جستجوی استاد راهنمای دانشگاهی

Jaakko Akola is a Professor in the Department of Physics at the Norwegian University of Science and Technology (NTNU). His research focuses on computational materials science, particularly density functional theory (DFT) and atomistic simulations of materials, nanoparticles, molecules, and interfaces. He leads significant projects such as "SIDI" (inoculation in cast iron), "Infinity-RETIS" (chemical rare events), and "AllDesign" (rational alloy design), alongside coordinating EU-funded initiatives like "CritCat" for catalyst development. The Materials Theory group under Akola employs DFT, molecular mechanics, and Monte Carlo methods to explore atomic-scale structures and functions in technological applications. Key research areas include platinum-free catalysts for hydrogen energy, amorphous semiconductors for memory devices, noble metal nanoparticles in biological environments, and alloy design for cast iron and aluminum. Recent work integrates machine learning to advance theory-driven material design, reducing reliance on experimental trial-and-error. Akola's publications highlight advancements in hydrogen evolution catalysis, phase-change memory materials, and alloy precipitation. His projects often involve interdisciplinary collaborations with experimental teams. He teaches Quantum Physics 1 (FY2045) and Computational Physics (TFY4235) at NTNU, reflecting his commitment to education alongside research.

• Computational Physics
• Density Functional Theory (DFT)
• Atomistic Simulations
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Ingrid Hobæk Haff is an Associate Professor in insurance mathematics and statistics at the Department of Mathematics, University of Oslo since 2015. She holds a master's degree in Industrial Mathematics from NTNU (2002) and a PhD from the Statistics for Innovation center (2008–2012), with a 20% position as a research scientist at the Norwegian Computing Centre. Previously, she worked there as a research scientist and senior scientist. Her research interests focus on multivariate statistics, copulae, skew and heavy-tailed distributions, and applications in insurance and finance. She has contributed to advancements in statistical modeling, particularly in copula constructions and their applications to risk assessment and extreme value analysis. Key awards include the Sverdrup award for young scientists and the mathematical award of Hanna og John Olav Stubban . She is affiliated with the Statistics and Data Science research group and the completed Stochastics of Renewable Energy Markets (STORE) project. Her work spans interdisciplinary collaborations, including applications in immunology and bioinformatics, leveraging machine learning for antibody-antigen interaction studies and synthetic data generation.

• Multivariate statistics
• Copulae
• Skew distributions
• +۳ مورد دیگر

Victor Greiff is a Professor at the University of Oslo's Institute of Clinical Medicine , leading the Computational and Systems Immunology group. His research focuses on integrating high-throughput single-cell sequencing , artificial intelligence , and high-dimensional statistics to advance therapeutic antibody design, diagnostics, and vaccine development for infectious diseases, autoimmunity, and cancer. Key Research Areas : Computational immunology, adaptive immune receptor repertoires, machine learning in antibody discovery, bioinformatics, structural biology, and immune diagnostics. Funding : European Research Council (ERC) Grant AB-AG-INTERACT (Project ID: 101125630). Recent Publications highlight interdisciplinary work in: Machine learning for antibody design and immune repertoire classification . Structural analysis of antibody-antigen interactions and evolutionary immunogenetics . Development of bioinformatics tools (e.g., ExpoSeq, TCRpower, CompAIRR) for immune sequencing data analysis. Scientific Contributions include: Establishing computational frameworks for synthetic immune repertoire generation. Exploring genetic constraints on TCR and BCR diversity. Advancing AI-driven antibody engineering for improved therapeutic developability.

