swedish Transport Administration (Trafikverket) His research focuses on maritime navigation systems , particularly examining human factors in automated environments. Key areas include: Algorithmic decision support in maritime traffic Collision avoidance mechanisms Impact of automation on vessel traffic services Development of web-based simulation tools Route exchange protocols and e-navigation solutions Remote ship monitoring ergonomics Reto's publications reveal trends in SMART ship technologies and Lighthouse projects , emphasizing the integration of artificial intelligence with traditional maritime practices. His work spans simulation-based training tools, COLREG compliance, and physics-informed machine learning architectures for wind propulsion optimization. As an examiner for courses like MManeuvering and Navigation in Confined Waters and Bridge Service , he bridges academic research with practical maritime education through Chalmers' Full Mission Bridge Simulator . Collaborations with institutions like Lighthouse and Trafikverket demonstrate his commitment to advancing maritime safety and efficiency through technology.

Chun-Biu LiView profile

Associate Professor

• Computational Mathematics
• Statistical and Computational Methods in Biophysical Systems
• Information Theory
• +4 more

Chun-Biu Li is an Associate Professor at the Department of Mathematics , Stockholm University , specializing in computational mathematics and statistical physics of biophysical systems. His research bridges information theory, machine learning, and nonequilibrium statistical mechanics to understand complex biological processes. Education: PhD in mathematical & statistical physics from the University of Texas at Austin (supervised by Ilya Prigogine), M.S. in mathematical physics from the University of Utah. Academic Experience: Associate Professor (2016–present) at Stockholm University, Associate Professor (2008–2016) at Hokkaido University, and JST/CREST Researcher (2005–2008) at Kobe University. Research Interests focus on data-driven statistical analyses, nonequilibrium biophysical systems, AI explainability, and fluctuation theorems. His work applies these methods to plant morphogenesis, molecular motor dynamics, and machine learning applications in life sciences. Teaching includes advanced courses on deep learning, reinforcement learning, and statistical methods for life science applications. His Supervision has guided over 30 students in topics ranging from protein mutation modeling to causal inference algorithms. Scientific Awards: Professional Development Award, University of Texas at Austin (2003) Summer Research Fellowship, University of Texas at Austin (2001) National Dean's List for Outstanding College Students (1997) Publications (110+) highlight his contributions to plant morphogenesis, single-molecule analysis, and statistical methods. Recent works examine DNA barcode clustering, rotary motor protein dynamics, and shape-aware data visualization techniques.

• Cyber Situational Awareness
• Simulator Training
• Live Virtual Constructive
• +3 more

Henrik Artman is a Professor at KTH Royal Institute of Technology, affiliated with the Media Technology and Interaction Design (MTM) school. His research focuses on Cyber Situational Awareness , Simulator Training , Live Virtual Constructive (LVC) systems, and intersections with Sustainability and Energy Supply . He serves as Deputy Head of School and teaches courses such as Advanced Individual Course in Human-Computer Interaction and Computer Game Design . Research Interests include: Human-Computer Interaction Cybersecurity and situational awareness LVC military training systems Sustainability in digital design Energy infrastructure resilience Key Contributions involve analyzing LVC training value for air combat, cyber threat response frameworks, and simulator mission design. His work bridges military training, cybersecurity, and interaction design, with a focus on real-world applications.

