Find Academic Supervisors

• Biometrics
• Soft-Biometrics
• Mobile Biometrics
• +7 more

Fernando Alonso Fernandez is a Professor at the School of Information Technology, Halmstad University, Sweden , with a permanent position since 2017 and a full professorship since 2025. He also serves as an External Collaborator at the University of the Balearic Islands, Spain since 2019. Research Interests : Biometrics (face, iris, periocular, fingerprint analysis), Soft-Biometrics, Mobile Biometrics, Forensic Analysis, Privacy and Security, with foundational expertise in Artificial Intelligence, Signal/Image Processing, Computer Vision . His work spans EU projects like Horizon PopEye (3.2M€) and national grants totaling over 9.4MSEK from the Swedish Research Council and Innovation Agency. 2025: Horizon Europe PopEye (3.2M€) - Biometrics on-the-move for border control 2022: Swedish Innovation Agency Grant (2.6MSEK) - AI-Powered Crime Scene Analysis 2022: Swedish Research Council Grant (3.6MSEK) - Facial Analysis in the Era of Biometric Masks Awards & Editorial Roles : Distinguished Lecturer (IEEE Biometrics Council 2022-2024), Associate Editor for IEEE Transactions on Information Forensics and Security , Pattern Recognition Letters , and IEEE Biometrics Council Newsletter . Co-chaired ICB2016 and EAB-RPC 2024 Round Table on Generative AI. Education : MSc/PhD in Telecommunications Engineering from Universidad Politécnica de Madrid, Spain (2003/2008). Postdoc at Halmstad University with Marie Curie IEF and Swedish Research Council Fellowship (2010-2017). Publications : Over 140 international papers with h-index 43 (Google Scholar 2025). Recent work explores adversarial attacks in de-identification, CNN pruning for mobile face recognition, and nano-drones for crime scene analysis.

Andreas ArchentiView profile

Professor

• Precision Engineering
• Metrology
• Industrial Analytics
• +7 more

Professor Andreas Archenti is a Chair Professor in Industrial Dependability at KTH Royal Institute of Technology , focusing on Precision Engineering, Metrology, and Analytics. He serves as the Director of the Center for Design and Management of Manufacturing Systems (DMMS) and teaches courses like Advanced Manufacturing Equipment and Industrial Analytics. Education: PhD in Machine and Process Technology (2011), MSc in Mechanical Engineering (2007) Research Interests: Precision manufacturing, robotics for biomedical applications, integrated metrology, and machine tool dynamics Collaborations: University of Tokyo on robotics for scientific exploration Recent Publications highlight data-driven surface quality prediction, compliance compensation in robotics, bearing fault diagnosis, and machine tool calibration. His work spans aerospace to micro/nano fabrication, emphasizing accuracy from nanometers to large-scale systems. Key Contributions include methodologies for machine tool error compensation, dynamic interaction modeling, and transfer learning applications in manufacturing. He has authored chapters in Springer publications and holds a patent for machine parameter determination.

• Computer Vision
• Machine Learning
• Medical Image Analysis
• +4 more

Fredrik Kahl is a Professor at Chalmers University of Technology, leading the Computer Vision Group under the Department of Signal Processing and Medical Technology. His research spans Computer Vision , Machine Learning , and Medical Image Analysis , with a focus on geometric deep learning and 3D reconstruction. University: Chalmers University of Technology Department: Signal Processing and Medical Technology Email: fredrik.kahl@chalmers.se His work addresses rotation equivariance , out-of-distribution detection , and privacy-preserving representations . Recent publications explore Gaussian splatting for 3D edge mapping, semi-supervised learning frameworks, and symmetry encoding in ReLU networks. Projects include collaborations with institutions like Wallenberg AI, Autonomous Systems and Software Program and grants from VINNOVA and Vetenskapsrådet (VR) .