• Computational Immunology
• Adaptive Immune Receptor Repertoires
• Machine Learning in Antibody Design
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Sebastian Georg Zieglmeier is a Research Fellow at the University of Oslo's Faculty of Mathematics and Natural Sciences, affiliated with the Section for Autonomous Systems and Sensor Technologies. His research focuses on advanced control systems, energy systems, and machine learning applications such as reinforcement learning and deep learning. He explores modeling techniques for autonomous power systems and data-driven control strategies. His recent publications emphasize RNA engineering, therapeutic applications, and immunogenicity reduction in vaccines. Key areas include RNA purification, lipid-based formulations, and cancer-targeted agents. Zieglmeier's work bridges biotechnology and engineering, with contributions to molecular diagnostics and vaccine development. While no specific grants or awards are noted, his research aligns with cutting-edge technologies in mRNA therapeutics and autonomous systems. He is based at the University of Oslo's Institute of Transport Economics (ITS) and contributes to interdisciplinary projects at the Faculty of Mathematics and Natural Sciences.

• Control Systems
• Data-driven Control
• Energy Systems
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Dag Trygve Truslew Haug is a Professor at the Department of Classics at the University of Oslo, specializing in Greek and Latin linguistics with a focus on syntax and computational approaches. His research bridges classical philology with modern computational linguistics, particularly through treebank development and semantic analysis. His primary research interests include: Greek and Latin grammatical structures Lexical-Functional Grammar and formal semantics Computational linguistics and treebank development Historical linguistics and syntactic change Semantic annotation frameworks Morphological tagging systems His recent publications demonstrate a strong focus on computational linguistics applications for classical languages, semantic parsing methodologies, and the development of linguistic resources for Norwegian. The work shows consistent innovation in formal semantics, corpus linguistics, and interdisciplinary applications in computational biology. He leads the DAMOS project (Database of Mycenaean at Oslo) and participates in multiple research groups including Digital Humanities, Grammar and Meaning, Language Change, Linguistics and Poetics, Pragmatics: Theory & Experiments, and Super Linguistics.

• Syntax
• Formal Semantics
• Computational Linguistics
• +۵ مورد دیگر

Beathe Kiland Granerud is an Assistant Professor at the Department of Nursing, Health and Laboratory Science at Østfold University College. She holds a BSc in Biomedical Science, an MSc in Medical Microbiology, and is pursuing a PhD in Clinical Virology at the University of Oslo. Her academic roles include teaching medical microbiology, ethics, communication, and molecular biology. She has extensive industry experience as a biomedical scientist, laboratory engineer, and study program leader for the Biomedical Laboratory Science program. Her research focuses on medical microbiology (particularly highly pathogenic microbes), antibiotic resistance, infection immunology, bioinformatics, and pedagogical strategies in biomedical education. Recent work has centered on SARS-CoV-2 variants, host immune responses, and clinical outcomes in severe COVID-19 cases. Granerud has contributed to over 15 peer-reviewed articles since 2013, analyzing topics like Omicron/Delta variant comparisons, complement activation in infections, and predictive analytics for patient outcomes. Her studies often involve multinational collaborations, such as the ISARIC-COVID-19 dataset initiative. Her teaching emphasizes practical skills in biomedical laboratory practices and ethical considerations in science. She has advised no formally documented students but actively contributes to curriculum development and laboratory training programs. Labs/Teams: Collaborates with institutions like the Norwegian Institute of Public Health and University of Oslo on virology and microbiology research. Active in pandemic response initiatives through clinical and bioinformatics studies.

• Medical Microbiology
• Antibiotic Resistance
• Infection Immunology
• +۳ مورد دیگر

Tone Berge is a Professor at Oslo Metropolitan University's Faculty of Technology, Art and Design, Department of Mechanical, Electrical and Chemical Engineering. Their research focuses on neurology, medical immunology, medical genetics, and molecular biology with specific interest in multiple sclerosis (MS), T cells, vitamin D, and autoimmunity. 2025: Professor, OsloMet 2023: Major publications in Journal of Neurology and Journal of Neuroimmunology 2022: Nature Communications correction for systems biology approach in MS research Research trends show heavy emphasis on: Systems biology approaches to MS pathogenesis Immune cell subpopulation analysis in MS progression Vitamin D receptor binding in T cells Neurofilament light chain biomarkers Gene regulation in autoimmune responses Machine learning applications in MS severity prediction

