Find Academic Supervisors

Lars EngstrandView profile

Professor

• Microbiome Research
• Women's Reproductive Health
• Gastroenterology
• +7 more

Lars Engstrand is a Professor in infection control at Karolinska Institutet, heading the Translational Microbiome Research and Pandemic Preparedness group within the Department of Microbiology, Tumor and Cell Biology. His research spans multiple disciplines with a focus on translational microbiome research and pandemic preparedness. Engstrand's research interests center on understanding the human microbiome's role in health and disease, particularly in women's reproductive health and gastroenterology. His group has established multiple large-scale clinical studies including SweMaMi (Swedish Maternal Microbiome project), BASIC (associations between microbiota and preterm birth), VaMiGyn (Vaginal Microbiota in Gynaecological health), and several others investigating the vaginal microbiome's relationship to pregnancy outcomes, HPV infection, and cervical cancer. His team also conducts significant research on gut microbiome in inflammatory bowel disease and colorectal conditions through projects like PopCol and KOLBIBAKT. Analysis of Engstrand's most recent publications reveals a strong focus on the relationship between microbiome composition and women's health outcomes. His research consistently examines how vaginal, gut, and oral microbiomes influence pregnancy complications, preterm birth, HPV infection, and mental health during pregnancy. The work often employs large cohort studies with comprehensive sampling strategies across multiple body sites and time points, providing robust data for understanding microbiome dynamics in health and disease. Engstrand leads the Microbiome Exploration and Development for Intervention (MEDI) initiative and the National Pandemic Center (NPC) at Karolinska Institutet. The NPC conducted large-scale sequencing during the COVID-19 pandemic and has amassed over 1.5 million samples. His research group includes multiple specialized teams focusing on culturomics, bioinformatics, labcore operations, women's health research, and pandemic preparedness.

Hedvig KjellströmView profile

Professor

• Computer Vision
• Artificial Intelligence
• Human-Computer Interaction
• +6 more

Hedvig Kjellström is a Professor at the Division of Robotics, Perception and Learning within the School of Electrical Engineering and Computer Science at KTH Royal Institute of Technology. She holds significant affiliations with the Swedish e-Science Research Centre and the Max Planck Institute for Intelligent Systems in Germany. Her work spans multiple interdisciplinary domains and she serves as Editor-in-Chief for CVIU and was Program Chair for CVPR 2025. Her research centers on Computer Vision as a sub-field of AI, with three interconnected themes: Computational Aesthetics (exploring aesthetic aspects of human communicative behavior), Communicative Behavior (developing models of how humans and animals perceive and produce non-verbal communication), and Embodied Artificial Intelligence (creating methodologies for robots and autonomous agents to perceive the world through sensors, primarily vision). Her work has significant applications in medical diagnostics, animal welfare, human-robot interaction, and creative arts. Analysis of her recent publications reveals a strong trend toward multimodal AI systems that integrate vision, language, and action understanding. Her research increasingly focuses on animal-centered applications, particularly equine pain detection and behavior analysis, while maintaining strong foundations in human communication modeling, gesture recognition, and 3D reconstruction techniques. The interdisciplinary nature of her work bridges computer science with veterinary medicine, neuroscience, and performing arts. Hedvig Kjellström actively supervises numerous PhD and Master's students across various projects and maintains extensive collaborations with institutions including Karolinska Institutet, Swedish University of Agricultural Sciences, and international partners. Her research is supported by major funding bodies including WASP, VR, and SeRC. She leads or participates in several notable projects including OrchestrAI (communication between conductor and orchestra), ANITA (Animal Translator), MARTHA (3D horse motion analysis), and STING (synthesis and analysis with transducers and invertible neural generators). Her work with ACAI (Animal Centered Artificial Intelligence), which she co-founded and directs, demonstrates her commitment to applying AI for animal welfare.

