جستجوی استاد راهنمای دانشگاهی

Tommy Löfstedtمشاهده پروفایل

دانشیار

• Machine Learning
• Computer Vision
• Medical Image Analysis
• +۴ مورد دیگر

Tommy Löfstedt is an Associate Professor at Umeå University , affiliated with the Department of Computing Science and the Department of Mathematics and Mathematical Statistics. His research focuses on machine learning , computer vision , and medical image analysis , with applications in life sciences, radiation therapy, and biomedical imaging. He leads multiple research projects, including AI-driven delineation in radiation therapy, quantitative MRI for radiotherapy, and machine learning for plant nutrient uptake. Current research emphasizes structured regularization methods to improve model interpretability and robustness. Key applications include medical image segmentation , Alzheimer's classification , and uncertainty estimation in MRI . Recent publications highlight his work on morphological regularization , adversarial attack mitigation , and multi-task learning in medical imaging contexts. His projects span 2022–2026 with funding for pediatric oncology automation and gynecological cancer staging. Affiliated with both computing and mathematical departments, he bridges algorithm development with applied mathematical frameworks in medical and life science domains.

Jens Carlssonمشاهده پروفایل

استاد

• G protein-coupled receptors (GPCRs)
• Structure-based drug design
• Molecular docking
• +۷ مورد دیگر

Jens Carlsson is a Professor at Uppsala University, affiliated with the Department of Cell and Molecular Biology and the Science for Life Laboratory (SciLifeLab) . His research focuses on computational biochemistry , particularly G protein-coupled receptors (GPCRs) , using physics-based modeling to advance structure-based drug design . Academic rank: Full Professor (since 2022) Key methodologies: Molecular dynamics simulations, docking, free energy calculations Research themes: GPCR ligand interactions, virtual chemical space screening, allosteric modulators Recent work (2025) highlights AI-driven discovery of brain disease therapeutics and DNA repair inhibitors , while 2024 projects explore AlphaFold applications in TAAR1 agonist design . His group has received Swedish Research Council grants (3.6M SEK, 6M SEK) and industry collaborations . Scientific awards include the Göran Gustafsson Prize (2016), Excellence Prize in Molecular Design (2022), and Ingvar Carlsson Award (2012). Key students include PhD candidates Mariama Jaiteh and Pierre Matricon , with postdocs like Nicolas Panel and Duy Duc Vo .

• Population Genetics
• Human Evolution
• Genomics
• +۶ مورد دیگر

Professor Mattias Jakobsson is a faculty member at Uppsala University's Department of Organismal Biology (Human Evolution), holding a PhD and Docent title. His research focuses on population genetics, human evolution, and genomic analysis of modern and ancient human populations. Jakobsson leads a lab using computational methods to study genomic variation, migration patterns, and adaptation in Stone Age Eurasia and sub-Saharan Africa. Key projects include investigations into hunter-gatherer populations, plague infections in Neolithic farmers, and genetic continuity in Scandinavia. Education: PhD (exact field unspecified), Docent Lab: Jakobsson Lab (website: jakobssonlab.iob.uu.se ) Research interests emphasize applying genomic data to understand human migration, admixture, and adaptation. Recent work highlights studies on HLA diversity in Thai hunter-gatherers, ancient European genetic shifts, and plague dynamics in Neolithic communities. Collaborations span global archaeological and genomic projects.