• Neurology
• Medical Immunology
• Medical Genetics
• +۶ مورد دیگر

Anne Margarita Dyrhol Riise is a Professor at the Department of Infectious Diseases , University of Oslo and Oslo University Hospital. Her research focuses on translational studies of major global infectious diseases including HIV, tuberculosis, and COVID-19, emphasizing clinical intervention studies, vaccines, immune mechanisms, and diagnostic/prognostic biomarkers with applications in low-income countries and personalized treatment strategies. Head of the Chronic Infections Research Group (CIRG) Principal investigator for EU Horizon 2020 projects and ClinicalTrials.gov studies (NCT04575519, NCT05069623) Supervisor for eight PhD students Recent projects include the SMA-TB stratified medicine algorithm, TBCOX2 therapeutic vaccination trials, and EU-SolidAct pandemic response platform. Collaborations span multiple institutions including Norwegian Institute of Public Health, Stellenbosch University, University of Leiden, and international networks like EUROSIDA and TBnet. Awards include OUS Prize for Outstanding Research Articles (2021) and UiO Teaching Award. Her work demonstrates strong integration of clinical trials, immunology, and global health initiatives, with publications spanning topics from complement activation in severe COVID-19 to host-directed therapies in tuberculosis .

• Infectious Diseases
• Translational Research
• HIV
• +۷ مورد دیگر

Jan Terje Andersen is a Professor in the Department of Pharmacology at the University of Oslo, Faculty of Medicine, and is affiliated with Oslo University Hospital. He leads the Laboratory of Adaptive Immunity and Homeostasis, focusing on the molecular mechanisms of IgG and albumin, particularly through the neonatal Fc receptor (FcRn), with applications in drug delivery, immunotherapy, and infectious disease. His research bridges fundamental immunology and translational biotechnology innovation. His research interests center on antibody engineering , albumin-based therapeutics , and immune regulation . Key areas include FcRn biology, antibody half-life extension, mucosal immunity, and intracellular antiviral defense via TRIM21. His lab investigates how molecular modifications can enhance the pharmacokinetics and biodistribution of biologics, enabling less frequent dosing and improved patient outcomes. His work also explores novel vaccine platforms and antibody technologies for cancer and infectious diseases. The recent publications highlight a strong trend in protein engineering for improved pharmacokinetics , particularly through FcRn engagement, and translational applications in oncology, virology, and autoimmune disorders. There is a consistent focus on pH-dependent binding, antibody developability, and innovative delivery systems, including mucosal and oral routes. His scientific awards include: Fridtjof Nansen Prize for Early Career Achievements Oslo University Hospital Early Career Award Member of The Young Academy of Norway Andersen actively mentors researchers and leads a highly innovative lab with extensive collaborations with biotech and pharmaceutical companies. His lab is recognized as the most innovation-productive at the University of Oslo and Oslo University Hospital through Inven2. He is involved in advising on drug development, translational research, and fostering innovation in academia. His laboratory explores therapeutic concepts in vaccine design, autoimmune disorders, and targeted delivery systems, with a strong emphasis on real-world applicability.

