Find Academic Supervisors

• Theoretical Computer Science
• Distributed Computing
• Approximation Algorithms
• +4 more

Mohit Daga is a Researcher at KTH Royal Institute of Technology, Sweden, specializing in theoretical computer science, distributed computing, and algorithmic research. He holds an MS in Computer Science from IIT Madras (2018). His current role involves research engineering and supervising master thesis projects across Machine Learning, AI, and GPU Programming. Education: MS in Computer Science, Indian Institute of Technology Madras (2018) Research Interests: His work focuses on distributed algorithms, approximation methods, and dynamic systems. He has explored applications in network analysis, optimization, and medical imaging. Recent projects include developing consensus protocols for DAG-based systems and analyzing multi-shot broadcast stability in distributed networks. Awards: Google Summer of Code Scholarship (2020) Advising & Grants: Supervised 9 master’s theses since 2020. Research internships include Cystar Labs (IIT Madras), IMDEA Networks Lab, and Xerox Research. His work on resource allocation at Xerox led to a patented solution. Labs/Teams: Contributed to projects at KTH’s Department of Computer Science and collaborated with IMDEA Networks and Cystar Labs. Part of the team developing the AciSpace CubeSat payload integration system.

• Numerical Analysis
• High-Performance Computing
• Parallel Computing
• +5 more

Carl C. Kjelgaard Mikkelsen is an Associate Professor at the Department of Computing Science, Umeå University. He specializes in numerical analysis and high-performance parallel computing, focusing on robust algorithms that cannot fail. He co-authored the StarNEig library for nonsymmetric eigenvalue problems and works on parallel constraint solvers for molecular dynamics and ultra-sparse linear systems. Research Interests: Numerical analysis, parallel computing, eigenvalue problems, linear systems, algorithm design. His recent publications emphasize robust task-based algorithms, GPU acceleration, and precision requirements in Newton's method. He teaches numerical analysis and scientific computing, emphasizing finite precision arithmetic and software documentation.

Helena LindgrenView profile

Professor

• Artificial Intelligence
• Human-AI Collaboration
• Sociotechnical Systems Design
• +5 more

Helena Lindgren is a Professor of Computer Science at Umeå University, specializing in Human-Centered AI and Human-AI Collaboration at the intersection of Artificial Intelligence , Interaction Design , and Cognitive Science . Her work focuses on developing intelligent and autonomous systems for healthcare through sociotechnical design principles. Department of Computing Science, Umeå University Founder of Interactive Intelligent Systems research group and Collaborative AI Lab (2010-2011) Co-developer of UMeHealth Lab for AI-based eHealth solutions Her research emphasizes: Digital Coaching for health behavior change Participatory Design of adaptive systems Formal Argumentation in human-AI dialogues Clinical Reasoning and knowledge representation Behavior Change Evaluation in aging populations Contextual Adaptation of AI systems Recent publications highlight socially intelligent agents , norm interpretation , and personalized digital coaching for seniors. She serves as Co-Director of Wallenberg Autonomous Systems, AI and Software Program - Humanities and Society (WASP-HS) and holds leadership roles in AI councils at Umeå University.

Jerry ErikssonView profile

Associate Professor

• Computer Science
• Computational Science
• Medical Imaging
• +5 more

Jerry Eriksson is an Associate Professor at the Department of Computer Science , Umeå University. He is also affiliated with the High Performance Computing Center North (HPC2N) at the same institution, focusing on computational methods and applications. Academic Rank : Associate Professor Primary Affiliation : Department of Computer Science, Umeå University Secondary Affiliation : High Performance Computing Center North (HPC2N) Email : jerry.eriksson@umu.se Dr. Eriksson's research spans interdisciplinary domains where computer science intersects with applied physics and network engineering . His work includes: Medical Imaging : Fluorescence optical tomography and electromagnetic shape tomography using advanced mathematical models Computational Methods : Implicit radial basis function techniques, Gauss-Newton optimization, and regularization schemes Network Engineering : Collision detection algorithms in wireless networks and peer-to-peer streaming protocols 3D Measurement : Bundle adjustment formulations for photogrammetry and robotics applications Article trends show a focus on applied inverse problems (2003-2017) with emphasis on: Medical imaging reconstruction algorithms Wireless network optimization techniques Geometric computing for 3D modeling Mathematical methods in computational engineering