Andrea Fossatiمشاهده پروفایل

استادیار

• Bacterial Defense Systems
• Phage Biology
• Virology
• +۵ مورد دیگر

Andrea Fossati is a DDLS Fellow and Principal Investigator at Karolinska Institutet, leading the Fossati Lab at SciLifeLab. His research focuses on bacterial defense systems and phage biology, utilizing interaction proteomics and machine learning to develop novel strategies against antibiotic-resistant bacteria by disabling bacterial immunity during phage-bacterial warfare. Dr. Fossati's work centers on discovering bacterial defense mechanisms and phage counter-defense systems through advanced proteomic techniques like DIP-MS and quantitative interaction mapping. His lab integrates systems biology and machine learning to analyze host-pathogen interactions, with emphasis on jumbo phage infection mechanisms and lipid compartment formation. This research directly targets the enhancement of phage therapy efficacy by tilting the evolutionary balance toward phages. His publication trends reveal deep specialization in virology and microbiology, with dominant themes in bacterial immunity, phage-bacteria interactions, and proteomic methodology development. Over 80% of recent work involves jumbo phages and defense system characterization, while computational frameworks like PCprophet demonstrate cross-disciplinary integration of machine learning. Scientific awards: DDLS Fellow Dr. Fossati actively mentors the next generation of scientists, currently supervising two PhD students and collaborating with three postdoctoral researchers. His DDLS fellowship provides substantial research funding enabling cutting-edge instrumentation for proteomic analysis and high-throughput screening of phage-bacterial interactions, with recent grants focusing on quantitative interaction mapping and defense system discovery. The Fossati Lab operates within SciLifeLab's national infrastructure, maintaining close collaborations with leading proteomics and virology groups across Europe. The team specializes in next-generation interaction proteomics, developing novel methodologies for complex deconvolution while maintaining strong computational biology capabilities for data analysis and machine learning applications in host-pathogen systems.

Olli-Pekka Kallioniemiمشاهده پروفایل

استاد

• Precision Cancer Medicine
• Functional Drug Testing
• Oncogenomics
• +۳ مورد دیگر

Olli-Pekka Kallioniemi is a Professor of Molecular Precision Medicine and Director of Science for Life Laboratory (SciLifeLab) at Karolinska Institutet. He leads the Precision Cancer Medicine research group within the Department of Oncology-Pathology, focusing on translational research to improve cancer treatment through ex vivo drug testing and multi-omics profiling. His work bridges laboratory discoveries with clinical applications, emphasizing actionable insights for personalized therapy. Research Interests: Dr. Kallioniemi’s group develops functional precision medicine approaches to identify therapeutic vulnerabilities in cancers like AML, ovarian, prostate, and renal cancers. Techniques include patient-derived 2D/3D cell models, organoids, and comprehensive genomic/drug-response profiling. Their work progresses through three translational phases: model feasibility (Phase I), representativity optimization (Phase II), and clinical actionability (Phase III). Selected Achievements: - Directed 75 million SEK in grants from the Swedish Cancer Society (2022) - Pioneered functional drug testing platforms for solid tumors and hematologic malignancies - Coordinated multi-institutional collaborations between Karolinska Institutet and the Institute for Molecular Medicine Finland Labs/Teams: His group operates at SciLifeLab (Stockholm) and the Institute for Molecular Medicine Finland (Helsinki), with sub-teams like the Functional Systems Oncology group led by Dr. Tom Erkers. Core personnel include postdoctoral researchers, PhD students, and clinical assistants.

• Population Genetics
• Human Evolution
• Ancient DNA
• +۲ مورد دیگر

Federico Sánchez Quinto is a Visiting Researcher at Uppsala University's Department of Organismal Biology, specializing in ancient DNA analysis and population genomics. His work bridges evolutionary biology, archaeology, and anthropology to investigate human prehistory through genomic evidence. His research focuses on Population Genetics, Human Evolution, and Archaeogenetics, with specific expertise in Neolithic Scandinavian populations, Denisovan ancestry in Southeast Asia, and prehistoric migration patterns. He examines how genetic adaptations, pathogen evolution, and social structures shaped ancient societies, integrating genomic data with archaeological context to reconstruct human history. Recent publications reveal trends in analyzing ancient pathogen genomes, kinship systems in megalithic tombs, and high-impact discoveries like the Philippine Ayta's exceptional Denisovan ancestry. His methodological contributions to ancient DNA imputation enhance analytical precision in population genomics, while cross-disciplinary studies on Philippine migrations and Scandinavian adaptations demonstrate his field's expanding scope. Based at Uppsala University's Evolutionary Biology Centre (EBC), he collaborates within multidisciplinary teams combining genomics, archaeology, and anthropology. His research leverages institutional resources at Norbyvägen 18 C to advance understanding of human evolution through cutting-edge ancient DNA methodologies.

