Find Academic Supervisors

• Sustainable Forestry Management
• Continuous Cover Forestry
• Individual-Tree-Selection Methods
• +3 more

Nils Fagerberg is a Lecturer at Linnaeus University's Department of Forestry and Wood Technology within the Faculty of Technology. He holds a PhD in Forest Industry Production Systems and focuses on sustainable forestry practices, particularly continuous cover forestry and individual-tree-selection methods. He works 60% at the university, teaching courses like Sustainable Family Forestry III and Hygge-Free Forestry, while dedicating the remaining time to his family farm and consulting in continuity forestry and beef production. His education includes a B.Soc.Sc. in Ecological Economics, M.Sc. in Forestry, and M. in Sustainable Development. His doctoral research investigated optimizing tree selection in uneven-sized forests to balance economic returns with environmental and social benefits. He collaborates with the Forest Management research group, addressing sustainable forest use through interdisciplinary approaches. Fagerberg’s publications emphasize quantitative models for tree growth, knot prediction, and optimization strategies in continuous cover forestry. He has contributed datasets from Linnaeus University’s field trials, enabling further research into spruce growth and canopy dynamics. His work bridges academic research with practical forestry applications, advocating for sustainable management practices.

Stefan Cavalcante Bernat JuniorView profile

Assistant Professor

• Innovation Management
• Digital Transformation
• Living Labs
• +3 more

Stefan Cavalcante Bernat Junior is an Assistant Professor at Linköping University’s Department of Management and Engineering (IEI), affiliated with the Project, Innovations and Entrepreneurship (PIE) division. He holds a Master’s in Electrical Engineering and a PhD in Industrial Engineering and Management. A retired Brazilian Army colonel with 30+ years’ experience in project management and leadership roles, including military unit command and instructor positions at the Military Academy of Agulhas Negras. His research focuses on innovation capability development in emerging economies, digital transformation, and living labs for urban sustainability. He teaches courses on advanced project organization, leadership, and organizational change. Key affiliations include the PIE division and IEI department at LiU. Research interests span strategic alignment of technology in defense industries, innovation ecosystems in emerging markets, and leveraging digital tools for sustainable urban solutions. His work bridges academic insights with practical applications in project management and business process optimization. Current projects explore the role of living labs in mobility innovation and sustainability.

Colm NestorView profile

Associate Professor

• Epigenetic Control of Human T-cell Biology
• Autoimmunity and Allergy
• Cancer (Hematology and Other Tumors)
• +3 more

Colm Nestor is a Senior Associate Professor at Linköping University, Sweden, affiliated with the Faculty of Medicine and Health Sciences, Department of Biomedical and Clinical Sciences, and the Division of Children's and Women's Health. His research focuses on epigenetic control of T-cell biology, sex differences in disease susceptibility, and developing therapies targeting DNA methylation. He holds leadership roles including Chair of the Junior Faculty Club, Co-Chair of the Centre for Personalised Medicine, and Member of the Academic Employment Board. Education highlights include a B.A. in Natural Sciences from Trinity College Dublin, followed by M.Sc. degrees in Computer Science (University of Cork) and Bioinformatics (University of York). He earned his Ph.D. in 2003 from the University of Glasgow. Postdoctoral training includes roles at the University of Edinburgh and Linköping University, alongside industry experience as a Bioinformatics Specialist at DeCODE Genetics and a Database Developer at LION Biosciences. Research interests center on understanding how the X-chromosome and DNA methylation influence health, particularly in autoimmune diseases, infections, and cancers like childhood leukemia. He investigates sex-specific disease mechanisms and leverages systems medicine to identify diagnostic/therapeutic targets. His work also addresses methodological flaws in epigenetic research, such as the widely used DIP-seq method. Recognized with prestigious awards: the 2025 Onkel Adam Prize and an ERC Consolidator Grant (2020) for sex-bias research. He also received funding from the Joanna Cocozza Foundation for pediatric medicine studies. Current projects include studying TET2 reactivation in leukemia and epigenetic changes in pregnancy-related T-cell dysfunction. Nestor advises four PhD students and collaborates with researchers like Huan Zhang (Principal Research Engineer) and Antonio Lentini (Researcher). He contributes to teaching at the Medical Program, Experimental Biosciences M.Sc., and Ph.D. courses. His lab, The Nestor Lab , integrates epigenetic, genomic, and computational approaches for clinical impact.