• Bioinformatics
• Comparative Genomics
• Stochastic Models
• +4 more

Marina Axelson-Fisk is a Professor in Mathematical Statistics at Chalmers University of Technology, working within the Department of Applied Mathematics and Statistics in the School of Engineering. She is an active researcher with publications spanning from 1998 to 2023, demonstrating sustained scholarly contribution to her field. Her primary research focus lies in bioinformatics, with particular expertise in stochastic models and algorithms for comparative genomics and cross-species gene finding. She has made significant contributions to the field through her work with the Mouse and Rat Sequencing Consortia, where she was involved in the initial comparative analyses of human, mouse and rat genomes. She is also an associate member of the Linnaeus Centre for Marine Evolutionary Biology (CeMEB), contributing bioinformatics expertise to the analysis of newly sequenced Swedish coastal organisms. Analysis of her 15 most recent publications reveals a consistent research trajectory at the intersection of mathematical statistics and biological applications. Her work demonstrates expertise in developing and applying statistical models to genomic data, with particular emphasis on gene prediction algorithms, comparative genomic analysis, and the application of hidden Markov models to biological sequence analysis. Her research spans both theoretical statistical development and practical biological applications. She has received research funding from the Swedish Research Council (VR) for projects including 'Statistical Significance of Biological Sequences' (2012-2015) and 'Next Generation Comparative Genomics' (2011-2013), indicating sustained recognition of her research contributions by national funding agencies.

Igor ZozoulenkoView profile

Professor

• Condensed Matter Physics
• Organic Electronics
• Materials Science
• +3 more

Prof. Igor Zozoulenko is a Professor and Head of Unit at the Department of Science and Technology (ITN) at Linköping University, leading the Theory and Modelling group within the Laboratory of Organic Electronics (LOE). He holds a Ph.D. in theoretical physics from the National Academy of Sciences of Ukraine and has extensive postdoctoral experience at institutions in Norway and Sweden. His research focuses on electronic and transport properties of low-dimensional semiconductors, conducting polymers, and wood-based materials, with applications in organic bioelectronics and photonics. He has pioneered studies on cellulose-based supercapacitors, such as the plant-based energy storage system in roses. Prof. Zozoulenko teaches undergraduate and Ph.D. courses at Linköping University, earning nominations for the prestigious Gyllene Moroten award in 2005 and 2028. He serves as vice-director of the Wallenberg Wood Science Center Academy, fostering industry-academia collaboration. His research spans theoretical modeling of organic electronics, redox electrochemistry in polymers, and multiscale simulations of electronic transport. Key research themes include the electronic structure of conducting polymers, ion diffusion in cellulose composites, and photonics in bio-inspired materials. He has secured Horizon 2020 funding for doctoral students exploring waste heat energy, perovskites, and computer graphics. His lab’s work has redefined understanding of PEDOT polymer behavior and pioneered transparent wood photonics.

Martin LindView profile

Assistant Professor

• Mathematical Analysis
• Number Theory
• Discrepancy Theory
• +4 more

Martin Lind is an Assistant Professor of Mathematical Analysis at Karlstad University. His research focuses on advanced topics in mathematical analysis, including discrepancy theory, functions of bounded variation, approximation theory, and multiscale systems. He holds a PhD from Karlstad University (2013) and completed a post-doctoral fellowship at the University of South Carolina (2014-2015). Education: PhD in Mathematics, Karlstad University, 2013 His work bridges pure and applied mathematics, addressing problems in number theory, functional analysis, and numerical methods. Key research themes include: Discrepancy estimates for pseudorandom sequences Properties of functions with bounded variation (p-variation, Lambda-variation) Nonlinear approximation methods using splines Analysis of multiscale elliptic-parabolic systems His recent publications (2020-2024) emphasize number-theoretic aspects of sequences and their applications in quasi-Monte Carlo methods. He collaborates actively on applied projects like pollution reduction modeling with photocatalytic materials. Notable contributions include: Developing variational characterizations of Sobolev spaces Establishing convergence rates for semidiscrete Galerkin schemes Exploring Fubini-type properties in multivariate analysis

John Sören PetterssonView profile

Professor

• Human-Computer Interaction (HCI)
• Usability Engineering
• Privacy-Enhancing Technologies
• +6 more

