Find Academic Supervisors

• Pharmacokinetics/Pharmacodynamics (PKPD) Modeling
• Translational Research
• Antibiotic Resistance
• +7 more

Lena Friberg is a Professor at Uppsala University's Department of of Pharmacy (Pharmacokinetics and Pharmacodynamics) since 2021, previously holding the same title in Pharmacometrics (2014-2021). With over 190 peer-reviewed publications and an h-index of 56, her research focuses on translational PKPD modeling for dose optimization in oncology and infectious diseases. Developed frameworks for preclinical-to-clinical translation Work spans cancer chemotherapy, antibiotic resistance, and drug combinations Utilizes non-linear mixed effects modeling and physiologically-based approaches Scientific Awards : Giorgio Segré Prize (EUFEPS) Innovation Award (ISoP) ISoP Fellow Vinnova/BioSweden Key Scientist She supervises 9 PhD students, mentors postdocs, and holds grants from Swedish Research Council, Swedish Cancer Society, EU-IMI2, and Marie Skłodowska-Curie ITN. Her work facilitates drug development transitions while considering therapeutic and adverse effects.

• Microwave Engineering
• RF Systems Design
• Power Amplifier Design
• +7 more

Christian Fager is a Full Professor at the Department of Microwave Electronics, Chalmers University of Technology, Sweden. He has been affiliated with Chalmers since completing his Ph.D. there in 2003. As Head of the Microwave Electronics Laboratory, his research focuses on nonlinear transistor modeling, energy-efficient power amplifier architectures, and distributed MIMO systems. He has co-invented 8 patents and published over 250 papers, including a seminal book on Nonlinear Transistor Model Parameter Extraction Techniques (Cambridge University Press, 2011). Dr. Fager holds editorial roles as Associate Editor of IEEE Microwave Magazine and member of the MTT-S Technical Coordination Committee on Wireless Communications. He is a Board Member of the European Microwave Association (EuMA) and has chaired multiple IEEE topical conferences. His awards include the Chalmers Supervisor of the Year (2018), inaugural Area of Advance Award (2010), and IEEE IMS Best Student Paper (2002). He leads research initiatives in distributed antenna systems, digital pre-distortion, and GaN/SiGe-based high-efficiency amplifiers, with projects involving testbed development for 5G/6G applications. His work bridges theoretical modeling and practical implementation in RF/microwave systems, emphasizing thermal and multi-physical simulation integration.

• Machine Learning
• Natural Language Processing
• Predictive Maintenance
• +4 more

Tony Lindgren is an Associate Professor at the Department of Computer and Systems Science, Stockholm University, affiliated with the Data Science Research Group and Natural Language Processing Research Group. His work bridges data science and NLP , focusing on interpretable models, constraint programming, and predictive maintenance systems. Research interests include: Machine Learning for explainability and fairness Constraint Programming in maintenance optimization Natural Language Processing for risk analytics and troubleshooting Recent publications demonstrate trends in multi-objective optimization (2025 satellite scheduling), conformal prediction (2024 CoPAL), and fault detection (2024 Automotive Nowcasting). His work often integrates domain-specific constraints with scalable algorithms across applications like food safety and autonomous vehicles. Software tools developed by Lindgren include: Example-based Feature Tweaking Rule Indexing Frameworks His research groups focus on AI-driven decision support for high-stakes domains, combining technical innovation with societal impact considerations.

• 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.