Cheuk Wai TaiView profile

Researcher

• Structure-Property Relationships
• Functional Materials
• Electron Microscopy
• +6 more

Cheuk Wai Tai is a Senior Staff Researcher at Stockholm University's Department of Environmental and Materials Chemistry since 2009. He manages the transmission electron microscopes and sample preparation equipment at the Electron Microscopy Center and serves as Section Editor for the Journal of Electronic Materials. His work focuses on quantitative structure characterization in functional materials research, particularly within nanoscience and nanotechnology contexts. Education: Ph.D. in Applied Physics, The Hong Kong Polytechnic University, 2004 M.Phil. in Applied Physics, The Hong Kong Polytechnic University, 2001 M.Sc. in Physics, The Chinese University of Hong Kong, 1998 B.Sc. (Hons) in Engineering Physics, The Hong Kong Polytechnic University, 1997 Dip. in Mechanical Engineering (Computer Aided Engineering), Institute of Vocational Education (formerly Haking Wong Technical Institute), Hong Kong, 1992 His research centers on structure-property relationships in functional materials through advanced electron microscopy techniques. Current specializations include Pair Distribution Function (ePDF) & Diffuse Scattering, Energy Materials characterization, and EM sample preparation methodology development. The group maintains strong focus on translating structural data into functional performance metrics for nanomaterials. Recent publications (2013-2019) demonstrate consistent emphasis on electron microscopy applications for energy storage materials (batteries, photocatalysts) and functional ceramics. Key trends include structural disorder analysis in piezoelectrics, development of quantitative TEM methods like SUePDF, and nanoscale characterization of electrocatalyst surface phases. His work bridges materials chemistry with advanced imaging techniques. Scientific recognition includes: Fellow of The Royal Microscopical Society (U.K.) Senior Member of IEEE Marie Curie Fellowship (2007-2009) from European Commission Sir Edward Youde Memorial Fellowship (2003/2004) from Hong Kong S.A.R. Government He teaches Solid State Chemistry (KZ7003) and leads Introduction to Analytical Electron Microscopy (KZ8009), having previously taught Advanced Transmission Electron Microscopy (KZ8010) before 2011. Major grants supporting his work include: "Quantitative structural characterisation using 3D electron-based pair distribution function" (Swedish Research Council) "A Multidimensional Toolkit for Modern Electron Microscopy" (Swedish Foundation for Strategic Research) "Mitigating Ni-rich Li-ion cathode side-reactions" (Swedish Energy Agency, Co-applicant) He leads the Cheuk-Wai Tai group within Stockholm University's chemistry department and oversees operations at the Electron Microscopy Center, where his team develops and applies advanced characterization techniques for functional materials research.

Sara HäggView profile

Senior Lecturer

• Epidemiology
• Gerontology
• Medical Genetics and Genomics
• +3 more

Sara Hägg is a Senior Lecturer at the Karolinska Institutet , affiliated with the Department of Medical Epidemiology and Biostatistics . She is also a Docent in molecular epidemiology. PhD in Computational Biology (Linköping University, 2009) MSc in Molecular Biology (Stockholm University, 2003) BSc in Computer Science (Stockholm University, 2003) Her research focuses on human biological aging , including measurement of aging markers (telomere length, epigenetic clocks, frailty index), causal pathway analysis, and identification of geroprotectors for age-related diseases. She utilizes longitudinal twin studies (SATSA, GENDER, HARMONY), UK Biobank, and Swedish cohorts with methods like Mendelian randomization and genome-wide analyses . Recent articles demonstrate trends in epidemiological aging research , with emphasis on cardiovascular aging , neurological disease interactions , metabolic profiling , and epigenetic clocks . Her work often involves multivariable modeling and cross-cohort validation . Leadership roles include Director of LifeGene Core Facility (2024-) and Founding Board Member of the Nordic Aging Society (2023-). She serves on expert groups for the Swedish Twin Registry and Strategic Research Area in Epidemiology and Biostatistics .