Nina KhairovaView profile

Visiting Professor

• Computational Linguistics
• Machine Learning for Text Mining
• Misinformation Detection
• +2 more

Nina Khairova is a Visiting Professor at the Department of Computing Science , Umeå University, specializing in computational linguistics and responsible AI. Her research focuses on misinformation detection, machine learning for text mining, and the ethical implications of large language models (LLMs). She actively contributes to projects analyzing war-related news reporting and social media credibility during the Russian invasion of Ukraine. Projects: Human-AI Method for Detecting Misinformation in News Reporting on Russia’s Invasion of Ukraine Building Trust in Social Media: Assessing Credibility of Ukrainian Migration Information Her work involves multilingual dataset creation, semantic labeling, and AI algorithm integration for text analysis. Contact: nina.khairova@umu.se .

Vicenç TorraView profile

Professor

• Data Privacy
• Approximate Reasoning
• Decision Making
• +7 more

Vicenç Torra is a Professor at the Department of Computing Science, Umeå University, Sweden. He leads the NAUSICA: PrivAcy-AWare traNSparent deCIsions research group, focusing on artificial intelligence, data privacy, and approximate reasoning. His work bridges computer science and applied mathematics. Research Interests: Data Privacy (differential privacy, k-anonymity, secure multiparty computation) Approximate Reasoning (fuzzy sets, non-additive measures, Choquet integrals) Decision Making and Aggregation Operators Information Fusion and Clustering Recent Article Trends: His publications emphasize data privacy in machine learning, non-additive measure theory applications, and integrating privacy guarantees with mathematical rigor. 2024 works focus on Frechet manifold privacy and LLM knowledge distillation. Scientific Awards: EurAI Fellow (2010) ISI Elected Member (2013) IEEE Fellow (2017) Additional Contributions: Founder of Transactions on Data Privacy and MDAI conference series. Active in editorial boards of Fuzzy Sets and Systems, IEEE Transactions on Fuzzy Systems, and Information Sciences. Collaborates extensively with institutions in Japan and Spain.

• Cancer Genetics
• Tumor Evolution
• Neuroblastoma
• +4 more

Jenny Karlsson is a Researcher at Lund University, specifically working in the Department of Clinical Genetics and as part of the Lund University Cancer Center (LUCC). Her work focuses on the evolution of cancer cells, particularly in pediatric malignancies. Her research interests span multiple areas of cancer biology including tumor evolution, genomic instability, neuroblastoma, and childhood cancers. She investigates how cancer cells evolve spatially within tumors and how this evolution affects treatment response, particularly chemotherapy resistance. Her work combines molecular biology techniques with spatial mapping approaches to understand tumor heterogeneity. Analysis of her recent publications shows a strong focus on cancer evolution across different tumor types including neuroblastoma, Wilms tumor, and other childhood cancers. Her research consistently examines how genetic alterations drive tumor progression and treatment resistance, with particular attention to spatial heterogeneity within tumors. She frequently employs advanced genomic techniques including whole genome sequencing to track cancer cell evolution. Dr. Karlsson has supervised 3 research projects according to her profile and has established collaborations across multiple institutions as evidenced by her co-authorship on publications with international researchers. Her work contributes to understanding cancer progression mechanisms which has implications for developing more effective therapeutic strategies.