Luis Velez QuinteroView profile

Assistant Professor

• Data Science
• Extended Reality (XR)
• Machine Learning
• +4 more

Luis Velez Quintero is an Assistant Professor at Stockholm University within the Department of Computer and Systems Sciences (DSV) . He is affiliated with the Data Science Research Group and the Stockholm Technology & Interaction Research (STIR) group, focusing on Human–Computer Interaction. His research spans adaptive immersive systems, affective computing, and physiological signal analysis in extended reality (XR) environments. Education & Background : Holds a PhD in Computer and Systems Sciences from Stockholm University (2023), MSc in Health Informatics from Karolinska Institutet (2019), and BSc in Electronics Engineering from the National University of Colombia (2015). He has led the startup PortalSense since 2018, developing VR solutions for real estate visualization. Research Interests : Combines data science and ML with XR technologies to create context-aware systems for healthcare, education, and professional training. Key themes include: Adaptive VR/AR systems using real-time physiological and behavioral signals Biosignal integration for personalized user experiences Immersive technologies for cognitive assessment and skill development Publications : Over 20 peer-reviewed articles, including work on affective databases (AVDOS-VR), biosignal frameworks (Excite-O-Meter), and XR applications in cybersecurity education. Recent efforts explore third-person locomotion in VR and early-stage Alzheimer’s detection via spatial navigation tasks. Awards & Grants : Wallenberg Foundation Grant (2023-2025): Analyzing non-verbal communication in psychotherapy Swedish Institute Scholarship (2017-2019): Fully funded Master’s and PhD studies Seed funding for PortalSense from Fondo Emprender SENA Colombia (2022-2023) Advising & Projects : Lead researcher in projects like AVDOS-VR and CS:NO . Co-designed the Excite-O-Meter open-source plugin for real-time physiological analysis in VR. Active in industry collaborations for scalable health interventions and immersive training systems. Labs & Teams : Collaborates with multidisciplinary teams at STIR and DSV, advancing human-centered AI and adaptive XR technologies.

• Control Engineering
• Telecommunications
• Cloud Computing
• +3 more

Johan Eker is a Professor at the Department of Automatic Control at Lund University and an Adjunct Professor at ELLIIT: the Linköping-Lund initiative on IT and mobile communication . He is also a member of the LTH Profile Area: AI and Digitalization and LU Profile Area: Natural and Artificial Cognition . His research focuses on control engineering, telecommunications, cloud computing, real-time systems, IoT, and anomaly detection. He actively contributes to UN Sustainable Development Goals through his work. He has received notable awards including the Best paper runner-up award at IEEE CloudNet 2023 , Best Paper Award at RTCSA 2004 , and Best Student Paper Award at RTCSA 1999 . Key projects include: AORTA: Advanced Offloading for Real-Time Applications (2023–2025) ICS: Industrial Cloud Sandbox (2019) AutoDC: Autonomous datacenter for long-term deployment (2018–2021) He has organized workshops such as the Real-Time Cloud Workshop and serves on the advisory board for Internet of Things and People (IoTaP) .

Markus H. FlierlView profile

Associate Professor

• Visual Computing and Communication
• Machine Learning
• Information Theory
• +3 more

Markus H. Flierl is an Associate Professor at the School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology in Stockholm. He holds a PhD in Engineering from Friedrich Alexander University (2003). His career includes senior research roles at École Polytechnique Fédérale de Lausanne (2003-2005), leadership of the Max Planck Center for Visual Computing and Communication (2005-2008), and a Visiting Assistant Professorship at Stanford University (2000-2002). He has served as Program Director of the EIT Digital Master School’s 'Visual Computing and Communication' program and as Associate Editor for the IEEE Transactions on Circuits and Systems for Video Technology. Education: PhD in Engineering, Friedrich Alexander University, 2003 Studies at Friedrich Alexander University (1999-2002), EPF Lausanne (2003-2005), and Stanford University (2005-2008) Research Interests: Focused on visual computing, machine learning, and information theory. Key areas include distributed coding of dynamic scenes, multiview video coding, motion-compensated transforms, and applications in video compression and multimedia systems. His work explores efficient signal processing techniques for video and 3D visual search, with recent contributions in drone-based environmental monitoring and adversarial training methods. Awards: SPIE VCIP Young Investigator Award (2007) Teaching & Grants: Teaches courses on image/video processing, information theory, and multimedia systems. His research is supported by Ericsson, the Swedish Research Council, the European Commission, and KTH’s Digitalization Platform. He advises PhD and master’s students in visual computing and communication. Labs & Teams: Leads the Visual Computing and Communication research group at KTH, collaborating with industry partners like Ericsson and Qamcom. Former members include researchers now at Tobii AB and the University of Iceland.