John Sören Pettersson is a Professor of Information Systems Research at Karlstad University, Sweden. He leads research in Human-Computer Interaction (HCI), with a focus on usability methodologies, privacy-enhancing technologies, and crisis management training systems. As former Dean of the Faculty of Economics, Communication and IT (2009-2012) and Director of the HumanIT Research Center (2000-2006), he has held significant academic leadership roles. His research spans multiple areas including: 1) Crisis Management Training via digital tools (e.g., CriseIT Interreg projects), 2) Mobile Technology for Development (M4D) through conferences like M4D 2022 in Rwanda, and 3) Usable privacy in cloud computing (e.g., CREDENTIAL EU projects). He co-developed Ozlab, a non-programming prototyping system, and its web-based successor. Teaching responsibilities include courses in HCI, Information Systems, and interdisciplinary programs like Rules-as-Code applications and AI in Law (starting 2024). He supervises students at all academic levels and collaborates with organizations including the Swedish Tax Agency and local game developers through The Great Journey partnership. Recent projects include the INCREDILAB initiative (2024-2026) addressing climate resilience education and digital transformation, plus pilot studies on generative AI in legal applications. His work bridges technical innovation with societal challenges, emphasizing user-centered design principles across domains.

Olov AnderssonView profile

Assistant Professor

• Autonomous Systems
• Robotics
• Artificial Intelligence
• +5 more

Olov Andersson is an Assistant Professor and WASP Fellow in AI for Autonomous Systems at KTH Royal Institute of Technology, leading the Division of Robotics, Perception and Learning. His research focuses on Embodied AI for autonomous robots and vehicles, combining advancements in Vision-Language Models (VLM), Large Language Models (LLM), and real-world navigation challenges. Key projects include the DARPA SubT Challenge-winning team CERBERUS and the EU H2020 Heron project for robotic road repair. He supervises multiple PhD students and postdocs, including Timon Homberger, Finn Lukas Busch, and Jesper Eriksson. Research interests emphasize full-stack autonomy in dynamic environments, including planning, mapping, and navigation. Notable contributions include the OneMap real-time open-vocabulary mapping system and self-supervised scene flow methods like Seflow. He has been recognized for technical leadership in autonomous systems through awards like the WASP Fellowship. Professional activities include co-chairing the 2024 IROS workshop on robot perception in dynamic environments and advising the Swedish Prime Minister’s AI initiative. Teaching roles span multiple graduate courses in machine learning, robotics, and systems engineering at KTH.

Florian T. PokornyView profile

Associate Professor

• Robotics
• Machine Learning
• Artificial Intelligence
• +5 more

Florian T. Pokorny is an Associate Professor in Machine Learning at the Division of Robotics, Perception and Learning (RPL), Department of Electrical Engineering and Computer Science (EECS), KTH Royal Institute of Technology. He coordinates research projects such as the Horizon Europe-funded SoftEnable and the WASP-funded Intelligent Cloud Robotics for Real-Time Manipulation at Scale . His research focuses on data-driven methods for robotic manipulation, including transfer learning, cloud robotics, and caging-based manipulation of rigid and deformable objects. Education: PhD in Mathematics, University of Edinburgh (supervisor: Michael Singer) MSc in Advanced Study in Mathematics (Part III), University of Cambridge BSc in Mathematics, University of Edinburgh Research Interests: His work emphasizes scalable robotic manipulation, leveraging deep learning and geometric/topological methods. Key areas include training data requirements, transfer learning, and cloud robotics paradigms for manipulation at scale. Recent projects explore energy margin analysis, caging-guided morphology optimization, and robust policy learning. Publications: His recent work spans topics like caging-based manipulation, federated learning, and cloud robotics infrastructure. Notable contributions include CageCoOpt (manipulation robustness), CloudGripper (open-source testbed), and RealCraft (zero-shot video editing). Awards & Grants: Funded by WASP, Horizon Europe, and the Knut and Alice Wallenberg Foundation. His group hosts the CloudGripper platform and collaborates on benchmarks like DLO@Scale. Advising & Labs: Supervises multiple PhD students and research engineers. Alumni include Robert Gieselmann (Amazon Robotics), Yiannis Karayiannidis (Chalmers University), and Anastasiia Varava (Postdoc at KTH). Active in organizing workshops like RoDGE (IROS 2025) and ICRA 2025 robotics learning events.