Anders ValindView profile

Researcher

• Tumor Heterogeneity
• Intra-tumor Evolution
• Somatic Mosaicism
• +5 more

Anders Valind is a researcher at Lund University's Department of Clinical Genetics and is affiliated with the Lund University Cancer Center (LUCC). Holding both MD and PhD degrees, he contributes to cancer research with a focus on tumor heterogeneity and evolution. His work spans multiple collaborative projects within the university's medical research ecosystem. Dr. Valind's primary research interests center on tumor cell heterogeneity and evolution within individual tumors, examining both biological mechanisms and clinical implications. His work particularly investigates intra-tumor evolution in genomic and clinical contexts, with additional focus on somatic mosaicism and its role in disease development. His research spans pediatric cancers, especially neuroblastoma and Wilms tumor, where he applies evolutionary biology principles to understand cancer progression and treatment resistance. His fingerprint analysis reveals strong expertise in Wilms' Tumor (100%), Aneuploidy (93%), Genetics (86%), Ganglioneuroblastoma (78%), Evolution (76%), Phylogeny (69%), Chromosome (60%), and Genetic Variation (52%). Analysis of his recent publications shows a consistent focus on tumor evolution across spatial domains, particularly in pediatric cancers. His work integrates genomic analysis with clinical observations to understand how tumors evolve during treatment, with particular attention to chemotherapy resistance mechanisms. The research demonstrates interdisciplinary approaches combining genomics, pathology, and clinical oncology to address fundamental questions about cancer progression. Oskar IIs stipendium (2018-04-16) Anna-Greta Crafoords pris (2018-04-12) Dr. Valind serves as a co-supervisor on doctoral projects including 'Phylogenetic analysis of pediatric tumors' (2020-2024) and 'Affektanfall i södra Sverige' studying demographics, diagnostics, and iron substitution treatment. He actively participates in LUCC activities, including the 'Clinical and Scientific Challenges' workshop scheduled for 2025. His collaborative network spans multiple research groups within Lund University, particularly connecting cancer genetics with clinical oncology. As part of the Lund University Cancer Center, Dr. Valind works within a multidisciplinary team focused on cancer genetics and tumor evolution. His research contributes to LUCC's mission of advancing cancer research through integration of basic science and clinical applications, particularly in the realm of pediatric oncology where understanding tumor evolution has direct implications for treatment strategies.

Johan SandbergView profile

Professor

• Digital Innovation
• Information Systems
• Organizational Transformation
• +3 more

Johan Sandberg is a Professor of Information Systems at the Swedish Center for Digital Innovation, Department of Informatics, Umeå University. He serves as Deputy Head of Department and focuses on digital innovation's impact on organizational models, with a specific emphasis on digital platforms and ecosystems. Affiliation: Swedish Center for Digital Innovation, Umeå University Editorial Board: Communications of the Association for Information Systems Key Research Areas: Digital platforms, ecosystem governance, organizational transformation His work explores tensions in digital policy calibration, resource optimization through digital twins, and institutional logics in public-sector transformation. Recent publications span topics like IoT-enabled process innovation, decelerated IT adoption, and modularity in IT infrastructure. He collaborates extensively with industry partners and leads research on digital entrepreneurship, platform establishment, and data-driven economies. The Swedish Center for Digital Innovation serves as a hub for his interdisciplinary research.

Viktor KaptelininView profile

Professor

• Human-Computer Interaction (HCI) Theory
• Activity Theory
• Affordances
• +5 more

Viktor Kaptelinin is a Professor at the Department of Informatics, Umeå University, Sweden. His research focuses on Human-Computer Interaction (HCI) theory, user research methods, and human-robot interaction. He is affiliated with Umeå University’s Department of Informatics and actively contributes to projects involving socially intelligent systems and IoT-enabled interaction design. Current academic rank: Professor Institution: Umeå University Department: Department of Informatics His research explores HCI theory through frameworks like Activity Theory and Existential Inquiry , analyzing how users engage with technologies in social and physical contexts. Key areas include human-robot interaction , affordances , and designing technology-enhanced activity spaces . Recent publications highlight trends in proactive social robotics , contextual framing , and stress management applications . His work spans robotic telepresence , ambient smart objects , and user-driven interaction design . Projects include: Digital Companions as Social Actors (2020–2026): Developing stress management systems using social robotics Mobile Remote Presence in IoT-enabled environments (2016–2019): Addressing interaction design challenges Viktor collaborates with researchers across Europe, contributing to workshops and conferences like CHI , HRI , and NordiCHI . His methodological focus includes low-fidelity prototyping , collaborative reflective rescaling , and empirical user studies .

• Dynamical Systems
• Number Theory
• Cryptography
• +3 more

Marcus Nilsson is a Lecturer in Mathematics at Linnaeus University's Faculty of Technology, where he focuses on teaching, research, and administrative responsibilities. He serves as the program manager for the Applied Mathematics program and vice dean for teacher education. Nilsson has taught at UC Berkeley, supported by the STINT Teaching Sabbatical program, and represents Linnaeus University on the National Committee for Mathematics at the Royal Academy of Sciences, addressing school collaboration issues. Teaching: Courses in discrete mathematics, number theory, and cryptography. Research: Specializes in dynamical systems, number theory, and cryptography, with external projects in information security. Commissions: Vice Dean for Teacher Education, project manager for Sonja Kovalevsky Days 2024-2025. Collaboration: Member of the International Center for Mathematical Modeling (ICMM), emphasizing interdisciplinary applications.