• Microfluidics
• Materials Science
• Biomedical Engineering
• +7 more

Klas Hjort is a Professor of Materials Science at Uppsala University's Ångström Laboratory , specializing in Microsystems Technology . He leads the microsystems technology program and has pioneered research in heterogeneous microsystems on stainless steel, flexible foils, and elastic substrates for biomedical applications and wireless sensor/actuator systems . Key projects: SSF robotic textiles , PERSIMMON smart patches Research themes: Microfluidic actuation , Liquid metal patterning , Stretchable electronics His recent publications focus on soft robotics , smart patches , and high-pressure microfluidic systems , with keywords spanning Microfluidics , Biomedical Engineering , and Stretchable Electronics . He collaborates extensively in robotic textiles , microvalve design , and liquid metal composites . Contact: klas.hjort@angstrom.uu.se

• Control Technology
• Distributed Optimization
• Machine Learning
• +4 more

Mikael Johansson is a Professor at Kungliga Tekniska Högskolan (KTH), specializing in Control Technology . He teaches and coordinates courses such as Distributed Optimization (FEL3311) and various advanced-level degree projects in computer science, electrical engineering, and systems engineering. His research spans Control Systems , Machine Learning , and Optimization , with a focus on asynchronous algorithms, federated learning, and applications in energy systems and construction. His work includes 15 recent publications on topics like neural networks, distributed optimization, and battery technology. Notable areas of contribution are in asynchronous learning, federated learning with privacy constraints, and quasi-Newton methods for optimization. His research bridges theoretical advancements with practical applications in urban design, healthcare, and autonomous systems.

• Physiology
• Sports Science
• Molecular Biology
• +3 more

Tommy Lundberg is a Senior Lecturer and Docent in Physiology at Karolinska Institutet. He works at the Department of Laboratory Medicine, Division of Clinical Physiology. His email address is tommy.lundberg@ki.se, and his postal address is H5 Laboratoriomedicin, H5 Klinisk Fysiologi Gustafsson, 141 52 Huddinge. Lundberg is affiliated with the university library and has held positions since 2022. Research Interests: Lundberg's research focuses on skeletal muscle mass and function adaptation, particularly in athletic performance, disease contexts, aging, and transgender individuals undergoing hormone therapy. He investigates molecular, metabolic, morphological, and functional responses to resistance and aerobic exercises. His work also explores biological maturity selection biases in youth sports, bio-banding applications in soccer and ice hockey, and the impact of anti-inflammatory drugs on muscle hypertrophy. Article Trends: Lundberg's recent publications (2025–2024) cover topics like sex differences in disc golf, muscle atrophy in space exposome, longitudinal hormone therapy effects in transgender individuals, and bio-banding in youth sports. Earlier works delve into molecular pathways in muscle hypertrophy, concurrent training effects, mitochondrial function, and imaging techniques (CT/MRI) for muscle assessment. Scientific Recognition: Most prominent young researcher in Sport Science, Swedish Central Association for Sport Promotion (SCIF), 2017 Teaching and Editorial Roles: Lundberg teaches human physiology and sports science in nursing, physiotherapy, and biomedical analytics programs. He leads a contract education course in advanced exercise physiology and contributes to a PhD course on scientific writing. He is an Associate Editor for Frontiers in Physiology - Exercise Physiology (2022) and a member of the editorial board for Translational Exercise Biomedicine (2024). Collaborations and Expertise: He collaborates with the Swedish Football Association and Swedish Ice Hockey Association on bio-banding studies. Lundberg served as an invited speaker at the ACSM Annual Meeting (2024) on transgender athletes and as an expert panelist for World Rugby's transgender workshop (2020). His supervision includes Andrea Tryfonos (2021) and thesis evaluations at Mid Sweden University and Linköping University.