Gouthanan PushpananthanView profile

Assistant Professor

• Artificial Intelligence
• Critical Infrastructure Management
• Innovation Ecosystems
• +3 more

Gouthanan Pushpananthan is an Assistant Professor at Linköping University (LiU), affiliated with the Department of Management and Engineering (IEI) and the Project, Innovations and Entrepreneurship (PIE) division. His research focuses on innovation ecosystems, agile project management, and the strategic implications of technological change in critical infrastructures such as healthcare, transportation, and energy. He explores topics like keystone firms, organizational adaptation, and the transformation of industries in the digital age. His work bridges management theory with practical applications, particularly in the automotive sector and emerging technologies. He contributes to LiU's mission of advancing innovative education and interdisciplinary research, emphasizing boundary-crossing collaboration between academia and industry. Key research trends in his publications include the dynamics of innovation ecosystems, competitive strategies for keystone firms, and the challenges of institutionalizing agile methodologies. His work often highlights the interplay between technological advancements and organizational structures. Gouthanan is a member of the NICER research group and actively contributes to the PIE division's mission of fostering project management, innovation, and entrepreneurship education. No formal awards or grants are explicitly mentioned in the provided texts.

• Condensed Matter Physics
• Spintronics
• Metamaterials Design
• +3 more

Qichen Xu is a Research Fellow at the Department of PHYSICS OF LIGHT AND MATTER within the Royal Institute of Technology (KTH). His work focuses on advanced materials science and computational magnetism, with specializations in spintronics, metamaterials, and machine learning-driven materials discovery. He has developed tools like SpinView for visual analysis of magnetic systems and contributed to understanding exotic spin textures like skyrmions through algorithmic approaches. Research Interests include computational modeling of magnetic materials, optimization of energy systems via metamaterials, and applying machine learning to accelerate materials design. His recent work explores chemical disorder effects in FeCo alloys, skyrmion-based metamaterial design, and high-throughput screening of halide perovskites for energy applications. Notable contributions span 14+ peer-reviewed articles (2018–2024) addressing topics from near-field thermophotovoltaic systems to genetic-algorithm-driven energy optimization. While no formal awards are listed, his work demonstrates significant impact in interdisciplinary fields combining physics, materials science, and AI. Advising and grants sections are pending further information, though his involvement in collaborative projects like SpinView suggests active team-based research. Part of KTH’s cutting-edge Physics of Light and Matter group, his research bridges fundamental physics and applied technology development in energy and spintronics domains.

• Energy Economics
• Operational Research
• Game Theory in Energy Markets
• +3 more

Afzal Siddiqui is a Professor at the Department of Computer and Systems Sciences, Stockholm University, and holds adjunct roles at Aalto University and HEC Montréal. His research focuses on applying operational research to energy economics, particularly decision-making under uncertainty in renewable integration, market design, and climate policy. He has led projects like STRING (Nordic hydro-renewable interactions) and SCORES (sector coupling analysis). Education: PhD in Industrial Engineering & Operations Research from UC Berkeley, with minors in Economics and Energy Resources. Notable academic roles include Professorships at University College London and Visiting appointments at Berkeley Lab and NTNU Trondheim. Research emphasizes strategic behavior in energy markets, including hydro operations, transmission planning, and CO2 pricing. Recent work examines prosumer impacts, storage economics, and policy coordination in decarbonization. Over 10 doctoral students supervised across multiple institutions. Key contributions include DER-CAM optimization tools, analysis of EU energy policies, and models for emission leakage in regional markets. Current affiliations include the EU-funded PlanFES project and leadership in Nordic energy transition studies.