• Systems Biology
• Biochemical Engineering
• Metabolic Engineering
• +9 more

Jens B Nielsen is a Professor of Quantitative Systems Biology at Chalmers University of Technology , Sweden, where he leads a research group of over 60 people. He previously served as full Professor and founded the Center for Microbial Biotechnology at Danish Technical University (DTU) , and as Chief Science Officer of the Novo Nordisk Foundation Center for Biosustainability (2013-2018). Current CEO of BioInnovation Institute (Denmark) since 2019 Member of National Academy of Engineering (USA), National Academy of Science (USA), and multiple European academies His research spans systems biology , metabolic engineering , and industrial biotechnology , with over 700 publications and 50 patents. Key innovations include CRISPR-based yeast engineering , enzyme-constrained metabolic models , and microbiome-host interaction frameworks . He has founded several biotech companies and supervised 100+ PhD students. Recent publications highlight work on: Antimicrobial resistance dynamics in microbiomes CRISPRi/a for yeast tolerance mechanisms Metabolism-driven enzyme evolution over millennia Precision modeling of gut microbiota Scientific Awards : Nature Mentor Award for academic leadership ENI Award for energy innovation Novozymes Prize for biotech impact Gold Medal from Royal Swedish Academy of Engineering Sciences He has received continuous recognition as a Highly Cited Researcher (2015-2018) and serves on editorial boards of leading journals like Nature Communications and Trends in Biotechnology .

Marc HellmuthView profile

Associate Professor

• Discrete Mathematics
• Combinatorics
• Graph Theory
• +10 more

Marc Hellmuth is an Associate Professor of Computational Mathematics at the Department of Mathematics, Stockholm University, Sweden. His academic career includes previous positions as Junior Professor for Biomathematics and Computer Science at University of Greifswald, Germany (2015-2020), Lecturer at School of Computing, University of Leeds, UK (2020), and PostDoc positions at Saarland University and Max-Planck Institutes. Dr. Hellmuth earned his PhD in Computer Science from University of Leipzig, Germany (2007-2010, summa cum laude), supervised by Peter F. Stadler, and completed his Venia Legendi (habilitation) at Saarland University, Germany (2016). His research spans the interface of discrete mathematics, computer science, and life sciences with emphasis on: Discrete Mathematics including Graph Theory, Combinatorics, and Optimization Algorithm Design and Complexity Theory Mathematical and Computational Biology Phylogenomics and Evolutionary Analysis Computational Chemistry and Atom Tracking His publication record demonstrates a consistent focus on developing mathematical frameworks and efficient algorithms for biological problems, particularly in phylogenomics, orthology detection, and evolutionary analysis. His work bridges theoretical computer science with practical applications in biology and chemistry, often resulting in open-source software tools. Dr. Hellmuth has developed numerous software tools including AsymmeTree for phylogenetic simulation, tralda for tree algorithms, and specialized tools for phylogenomics, atom tracking, and graph analysis. His collaborative work extends internationally with research visits to institutions including Yale University, University of Leoben, Vienna University of Economics, University of Southern Denmark, Université de Montréal, and institutions in China.

• Industry 4.0
• Resilience Engineering
• Sustainability in Production Systems
• +3 more

Arpita Chari is a Research Fellow at Chalmers University of Technology, specializing in Virtual and Digital Production Systems. Her work bridges Industry 4.0, Resilience Engineering, and Sustainability in Production Systems, focusing on integrating digital technologies to enhance resource efficiency and enable lean circular manufacturing. Her research explores the implementation of resilient and sustainable practices in manufacturing, emphasizing dynamic capabilities, digital platforms, and supply chain optimization. Key projects include the Digitala Stambanan initiative and the Produktion2030 strategic innovation program, which address sustainability transitions and systemic resilience. 2024 Highlights: Analyzed dynamic capabilities for resilience-sustainability integration, characterized battery lifecycle challenges, and modeled risk prioritization in supply chains. 2023 Themes: Digital platform adoption, battery production systems, and value chain sustainability in the Digitala Stambanan project. 2022–2021 Foundations: Developed frameworks for green manufacturing, circular supply chains, and stakeholder-driven sustainability in textiles.