• computer security
• formal methods
• program logics
• +3 more

Mads Dam is a Professor in Teleinformatics at the School of Computer Science and Communication at Kungliga Tekniska Högskolan (KTH), where he heads the Department of Theoretical Computer Science. His research focuses on computer security, formal methods, and program logics, with particular emphasis on the formal modeling and verification of low-level hardware and software execution platforms for security and application isolation. His educational background includes: PhD in Computer Science from the University of Edinburgh (1990) MSc in Computer Engineering from Aalborg University, Denmark BSc in Information Technology from Aalborg University, Denmark Mads Dam's research interests center on computer security, formal methods, and program logics. His current work focuses on the formal modeling and verification of low-level hardware and software execution platforms such as hypervisors and OS kernels and their underlying hardware. He has made significant contributions to information flow security, verification of microarchitectural systems, and network programming language security. His research bridges theoretical foundations with practical security applications. His recent publications show a strong trend toward verifying low-level systems, with a focus on information flow security for processors, network programming languages (particularly P4), and microarchitectural vulnerabilities. His work combines formal methods with practical security concerns, developing verification techniques that address real-world security challenges in hardware and software systems. The research spans theoretical foundations in temporal and epistemic logics to practical applications in network security and processor verification. His scientific awards and recognition include: Two framework grants from the Swedish Foundation for Strategic Research A junior individual grant from the Swedish Foundation for Strategic Research Project grants and a five-year research fellowship from the Swedish Research Council (VR) Project grants from Ericsson, Microsoft Research, US Air Force, and Vinnova (the Swedish Innovation Agency) Mads Dam has been a principal investigator on numerous research projects and has supervised many graduate students. He has been a partner in several European projects including HATS, S3MS, VerifiCard, LOMAPS, and UaESMC. His research has been supported by substantial grants from major funding bodies, reflecting the significance and impact of his work in computer security and formal methods. He is a founding member of several research centers at KTH, including Access, the CASTOR software research center, and the CDIS center for cyber defense and information security. These centers bring together researchers from multiple disciplines to address complex challenges in cybersecurity and software engineering.

• Thermodynamics
• Diffusion
• Phase Transformations
• +3 more

Powder Metallurgy (MH2100) and has expertise in computational materials science. His research emphasizes predictive modeling of material behavior, including precipitation kinetics, sintering processes, and coating interactions. Notable areas include phase field modeling of discontinuous precipitation, spinodal decomposition in Fe-Cr alloys, and high-entropy alloy design. His studies bridge experimental data with computational tools like the YAPFI phase-field framework. Key themes in his publications span cemented carbides, Co-based entropic alloys, and tool wear mechanisms. He combines CALPHAD thermodynamic modeling with first-principles calculations to address challenges in materials processing and corrosion resistance. His work often addresses industrial applications, such as optimizing machining tools and additive-manufactured superalloys.

Lena RoxellView profile

Lecturer

• Criminology
• Prison Research
• Recidivism
• +6 more

Lena Roxell is a Lecturer at the Department of Criminology, Stockholm University, where she conducts research on prison systems, recidivism, and criminal networks. She is an active member of the Quantitative Criminology Research Group, established in 2022, which focuses on the possibilities and limitations of quantitative methods in criminology. Her primary research interests include prison research, with particular focus on long-term sentenced prisoners, prison networks, and recidivism patterns. Dr. Roxell examines how prison experiences affect reintegration outcomes and studies the structural aspects of co-offending networks. Her work often employs quantitative methods to analyze large datasets related to criminal behavior and prison administration. Analysis of her recent publications reveals a consistent focus on prison governance, recidivism timing, and the social dynamics within correctional facilities. Her research spans comparative studies (particularly between Sweden and other countries), methodological approaches to criminological research, and specialized topics like faith-based units in prisons and hate crime patterns. The publications demonstrate a sophisticated use of quantitative methods and longitudinal data analysis throughout her career. Dr. Roxell teaches thesis work and supervises students in prison research. Her current research project focuses on analyzing reduced recidivism after prison sentences based on client composition, prison services, labor market connections, and substance abuse. She is actively involved in the Quantitative Criminology Research Group at Stockholm University, contributing to methodological developments in the field and applying these approaches to understand complex prison dynamics and criminal behavior patterns.

• 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.

Michael RosanderView profile

Professor

• Work and Organizational Psychology
• Workplace Bullying
• Psychosocial Safety Climate
• +4 more

Michael Rosander , Professor at Linköping University , specializes in Work and Organizational Psychology at the Department of Behavioural Sciences and Learning (IBL) and Division of Psychology (PSY) . His research explores organizational and social work environments, focusing on workplace bullying, discrimination, and their psychological impacts. Recent work examines psychosocial safety, bystander effects, and gender dynamics in Swedish workplaces. Project leader for Swedish Research Council (Forte) initiatives (2019–2024, 2024–2026) Collaborates with Stefan Blomberg, Ståle Einarsen, and Dieter Salin Research extends to crowds, leadership interplay, and PBL group dynamics Publications span longitudinal studies, psychometric tools, and cross-disciplinary analyses of workplace health. Current projects emphasize nationwide data collection and organizational interventions.