Malin Palö ForsströmView profile

Academic

• Discrete Probability Theory
• Lattice Gauge Theories
• Mathematical Physics
• +3 more

Malin Palö Forsström is a Visiting Lecturer at Gothenburg University and lectures at Chalmers University of Technology. She previously held a postdoctoral position at KTH Royal Institute of Technology, focusing on probability theory under supervision of Fredrik Viklund and Jonatan Lenells. Her PhD, completed in 2019, was at Chalmers University of Technology under Jeffrey E. Steif. She has also taught courses at multiple institutions, including Chalmers, KTH, and Gothenburg University. Malin Palö Forsström earned her PhD in 2019 from Chalmers University of Technology, supervised by Jeffrey E. Steif. Prior to that, she pursued academic training leading to her doctoral studies. Her primary research interests lie in discrete probability theory, particularly applying probabilistic methods to study lattice gauge theories and related models. She also investigates properties of Boolean functions, including noise sensitivity, volatility, and total influence. Her work bridges theoretical probability with applications in mathematical physics and statistical mechanics. Her recent publications focus on lattice gauge theories, exploring Wilson loops and Higgs models, as well as the analysis of Boolean functions' sensitivity properties. Her work often combines probabilistic techniques with insights from mathematical physics, contributing to both theoretical frameworks and applied models in statistical mechanics. Scientific Awards and Grants: 2021: Ruth och Nils-Erik Stenbäcks stiftelse 2019: Kungliga vetenskapsakademin, Stiftelsen G S Magnusons fond 2015: Stiftelsen Olle Engkvist byggmästare 2014: SveFuM Malin has received several grants supporting her research, including notable awards from the Ruth och Nils-Erik Stenbäcks Foundation and the Swedish Research Council. She has not listed specific advising roles or grants beyond those mentioned. Her work has been presented at numerous events, including the Nordic Congress of Mathematicians, the Mittag-Leffler Institute, and international conferences like ICMP 2021.

• Wood Chemistry
• Biomass Utilization
• Sustainable Materials
• +5 more

Martin Lawoko is a Professor at KTH Royal Institute of Technology, specializing in Wood Chemistry. His research focuses on developing sustainable materials from biomass and lignin, aiming to replace fossil-based products. He collaborates with industries like Stora Enso and the Wallenberg Wood Science Center (WWSC), and contributes to initiatives such as Bioinnovation, advancing Sweden's bioeconomy goals. His work integrates multidisciplinary approaches to address challenges in lignin valorization, biorefinery processes, and material synthesis. Lawoko’s research emphasizes the structural and reactivity analysis of lignin-carbohydrate complexes (LCCs), exploring their applications in thermosets, bioplastics, and functional polymers. His studies often involve advanced techniques like molecular dynamics simulations, spectroscopy, and process engineering. Key areas include lignin extraction methods, modification strategies, and the development of bio-based materials with tailored properties for industrial use. Publications highlight advancements in lignin-based materials, including studies on kraft lignin utilization, oxidative carboxylation, and thiol-ene thermosets. His work underscores the importance of preserving lignin structure during extraction to maximize its potential in renewable products. While no specific awards or grants are listed, his contributions significantly impact sustainable development and the forestry sector’s product diversification efforts.

• Mathematical Statistics
• Machine Learning
• Artificial Intelligence
• +4 more

Jimmy Olsson is a Professor in the Department of Mathematical Statistics at KTH Royal Institute of Technology. His research focuses on generative models, statistical computational methods, and dynamic systems analysis, particularly in the context of artificial intelligence and machine learning. He specializes in state-space models, sequential Monte Carlo methods, and Markov chain Monte Carlo techniques. His work emphasizes foundational contributions to hidden Markov models, computational algorithms for statistical inference, and the intersection of mathematical statistics with modern data science challenges. Key research areas include developing efficient computational tools for analyzing complex, time-dependent data streams, with applications in AI and machine learning. Olsson’s publications span advanced topics such as diffusion models, particle filtering, and online variational learning, reflecting his expertise in bridging theoretical statistics with practical computational methods. He collaborates with researchers across disciplines, including engineering, computer science, and applied mathematics.