• Immunology
• Molecular Biology
• Antibody Engineering
• +۹ مورد دیگر

Enrico Riccardi is an Associate Professor in Computational Engineering at the Department of Energy Resources, Faculty of Science and Technology, University of Stavanger (UIS), Norway. His work bridges computational chemistry, machine learning, and multi-scale modeling, with applications in energy, environmental science, and biophysics. Research Interests: His core expertise lies in molecular dynamics , rare event simulation methods (e.g., reaction kinetics and adsorption), and multi-scale modeling from molecular to continuum levels. He is a key developer of path sampling methodologies and software such as PyRETIS and PyVisA , enabling the study of slow and rare processes in complex systems. His research spans interfacial phenomena in emulsions, membrane permeation, atmospheric chemistry, and data-driven discovery of reaction pathways using machine learning. Recent Publication Trends: Over the past decade, Riccardi has consistently published in high-impact journals such as Journal of Chemical Physics , Physical Chemistry Chemical Physics , and Nature Machine Intelligence . His recent work (2023–2025) shows an expanded scope into educational technology , environmental science , and open-source tool development (e.g., GeoSight), reflecting a growing interdisciplinary impact. The publications reveal a strong focus on algorithmic innovation in simulation methods and their application across chemistry, biology, and engineering. Scientific Contributions: Lead and co-developer of PyRETIS, a widely used open-source library for rare event simulations. Contributor to immuneML, a machine learning ecosystem for immune repertoire analysis published in Nature Machine Intelligence . Active in promoting open science, data sharing, and academic integrity through public commentary and educational initiatives. Advising and Grants: While no formal students are listed in the provided text, Riccardi has mentored or collaborated with numerous early-career researchers and PhD candidates, particularly within the van Erp group. He has contributed to multiple collaborative research projects, likely funded by Norwegian and European research councils, though specific grants are not mentioned. His outreach on postdoctoral challenges suggests engagement with academic policy and mentorship. Labs and Teams: Riccardi is part of a vibrant computational research group at UIS, closely collaborating with Prof. Titus Sebastiaan van Erp and colleagues in the Department of Energy Resources. His work is embedded in a team focused on advanced simulation techniques, with strong ties to international networks in computational chemistry and soft matter physics.

• Molecular Dynamics
• Machine Learning
• Rare Event Simulation
• +۷ مورد دیگر

Jaya Kumari Swain serves as an Associate Professor at the Norwegian Fisheries College, UiT The Arctic University of Norway, specializing in fish immunology and vaccinology. She leads research within the Fish Immunology and Vaccinology group, with primary focus on Atlantic salmon health. Her research interests span Host-pathogen interactions , Molecular Immunology , T-cell immunity , Vaccinology , and Novel delivery methods . Key areas include salmon lice control mechanisms, viral pathogenesis in cardiac tissues, and AI-driven diagnostic approaches for aquatic diseases. Recent publications reveal a strong trend toward translational vaccinology (particularly for salmon lice and viral pathogens) and advanced imaging techniques (ultrasound/photoacoustic microscopy). Her work increasingly integrates artificial intelligence with traditional immunology, focusing on functional changes in embryonic hearts post-infection and 3D tissue visualization. No scientific awards are listed in available records. Dr. Swain coordinates multiple research projects including VirtualStain (AI solutions for label-free tissue imaging), DNA Vaccine Development for Salmon Viruses , and Sterilization of Atlantic salmon with Deadend nanomaterials . Her teaching portfolio includes Fish Diseases (BIO-2604), Pathology (BIO-2605), and specialized modules in aquaculture health courses. She actively collaborates within the Fish Immunology and Vaccinology research group, contributing to both fundamental immunology studies and applied aquaculture solutions through projects like Antisense delivery for large-scale sterilization.

• Host-pathogen interaction
• Molecular Immunology
• T-cell immunity
• +۳ مورد دیگر

Geir Kjetil Ferkingstad Sandve is a Professor at the Biomedical Informatics Research Group within the Department of Informatics (UiO), University of Oslo, specializing in machine learning methodology for biomedical applications. His research focuses on Generalization in machine learning models Exploiting mechanistic/causal domain relations Software platforms for domain-adapted ML Multiple-instance learning techniques Historical work in statistical genome analysis and motif discovery His recent publications (2022-2025) demonstrate expertise in Adaptive immune receptor repertoire analysis Antibody-antigen interaction prediction Proteome scoring systems for celiac disease Causal modeling in biomarker generalization Multi-modal single-cell data integration Synthetic dataset generation for immunology He leads a computational research group prioritizing Reproducible codebases and software development Competence-building through strategic research Interdisciplinary collaboration with biomedical teams Training in algorithmic challenges and software design

• Machine Learning
• Bioinformatics
• Immunology
• +۳ مورد دیگر