• Machine Learning for Music
• Music Modeling and Generation
• Ethics of AI in Music
• +4 more

Bobby Lee Townsend Sturm JR is an Associate Professor at KTH Royal Institute of Technology, leading the MUSAiC project (ERC-2019-COG). He holds a PhD in Electrical and Computer Engineering from UC Santa Barbara (2009), followed by postdoctoral research at LAM, Paris 6, and academic roles at Aalborg University and Queen Mary University of London. His research focuses on AI ethics in music, generative AI for music, and folk music preservation. Current roles at KTH include teaching and supervising in Machine Learning, Music Informatics, and AI Ethics. He has pioneered AI music generation challenges (e.g., 2020 Double Jigs Challenge) and investigates societal impacts of AI on traditional music cultures. His work bridges technical innovation with cultural and ethical considerations, addressing issues like data colonialism, algorithmic bias, and human-AI collaboration in creative contexts. Education: PhD (UCSB, 2009), Postdoc (Paris 6), Academic appointments at Aalborg University (2010–2014) and Queen Mary University (2014–2018) Key Projects: MUSAiC (ERC), Virtual Session System for Irish Music, Traditional Music Dataset Analysis Teaching: Courses in Machine Learning, Music Acoustics, and ICT Innovation Publications span peer-reviewed journals and conferences, emphasizing ethical AI, music generation, and interdisciplinary research in MIR (Music Information Retrieval). He actively collaborates with musicians, anthropologists, and technologists to ensure culturally informed AI development.

• Electrochemistry
• Surface Science
• Atomic Force Microscopy (AFM)
• +7 more

Jing Li is a Staff Scientist at Stockholm University's Department of Chemistry, leading operations at the MACAL Soft Matter Characterization Lab and Surface Analysis Core. She holds two PhDs in Physical Chemistry (Xiamen University, China) and Surface Science (KTH Royal Institute of Technology, Sweden), with postdoctoral experience at University of Alberta and Swedish University of Agricultural Sciences (SLU). Her interdisciplinary research bridges electrochemistry, atomic force microscopy (AFM), and bio-based nanomaterials. PhD in Physical Chemistry (2004-2010), Xiamen University PhD in Surface Science (2011-2015), KTH Royal Institute of Technology Postdoctoral Fellow, University of Alberta (2010-2011) Researcher, Swedish University of Agricultural Sciences (2016, 2017-2018, 2020) Guest Researcher, BOKU Vienna (2017-2018) Research Focus: Development of advanced AFM methodologies for nanoscale surface science, electrochemistry of conductive nanomaterials, and functionalization of cellulosic composites. She investigates corrosion mechanisms through in situ electrochemical-AFM, with applications in water treatment membranes and renewable energy systems. Her work employs quantitative force mapping and nanomechanical analysis of bio-based materials. Scientific Leadership: Manages MACAL's multimode AFM, DMA, tensile testing, and gas adsorption analyzers. Teaching responsibilities include two advanced courses: Introduction into AFM (KZ41005) and Introduction into Dynamic Mechanical Analysis (KZ41021) , emphasizing practical data acquisition and interpretation.

Hamed NematiView profile

Assistant Professor

• Security of systems software
• Formal methods and program logics
• Interactive theorem proving
• +2 more

Hamed Nemati is an Assistant Professor at the Division of Network and Systems Engineering under the School of Electrical Engineering and Computer Science at KTH Royal Institute of Technology in Stockholm, Sweden. He was previously a Visiting Assistant Professor at Stanford University and a Research Group Leader at the Helmholtz Center for Information Security (CISPA) , where he also worked as a PostDoc and Research Fellow. Education : PhD in Computer Science from KTH Royal Institute of Technology Research Interests : Security of systems software, formal methods and program logics, interactive theorem proving, machine code analysis, applied machine learning Current Projects : Systematic verification of multi-language security protocols, hardware-software co-design for Spectre mitigation, capability-based access control models Scientific Awards : WASP (Wallenberg AI, Autonomous Systems and Software Program) faculty member Teaching Activities : Formal Methods in Security (Fall 2020-2023) at CISPA/Saarland University Digital Forensics and Incident Response (EP2780) (Fall 2024) at KTH