• Quantum Optics
• Quantum Information
• Quantum Machine Learning
• +3 more

Anton Frisk Kockum is an Associate Professor in Applied Quantum Physics at Chalmers University of Technology. He holds a PhD in Physics from Chalmers (2014) and completed postdoctoral research at RIKEN in Japan (2014–2018), supported by a JSPS Fellowship. He joined the Wallenberg Centre for Quantum Technology in 2018, focusing on theoretical contributions to quantum computing and quantum program design. His research spans quantum optics, quantum information, and quantum machine learning, with emphasis on ultrastrong light-matter coupling, quantum acoustics, and circuit quantum electrodynamics. He explores quantum technologies for building scalable quantum computers and optimizing their applications. Recent work includes entanglement generation in hybrid systems, decoherence mitigation, and quantum process tomography advancements. His publications (67 total) address topics like giant atom dynamics, quantum amplification, and quantum algorithm optimization for real-world problems. He leads projects funded by EU, SSF, and VR, including studies on non-Hermitian topological phases and structured quantum environments.

• Non-equilibrium statistical physics
• Theoretical cell biology
• Theoretical computer science (unconventional computing)
• +4 more

Zoran Konkoli is an Associate Professor at Chalmers University of Technology, affiliated with the Department of Microtechnology and Nanoscience (MC2) within the Electronic Materials division. His research spans interdisciplinary areas including non-equilibrium statistical physics, theoretical cell biology, and unconventional computing. He holds a PhD in Theoretical Chemistry from Gothenburg University and has held postdoctoral positions at Chalmers, NORDITA, and the Applied Physics Department at Chalmers. His academic journey includes roles such as assistant professor in Biological Physics (2002–2006) and a permanent position as Associate Professor since 2007. Konkoli’s research focuses on diffusion-controlled reactions, theoretical cell biology (e.g., HIV latency mechanisms), and computational models like cellular automata and memristor networks. His work intersects condensed matter theory, statistical physics, and computer science. Key projects include the EU-funded RECORD-IT (2015–2018) and SYMONE (2012–2015), exploring reservoir computing and biomimetic systems. He collaborates widely, emphasizing interdisciplinary networks to advance theoretical ideas into practical applications. His expertise includes mathematical logic, measure theory, and approximation theorems, reflecting his broad academic interests.

Chiara TrentiView profile

Researcher

• Cardiovascular Magnetic Resonance Imaging
• Aortic Hemodynamics
• Wall Shear Stress Analysis
• +3 more

Chiara Trenti is a researcher at Linköping University, affiliated with the Department of Health, Medicine and Caring Sciences and the Division of Diagnostics and Specialist Medicine. She holds a PhD in Medical Sciences (2020), an MSc in Biomedical Engineering with a focus on Biomechanics and Biomaterials (Politecnico di Milano, 2019), and a BSc in Biomedical Engineering (Politecnico di Milano, 2016). Her research focuses on advancing cardiovascular magnetic resonance imaging (CMR) techniques, particularly 4D flow MRI, to study blood flow dynamics and their effects on aortic remodeling. Key interests include wall shear stress analysis, biomarker correlations in aortic diseases, and risk factor identification for vascular conditions like abdominal aortic aneurysms and aortic dilation. Her work has been recognized with awards including 2nd place for best presentation at the 2024 ISMRM Annual Meeting and the 2022 Potchen-Passariello Basic Science Award. She collaborates with the Center for Medical Image Science and Visualization (CMIV) and researchers like Petter Dyverfeldt and Tino Ebbers. Current research emphasizes decoding aortic disease mechanisms through enhanced MRI analysis and exploring hemodynamic factors influencing vascular remodeling. Publications highlight contributions to understanding oscillatory shear stress in bicuspid aortic valve patients, correlations between wall shear stress and biomarkers in aortic dilation, and risk factors for abdominal aortic aneurysms. Ongoing projects include follow-up studies on ascending aortic dilation progression and development of automated segmentation methods for 4D flow MRI.