Gemma Atkinsonمشاهده پروفایل

دانشیار

• Antibiotic resistance
• Bacteriophages
• Molecular evolution
• +۷ مورد دیگر

Gemma Atkinson is an Associate Professor at Lund University's Faculty of Medicine, leading the Atkinson Lab. She specializes in protein evolution and bioinformatics, focusing on antibiotic resistance, bacteriophages, and toxin-antitoxin systems. She manages LU-Fold, an infrastructure for high-throughput protein structure prediction using AlphaFold. Her research integrates computational tools with experimental methods to uncover microbial defense mechanisms. Key projects include developing bioinformatics tools (e.g., LoVis4u, webFlaGs) and investigating phage defense systems. She leads grants from the Swedish Research Council and the Knut and Alice Wallenberg Foundation. Her lab collaborates internationally, contributing to UN Sustainable Development Goals on health and innovation. Publications highlight advancements in toxin-antitoxin systems, antimicrobial peptides, and ribosome function. The lab's tools are widely used globally, aiding researchers in structural and functional genomics analysis.

Marc Hellmuthمشاهده پروفایل

دانشیار

• Discrete Mathematics
• Combinatorics
• Graph Theory
• +۱۰ مورد دیگر

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.

• Microbiology
• Bioinformatics
• Molecular Microbiology
• +۵ مورد دیگر

Magnus Fagerlind is a Senior Lecturer in Bioscience at the School of Bioscience, Department of Biosciences, University of Skövde. He serves as Deputy Head of Division and coordinates advanced-level courses in biosciences. His research spans Microbiology , Bioinformatics , and Systems Biology , focusing on bacterial pathogenesis, biofilm dynamics, and molecular mechanisms. Recent work includes genotyping of Escherichia coli and Klebsiella in sepsis, alongside computational models of quorum sensing in Pseudomonas aeruginosa . Key methodologies: Computational modeling, Next-generation sequencing, Bioinformatics pipelines Applications: Clinical microbiology, Reproductive biology, Educational technology His publications reflect interdisciplinary collaborations in infectious disease research, immunology, and pedagogical innovation. While no explicit awards or advisees are listed, his contributions to research and education at the University of Skövde demonstrate sustained academic engagement.

• Scientific Visualization
• Data Analysis
• Medical Applications
• +۶ مورد دیگر

Ingrid Hotz is a Professor in Scientific Visualization at Linköping University, affiliated with the Department of Science and Technology (ITN) and the Center for Medical Image Science and Visualization (CMIV). She holds a Master's in Theoretical Physics from Ludwig Maximilian University (Munich) and a PhD in Computer Science from the University of Kaiserslautern. Her research focuses on data analysis and scientific visualization, spanning applications in fluid dynamics, medical imaging, and large-scale simulations. She has led research groups at the Zuse Institute Berlin (2006–2013) and the German Aerospace Center (DLR, 2013–2015). Her work integrates methods from computer graphics, computational geometry, and topology. Key research areas include multi-field visualization, topological data analysis, and scalable systems for ocean data exploration. She has contributed to software tools like VIAMD and pyParaOcean. Notable collaborations include material science research (e.g., beryllonitrene synthesis) and large-scale conference organization (Eurographics 2020, attracting 23,000 participants). Her research bridges theoretical foundations with practical applications in medicine, engineering, and environmental science. Publications highlight advancements in visualization techniques for molecular dynamics, medical imaging, and climate modeling. She actively participates in interdisciplinary projects, such as predicting liver steatosis dynamics and developing frameworks for analyzing brain activity via fMRI data. Her work emphasizes bridging gaps between computational methods and real-world scientific challenges.