• Vehicular Control Systems
• Electric and Hybrid Vehicle Technology
• Vehicle Dynamics
• +4 more

Jonas Fredriksson is a Professor in the Mechatronics research group at the Department of Systems and Control Engineering, Chalmers University of Technology. His work focuses on electric/hybrid vehicles, vehicle dynamics, active safety systems, and optimization-based coordination of automated vehicles. Academic Rank: Professor Affiliation: Chalmers University of Technology Department: Systems and Control Engineering Email: jonas.fredriksson@chalmers.se Research Themes: Powertrain control and energy management for electric/hybrid vehicles Advanced control strategies for heavy articulated vehicles Autonomous driving in confined environments Battery thermal management and charging optimization Vehicle stability and safety systems using Newtonian mechanics Article Trends: Recent publications emphasize 1) optimization algorithms for electric vehicle coordination, 2) aerodynamic modeling under crosswind conditions, 3) stochastic approaches to longitudinal vehicle dynamics, and 4) robust control systems for articulated heavy vehicles. The work combines classical mechanics with modern machine learning techniques. Teaching & Leadership: Supervises doctoral students and leads research projects in mechatronics. Manages the master's program in Systems, Control and Mechatronics. Teaches courses in mechatronics and vehicle control systems.

• 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.

Martin SjölundView profile

Associate Professor

• Software Engineering
• Cyber-Physical Systems
• Modelica Compiler Development
• +3 more

Martin Sjölund is an Associate Professor at Linköping University's Department of Computer and Information Science (IDA), part of the Software and Systems (SAS) division. His work focuses on software engineering and cyber-physical systems, with a specialization in Modelica compiler development and open-source simulation tools. He contributes to the OpenModelica project, advancing compiler frameworks, integration with Julia, and standardization efforts. Research interests include compiler design, formal methods, and domain-specific languages. Recent work emphasizes modular compiler architectures, structural variability handling, and interoperability between Modelica and other systems like Julia and Python. He has co-authored over 30 peer-reviewed publications since 2017, with a focus on compiler optimization, co-simulation, and educational applications of Modelica. As part of the SAS division, he collaborates with researchers like Lena Buffoni, Adrian Pop, and Peter Fritzson on projects funded by the MODPROD Center and other initiatives. His contributions to open-source tools have been recognized through conference proceedings and industry partnerships.

• Density Functional Theory
• Van der Waals Interactions
• Molecular Binding
• +4 more

Per Hyldgaard is a Professor at the Quantum Component Physics department of Chalmers University of Technology . His research focuses on developing and applying van der Waals density functionals (vdW-DF) to study molecular binding, nanomaterials, and condensed matter systems. Key areas include nonlocal correlation effects, electronic structure analysis, and material properties under extreme conditions. Research Interests: Hybrids of van der Waals functionals, quantum materials, adsorption mechanisms, and computational materials science. His work bridges theoretical frameworks with experimental validation, addressing challenges in predicting CO₂ adsorption, metallic surface interactions, and polymeric systems. Recent Projects: 2019–2022: VR-funded study on charge transfer in soft materials. 2015–2018: Consistent vdW-DF studies for molecular systems. 2014–2019: High-speed graphene-based electronics collaboration. Publications: Over 100 peer-reviewed articles, including foundational work on vdW-DF methods and applications in nanotubes, layered materials, and catalytic systems. Recent trends emphasize hybrid functional optimization and energy scaling laws in nanostructures. Grants & Teams: Collaborations with EU and SSF on bio-inspired molecular networks and high-speed electronics. Active in developing libvdwxc , a software library for vdW-DF functionals.

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.

Nancy Joy LimView profile

Senior Lecturer

• Geospatial Information Science
• Flood Risk Management
• Climate Change Mitigation
• +3 more