Ulf KargénView profile

Assistant Professor

• Information Security
• Systems Security
• Software Security
• +4 more

Ulf Kargén is an Assistant Professor at Linköping University's Department of Computer and Information Science (IDA). His research focuses on information security, particularly systems and software security, with an emphasis on dynamic analysis of binary-code programs. He is a PhD student under the supervision of Professor Nahid Shahmehri, exploring topics such as scalable dynamic analysis methods and security flaw detection in software. He leads courses in software security (TDDC90) and information security (TDDD17) at Linköping University. His work includes developing tools like desync-cc for program obfuscation and analyzing Android app decompilation performance. He is part of the Security and Networks Group at ADIT, which emphasizes secure and reliable information systems. Key research areas include code obfuscation detection, malware analysis, and empirical studies of decompiler effectiveness. His publications span topics like autonomous vehicle compliance testing, binary code analysis, and compiler-level security mechanisms.

Fredrik LindstenView profile

Associate Professor

• Machine Learning
• Statistical Machine Learning
• Approximate Bayesian Inference
• +7 more

Fredrik Lindsten is a Senior Associate Professor in Machine Learning and Head of the Division of Statistics and Machine Learning at Linköping University's Department of Computer and Information Science (IDA). His research focuses on statistical machine learning, emphasizing probabilistic modeling and uncertainty quantification in methods such as approximate Bayesian inference, representation learning, and graph-based approaches. Applications span weather forecasting, materials science, biochemistry, and automotive industry challenges. Education: MSc (2008), PhD (2013) in Automatic Control from Linköping University; Postdoctoral roles at University of Cambridge, UC Berkeley, and University of Oxford. Affiliations: WASP (Wallenberg AI, Autonomous Systems and Software Program), ELLIIT (Lab for Information and Communication Technology). Research Interests: Lindsten’s work bridges statistical methodology and machine learning, particularly in quantifying uncertainty in predictions. His team explores method development across diverse applications, including spatio-temporal models and graph-based techniques. Recent projects include probabilistic weather forecasting with graph neural networks and cryo-EM reconstruction techniques. Publications: Over 25+ peer-reviewed articles, with recent highlights in Nature Methods , NeurIPS , and Physical Review Materials , focusing on Bayesian methods, generative models, and computational statistics. Awards: Ingvar Carlsson Award (Swedish Foundation for Strategic Research), Benzelius Award (Royal Society of Sciences in Uppsala). Grants & Teams: Supervises 7+ PhD students; active in collaborative projects funded by WASP, ELLIIT, and VR (Swedish Research Council). Labs/Teams: Leads the Division of Statistics and Machine Learning (STIMA) at IDA, fostering interdisciplinary research in probabilistic machine learning.

Andreas LarssonView profile

Researcher

• Educational Development
• Technology Education
• Educational Science
• +3 more

Andreas Larsson is a Postdoc researcher at Linköping University's Department of Behavioural Sciences and Learning (IBL), within the Division of Learning, Aesthetics, and Natural Science (LEN). His work focuses on educational development, particularly in science and technology education, and he actively contributes to the Swedish National Centre for Science and Technology Education (NATDID). His research emphasizes bridging educational research with practical teaching methods, including the integration of technology, programming pedagogy, and the role of spatial metaphors in instruction. Education: While specific academic degrees are not detailed in the provided texts, Larsson's role as a Postdoc indicates advanced qualifications in educational sciences or related fields. Research Interests: Larsson specializes in technology education, programming pedagogy, and the use of gestures and metaphors in teaching. He explores how spatial constructs and linguistic metaphors aid abstract concept comprehension, particularly in programming and STEM education. His work also addresses curriculum continuity and material resources in Swedish vocational training programs. Articles Overview: Larsson’s recent publications (2022–2025) focus on metaphor analysis in programming education, gesture-based teaching strategies, and the material foundations of effective technology education. His research highlights the interplay between embodied cognition and instructional design. Awards: No scientific awards are explicitly mentioned in the provided texts. Advising & Grants: While specific grants are not listed, Larsson collaborates with NATDID to translate research into practical educational tools. His involvement in conferences like the WERA Task Force Global Research in Extended Education (2025) underscores his contribution to educational policy and outreach. Labs/Teams: Active in LEN and NATDID, he contributes to projects on AI literacy in teacher education and the greening of working life (GROWL). His work intersects with interdisciplinary initiatives exploring digital tools in education and workplace dynamics.