Jussi Taipaleمشاهده پروفایل

استاد

• Gene regulation
• Transcription factors
• Systems biology
• +۴ مورد دیگر

Jussi Taipale is a Professor of Medical Systems Biology at Karolinska Institutet and holds professorships at University of Helsinki. His research focuses on transcription factor binding mechanisms , cancer genomics , and gene regulatory networks . The interdisciplinary Taipale Lab operates across three international locations: Wellcome Sanger Institute (UK), Karolinska Institutet (Sweden), and University of Helsinki (Finland), with over 20 members including senior scientists, postdoctoral fellows, and graduate students. Ph.D., University of Helsinki (1996) Postdoctoral training: University of Helsinki, Johns Hopkins University Research spans transcription factor cooperativity , epigenetic regulation , chromatin accessibility , and noncoding mutation analysis . Key methodologies include HT-SELEX , CUT&RUN , ATI assays , and CRISPR-based functional genomics . The lab has significantly advanced understanding of Myc-driven oncogenesis , TF-nucleosome interactions , and dinucleotide specificity mechanisms . Notable discoveries include chromatin context-dependent enhancers , water-mediated DNA recognition , and novel composite transcription factor motifs . The group maintains active collaborations across Europe and has trained numerous alumni now leading academic and industry positions worldwide.

Nicholas Pearceمشاهده پروفایل

استادیار

• Structural Biology
• Macromolecular Structure Determination
• X-ray Crystallography
• +۷ مورد دیگر

Nicholas Pearce is an Assistant Professor at Linköping University, affiliated with the Department of Physics, Chemistry and Biology (IFM) and the Bioinformatics (BIOIN) division. He leads the Data-Driven Determination of Macromolecular Structures (D3MS) group, also known as PearceLab @ LiU, and is affiliated with SciLifeLab and the Wallenberg Centre for Molecular Medicine (WCMM) through the Data-Driven Life Sciences (DDLS) program. His research focuses on advancing structural biology by developing computational and experimental methods that capture the dynamic nature of proteins. Key interests include protein flexibility, disorder, and functional dynamics, with applications in drug discovery and macromolecular modeling. The group employs techniques such as X-ray crystallography, cryo-EM, machine learning, and statistical modeling to improve the resolution and interpretability of macromolecular structures. The recent publications highlight a strong focus on software and method development for structural biology, particularly in multi-dataset analysis and crystallographic data processing. The work contributes to open-source tools like the CCP4 suite and introduces novel approaches such as PanDDA and PanDEMIC.adp for detecting ligand binding and modeling disorder. While no formal scientific awards are listed in the provided text, his involvement in major collaborative projects and national research initiatives underscores his growing impact in the field. He actively mentors students and welcomes Master’s candidates to join his research group. Nicholas began his independent research career at Linköping University on October 1, 2022, with funding supporting the launch of his lab. His group emphasizes data-driven decision-making in structural analysis and collaborates extensively within Sweden and internationally. Current projects include multi-dataset analysis for fragment screening and decomposition of protein disorder using elastic net models. The D3MS group is active in outreach and scientific communication, maintaining a blog and public presence, including a Twitter feed. They have participated in international research visits, such as a recent trip to the University of Hamburg, and national conferences like Sweprot in Tällberg.

Torsten Güntherمشاهده پروفایل

پژوهشگر

• Population Genomics
• Ancient DNA
• Human Evolution
• +۵ مورد دیگر

Torsten Günther is a Researcher at Uppsala University's Department of Organismal Biology, holding a PhD and the Swedish academic title of Docent. His work bridges evolutionary biology, archaeology, and genomics through cutting-edge analysis of ancient DNA from human and animal specimens across Europe, Africa, and the Middle East. His research focuses on reconstructing population histories using paleogenomic data, with particular expertise in human migration patterns, domestication processes of livestock (especially sheep and cattle), and methodological innovations in archaeogenomics. Recent work examines vanished hybrid zones in Saharan rock doves, genomic legacies of aurochs hybridization in Iberian cattle, and Neolithic transitions in Northwest Africa. His interdisciplinary approach integrates archaeological context with high-resolution genomic analysis to address fundamental questions about human prehistory and evolutionary adaptation. Analysis of his 15 most recent publications (2023-2025) reveals three dominant research strands: 1) Livestock domestication genomics (sheep, cattle, mouflon), 2) Human population dynamics during critical transitions (Neolithic, Bronze Age), and 3) Methodological advances in ancient DNA analysis. His collaborative network spans over 20 institutions across Europe and North America, with fieldwork concentrated in Mediterranean and Atlantic European regions. Günther frequently publishes in high-impact journals including Nature , Science , and eLIFE , demonstrating significant influence in archaeogenomics. He maintains active research leadership through methodological software development (READv2) and participation in major international consortia studying ancient human and animal genomes. His work consistently addresses how historical demographic processes shaped modern biodiversity and human genetic variation, with implications for conservation biology and understanding human adaptation.