David LorenzView profile

Senior Lecturer

• English Linguistics
• Language Variation and Change
• Grammaticalization
• +5 more

David Lorenz is a Senior Lecturer and Associate Professor at Lund University's Centre for Languages and Literature, specializing in English Linguistics. His work spans language variation, grammaticalization, and phonetic reduction in spoken language. Teaching: Courses in English language, academic writing, and linguistic theory/methods. Research: Focus on usage-based language dynamics, corpus analysis, and experimental linguistics. Recent publications explore epistemic modality, multi-word sequences, and statistical modeling. Projects include CRMWSE (2022-2025) on language cognition and upcoming work on TikTok hate speech rhetoric (2025). Contact: david.lorenz@englund.lu.se | +46 76 720 10 15 | SOL:H317b, Lund University.

• Digital Human Modeling
• Ergonomics
• Virtual Reality
• +4 more

Estela Perez Luque is a researcher at the University of Skövde within the School of Engineering Science and Interaction Lab (ILAB) . She specializes in Digital Human Modeling (DHM) , ergonomics, and simulation-based design for automotive and industrial applications, with a focus on integrating human variability into engineering workflows. Affiliated with the INFINIT research environment and projects like ADOPTIVE (Automated Design & Optimization of Vehicle Ergonomics) and VIVA (Virtual Vehicle Assembler). Collaborates with Chalmers University of Technology and SAFER Vehicle and Traffic Safety Centre . Her research explores: Ergonomic simulation tools for automotive design Exoskeleton evaluation using DHM frameworks 3D body shape prediction models for standardized DHM manikins Eye-tracking in VR for understanding motor redundancy Biomechanical reference points in vehicle packaging design Publications demonstrate expertise in multi-objective optimization for balancing ergonomics and productivity, statistical modeling of human variability, and VR validation for experimental setups. Funded by the Knowledge Foundation , Vinnova , and Swedish industry partners. Her work emphasizes open-source contributions, including MATLAB scripts for body shape prediction and validation protocols for VR eye-tracking. She collaborates with international teams at conferences like DHM 2025 and IEA 2021 .

• Manufacturing Engineering
• Laser Welding
• Digital Twin Technology
• +6 more

Wang Wei is a researcher at the University of Skövde's School of Engineering Science. His work spans multiple domains including manufacturing processes, laser welding, digital twin applications, and sustainable supply chain strategies. Key affiliations: University of Skövde, The Virtual Systems Research Centre, SYMBIO-TIC project, VF-KDO project Collaborations with institutions: Nanjing University of Aeronautics and Astronautics, Innovation Fund Denmark, Vinnova Research interests focus on: Advanced manufacturing techniques (machining deformation prediction, thin-walled part optimization) Laser welding process improvement (porosity reduction, dissimilar material joints) Digital twin security frameworks for cyber-physical systems Green technology adoption and sustainable supply chain coordination Recent publications demonstrate expertise in: Neural operator applications for manufacturing Multi-objective optimization in machining Cybersecurity modeling for industrial systems Environmental economics and consumer behavior analysis Co-funded by: Knowledge Foundation (SIMPLE, VF-KDO projects) Vinnova (QWELD, LaserBATMAN projects) EU H2020 SYMBIO-TIC M-ERA.NET 3 call

• Applied Computational Science
• Industrial Bioeconomy
• Radiative Transfer
• +3 more

Per Edström is a Professor at Mid Sweden University, affiliated with the Department of Engineering, Mathematics and Subject Didactics (IMD). His research spans applied computational science and industrial bioeconomy, with a focus on developing strategies for a Swedish circular bioeconomy and solving real-world problems through simulations and modeling. Current Role: Professor, Department of Engineering, Mathematics and Subject Didactics (IMD) Research Focus: Applied Computational Science, Industrial Bioeconomy Key Contributions: Advanced simulation tools for light scattering in paper/printing, parameter estimation methods for radiative transfer, and cross-border collaboration frameworks Edström's research emphasizes computationally efficient solutions for industrially relevant problems, particularly in the paper industry. His work includes modeling light scattering, fluorescence, and optical properties of materials, with applications in printing, coating, and paper production. He has developed mathematical tools like the DORT2002 method and open-source platforms for optical simulations. Scientific awards: None explicitly documented.