• Robotics
• Computational Geometry
• Topology in Robotics
• +3 more

Anastasiia Varava is an affiliated faculty member and PhD student at KTH Royal Institute of Technology, working within the Division of Robotics, Perception and Learning. Her research focuses on computational geometry and topology applied to robotic manipulation, particularly caging theory and its practical implementations for handling rigid and deformable objects. She collaborates with advisors Florian Pokorny and Danica Kragic on theoretical and applied robotics challenges. Her work integrates robotics with interdisciplinary fields such as topology, machine learning, and computer vision. Key topics include path planning, deformable object manipulation, and geometric algorithms for motion verification. Recent contributions emphasize data-driven approaches for latent space modeling and visual action planning in robotics systems. Varava has authored or co-authored over 30 peer-reviewed articles and conference papers, covering topics from caging-based motion planning to molecular screening algorithms inspired by robotics. Her publications span journals like IEEE Transactions on Robotics and conferences such as IROS and ICRA, reflecting a strong focus on practical robotic systems with theoretical rigor. Her doctoral thesis, Path-Connectivity of the Free Space: Caging and Path Existence (2019), established foundational work on caging and path non-existence in robotics. Current projects involve advancing geometric evaluation techniques for data representations and exploring diffusion models for robotic skill learning.

Stefan EngblomView profile

Professor

• Scientific Computing
• Numerical Methods
• Fast Multipole Methods
• +3 more

Stefan Engblom is a Professor in Scientific Computing at Uppsala University, Department of Information Technology. His research focuses on developing computational methods and software for scientific applications, with particular expertise in numerical methods, fast algorithms, and simulation of complex systems. He is affiliated with the Scientific Computing division within the Information Technology department at Uppsala University. Engblom's research spans several key areas including fast multipole methods for efficient computation of long-range interactions, stochastic simulation of reaction-diffusion processes in complex geometries, computational epidemiology for modeling disease spread, and fluid dynamics simulations. His work combines theoretical development with practical implementation, resulting in several widely used software packages. His publications reveal a consistent focus on developing efficient numerical algorithms that address computational challenges in various scientific domains. The research shows a progression from fundamental algorithm development (fast multipole methods) to applications in biology (reaction-diffusion systems) and public health (epidemic modeling), demonstrating the versatility and applicability of his computational approaches. Engblom maintains active software development through several research codes including SimInf for epidemic modeling, URDME for reaction-diffusion processes, FMM2D/FMM3D for fast multipole methods, and other specialized tools for fluid dynamics and fiber simulations. His stenglib provides general-purpose Matlab libraries used in his research and available to the broader scientific community.

Jesper JacobssonView profile

Associate Professor

• Optoelectronics
• Electronic and Photonic Materials
• Perovskite Solar Cells
• +6 more

Jesper Jacobsson is an Associate Professor (Docent) at Linköping University, affiliated with the Department of Physics, Chemistry and Biology (IFM). His research lies at the intersection of materials science, optoelectronics, and renewable energy technologies, with a strong focus on perovskite solar cells and photovoltaic materials. His primary research interests include optoelectronics , electronic and photonic materials , surface passivation mechanisms , ion diffusion in 2D perovskites , and the integration of artificial intelligence in materials discovery . He investigates fundamental degradation processes and material design principles to enhance solar cell efficiency and stability. The recent publication trends highlight a growing emphasis on computational modeling, AI-assisted hypothesis generation, and performance benchmarking of emerging photovoltaic materials. His collaborative work spans international research groups and addresses both experimental and theoretical challenges in next-generation solar technologies. Scientific Awards: No awards listed in the provided text. Advising and Grants: No formal advisees or grant information is mentioned in the available content. Labs and Research Teams: Jesper Jacobsson is part of the active materials research ecosystem within the Department of Physics, Chemistry and Biology at Linköping University, contributing to advanced studies in photovoltaics and functional materials, likely within a collaborative lab environment focused on sustainable energy solutions.