• Nanotechnology
• Surface Chemistry
• Biophysics
• +۷ مورد دیگر

John Andersson is a Researcher at the Department of Applied Chemistry, Chalmers University of Technology, working in the research group of Prof. Andreas Dahlin. His research focuses on nanotechnology, surface chemistry, and biophysics, with expertise in polymer brushes, nanopores, nanofabrication, and advanced characterization techniques like SPR and AFM. He holds a doctoral degree (2022) on polymer brush coatings for nanoscale devices. Research Interests: Functionalization of nanopores for biomolecule trapping Surface plasmon resonance sensing applications Thermoresponsive polymer networks Interdisciplinary approaches to biomolecular manipulation His publications (19 total) demonstrate contributions to nanoscale device development, biomolecular interaction studies, and advanced material characterization. Key techniques include solid-state nanopore engineering and SPR-based sensing systems. Currently affiliated with Chalmers' Applied Chemistry division, he collaborates on projects involving biomimetic nanopore systems and surface-functionalized nanomaterials.

Trung Nghia Vuمشاهده پروفایل

پژوهشگر

• Bioinformatics
• Computational Biology
• Cancer Genomics
• +۵ مورد دیگر

Trung Nghia Vu is a Principal Researcher at the Department of Medical Epidemiology and Biostatistics at Karolinska Institutet in Stockholm, Sweden. His research group focuses on developing and applying statistical and bioinformatics methods for molecular biology and medicine, with particular emphasis on cancer genomics and pharmacogenomics. Dr. Vu received his PhD from the Department of Mathematics and Computer Science at the University of Antwerp, Belgium (2009-2014), following an MSc in Computer Engineering from Korea Aerospace University (2006-2008) and a BSc in Technology from Vietnam National University in Hanoi (2000-2004). His research focuses on developing statistical and bioinformatics methodologies for analyzing high-throughput omics data, with specific interests in single-cell sequencing analysis, characterization of cancer omics, and pharmacogenomics. His group has developed 20 statistical and bioinformatics tools available through Biostat Wiki Primary research areas include gene/isoform quantification, detection of abnormal RNAs, single-cell RNA-seq analysis, and drug response prediction Current projects focus on breast cancer and Acute Myeloid Leukemia (AML) Analysis of Dr. Vu's recent publications reveals a strong focus on cancer genomics, particularly in AML and breast cancer. His work bridges computational biology with clinical applications, developing methods for spatial transcriptomics, drug synergy prediction, and circular RNA analysis. The research demonstrates a clear trajectory toward precision medicine applications, with increasing emphasis on personalized drug response prediction and pathway activation modeling. Dr. Vu actively supervises multiple students and researchers, including both completed PhD students (Quang Thinh Trac, Lu Pan, Wenjiang Deng) and ongoing supervisees (Gulser Caliskan, Meghana Alugunoolla, Yuying Li, Aron Arzoomand). His research is supported by significant grants from the Swedish Research Council, CancerFonden, and Karolinska Institutet. He leads the Computational Medicine and Bioinformatics research group at Karolinska Institutet, which collaborates with international clinical and systems-biology researchers. The group maintains active development of bioinformatics tools and maintains the Biostat Wiki platform for academic use. Dr. Vu also contributes to teaching through master's and doctoral courses in biostatistics and R programming at Karolinska Institutet.