Nancy Joy Lim is a Senior Lecturer in the Department of Geography at the University of Gävle. Her research focuses on Geospatial Information Science, particularly in flood risk management, environmental modeling, and urban resilience planning. She specializes in analyzing uncertainties in flood maps and their implications for decision-making, leveraging advanced geovisualization techniques and ensemble modeling approaches. Her educational background includes a PhD in Modelling, Mapping and Visualisation of Flood Inundation Uncertainties (2018). She has published extensively in journals like Geomatics, Natural Hazards and Risk and International Journal of Geographical Information Science , and contributed to books such as DEM Resolution and Roughness Effect in Relation to Model Performance (2023). Her work bridges theoretical geospatial analysis with practical applications in climate change mitigation and urban sustainability. Key research themes include the role of blue-green infrastructure in climate adaptation, DEM resolution impacts on flood modeling, and cartographic frameworks for visualizing uncertainty. She collaborates internationally, evidenced by co-authored papers with institutions in Sweden and beyond. While no academic awards are cited, her contributions to flood resilience planning and geospatial methodologies are notable. Nancy’s publications reflect a trajectory from foundational flood uncertainty studies (2014–2016) to contemporary urban resilience challenges (2021–2025), emphasizing interdisciplinary approaches to environmental challenges. Her conference presentations and doctoral work further highlight expertise in hydraulic modeling and spatial decision-support systems.

Cristian RojasView profile

Professor

• Automatic Control
• System Identification
• Control Theory
• +7 more

Cristian Rojas is a Professor of Automatic Control at KTH Royal Institute of Technology, specializing in system identification. His research bridges control theory, statistics, and machine learning to develop data-driven methods for analyzing and controlling dynamical systems. He holds an MS in Electronics Engineering from Universidad Técnica Federico Santa María (Chile) and a PhD in Electrical Engineering from the University of Newcastle (Australia). Research focuses on efficient utilization of data for self-learning systems, including topics like continuous-time system identification, robust control, and statistical estimation. Notable contributions include work on subspace identification, input design for sparse systems, and algorithms for H-infinity norm estimation. His methodologies emphasize practical applications in industrial automation, smart infrastructure, and autonomous systems. Recent publications highlight advancements in inverse filtering, decentralized learning systems, and the theoretical underpinnings of data-driven control. He collaborates widely on projects involving Bayesian methods, adversarial systems, and privacy-protected decision-making frameworks. Rojas' work often addresses challenges such as undersampling effects, model consistency, and computational efficiency in real-world control scenarios. His academic contributions include organizing academic ceremonies at KTH and mentoring researchers in the Department of Automatic Control. Current research explores intersections between machine learning interpretability and control theory, with applications to explainable AI in engineering systems.

Bestoun S. Ahmed Al-BeywaneeView profile

Professor

• Quality Assurance of Machine Learning Systems
• Software Testing
• Trustworthy AI Systems
• +5 more

Bestoun S. Ahmed Al-Beywanee is a Professor in AI and Software Engineering at the Department of Mathematics and Computer Science, Karlstad University, Sweden. He joined the university as a Senior Lecturer in 2019, was promoted to Associate Professor in 2020, and to Professor in 2023. His roles include teaching advanced courses such as AI Engineering, Automated Software Engineering, and Software Testing Fundamentals. His research focuses on software quality assurance, trustworthy AI systems, and MLOps, with a strong emphasis on combinatorial testing, IoT systems, and applied optimization techniques. Education: BSc (Electrical and Electronic Engineering, University of Salahaddin-Erbil, 2004); MSc (University Putra Malaysia, 2009); PhD (Software Engineering, University Sains Malaysia, 2012). Postdoctoral research at the Swiss AI Lab IDSIA (2015) and positions at Salahaddin University and Czech Technical University further enriched his expertise. Research interests span Quality Assurance of machine learning systems, software testing methodologies, trustworthy AI, IoT system reliability, and optimization algorithms. He has pioneered frameworks like PatrIoT for IoT testing and contributed to MLOps robustness. His work integrates machine learning with anomaly detection, adaptive systems, and industrial applications. Recent articles highlight advancements in data-driven heat pump management, MLOps robustness, and edge-cloud AR/VR optimization. Collaborations include projects on digital twins, smart manufacturing, and industrial IoT. His contributions bridge theoretical research with practical industrial solutions, emphasizing system reliability and AI ethics.