Rodrigo Caballero AugiView profile

Professor

• Atmospheric Dynamics
• Climate Dynamics
• Arctic Climate
• +5 more

Rodrigo Caballero Augi is Professor of Dynamic Meteorology at Stockholm University's Department of Meteorology (MISU), where he leads research on atmospheric dynamics and climate systems. His work spans from planetary-scale waves to cloud droplet motion, examining how these processes shape past, present, and future climates. He maintains strong affiliations with the Bolin Center for Climate Research and the Swedish e-Science Research Centre. Caballero received his Laurea in Physics (1994) and PhD in Physics (1998) from La Sapienza University in Rome, Italy, under the guidance of Alfonso Sutera. His academic journey continued with postdoctoral positions at the University of Copenhagen and University of Chicago, followed by faculty roles at University College Dublin before joining Stockholm University in 2011. His research focuses on understanding atmospheric dynamics in the context of climate change, with particular emphasis on Arctic climate where warming occurs at more than twice the global average rate. His group investigates circulation systems that co-evolve with ice sheets, mountain ranges, and carbon redistributions between climate system compartments. Using a combination of simple models, general circulation models, observational data analysis, and statistical modeling, his team explores how atmospheric dynamics influences energy and material exchanges across the climate system. Recent publications reveal a strong focus on Arctic climate processes, particularly moist intrusions, cloud feedbacks, and polar amplification mechanisms. His work spans multiple disciplines including atmospheric physics, climate dynamics, and polar meteorology, with significant contributions to understanding storm tracks, cloud albedo asymmetries, and energy transport mechanisms in changing climates. Caballero has mentored numerous PhD students and postdocs who have gone on to successful careers at institutions worldwide, including University of Arizona, Uppsala University, Chalmers University of Technology, and UQAM in Montreal. His research group continues to investigate critical climate questions through projects like Arctic Climate Across Scales, North Atlantic Deep-Water formation, and storm track-cloud feedback relationships.

• Fusion Science
• Plasma-Material Interactions
• Ion Beam Analysis
• +3 more

Per Petersson is a Researcher at the KTH Royal Institute of Technology , affiliated with the Division of Electromagnetic Engineering and Fusion Science . His work focuses on plasma-material interactions , ion beam analysis , and tokamak diagnostics , particularly for fusion reactors like JET and TOMAS. Teaching: Serves as assistant for Algebra and Geometry (IX1303) and as examiner/course responsible for Introduction Course to Fusion Technology (ED2240) . Research: Investigates ion irradiation effects , fuel retention in plasma-facing materials , and RF/ECR plasma production for fusion applications. Recent publications highlight advancements in tokamak diagnostics , material degradation under fusion conditions , and innovations in ion beam analysis for reactor safety. His work supports the development of ITER and DEMO fusion projects through experiments at facilities like JET and TOMAS.

Malcolm FairbrotherView profile

Professor

• Climate policy
• Political trust
• Globalization
• +6 more

Malcolm Fairbrother is a Professor at Uppsala University's Department of Sociology, focusing on climate change, political trust, and globalization. His work bridges sociological theory with practical policy analysis, emphasizing multilevel modeling and comparative survey methodologies. Primary affiliation: Department of Sociology, Uppsala University Research themes: Climate policy, institutional trust, globalization, environmental justice Email: malcolm.fairbrother@uu.se His recent research explores the interplay between social trust and climate policy acceptance, including studies on energy transitions and governance for future generations. Publications analyze institutional frameworks for climate policymaking (UK), regional cooperation (North America), and environmental attitudes across cultures. Key awards include no explicitly mentioned honors. He collaborates on cross-national surveys like the 2020 ISSP environment module and contributes to debates on statistical methods in sociology (e.g., fixed vs. random effects models). His full description includes extensive policy-relevant findings and methodological innovations.