جستجوی استاد راهنمای دانشگاهی

Dr. Nils Morten Kriege is an Associate Professor at the Faculty of Computer Science, University of Vienna, where he leads the Data Mining and Machine Learning research group. Previously, he served as Assistant Professor (2020-2023) at the same institution and held positions at TU Dortmund including Interim Professor (2019/2020) and Postdoctoral Researcher (2015-2020). His research focuses on graph-based machine learning methods with applications in cheminformatics and drug discovery. His educational background includes a Doctorate in Computer Science (2015) and Diploma in Computer Science (2009), both from TU Dortmund. He has also been a Visiting Researcher at the University of York, UK. Dr. Kriege's research centers on graph algorithms and machine learning with graphs, particularly focusing on graph neural networks, graph kernels, and their applications in cheminformatics and drug discovery. His work bridges theoretical computer science with practical applications, developing novel methods for graph similarity, graph classification, and network analysis. He has made significant contributions to understanding the expressivity and robustness of graph neural networks, as well as developing efficient algorithms for graph similarity search and molecular analysis. His recent publications (2023-2025) demonstrate a strong focus on graph neural networks, with particular attention to their expressivity, robustness against attacks, and practical applications in drug discovery. His work spans theoretical foundations (Weisfeiler-Leman hierarchy, graph isomorphism testing), practical implementations (efficient quantization, defense frameworks), and domain-specific applications (cheminformatics, drug discovery). Vienna Research Groups for Young Investigators (2019) - €1,466k funding for "Algorithmic Data Science for Computational Drug Discovery" Member of the Global Young Faculty V, Stiftung Mercator (2017) Dr. Kriege leads an independent research group funded through the Vienna Research Groups for Young Investigators program, focusing on computational drug discovery. He has served on program committees for major conferences including NeurIPS, ICML, IJCAI, AAAI, ICLR, and ICDM, and has reviewed for prestigious journals such as Transactions on Pattern Analysis and Machine Intelligence. His teaching portfolio includes courses on Data Mining, Graph Learning, and Introduction to Machine Learning. He leads the Machine Learning with Graphs work group within the Data Mining and Machine Learning Research Group at the University of Vienna, collaborating with researchers like Wilfried Gansterer and Petra Mutzel on graph-based methods for drug design and molecular analysis.

• Data Mining
• Machine Learning with Graphs
• Combinatorial Optimization
• +۵ مورد دیگر

Martin Nöllenburg is a Full Professor in the Department of Algorithms and Complexity at TU Wien, Vienna University of Technology. He holds roles as Curriculum Coordinator for the Bachelor and Master’s programs in Theoretical Informatics and Algorithms and Complexity. His research focuses on algorithm engineering, computational geometry, graph algorithms, and information visualization. He leads projects such as 'Parameterized Graph Drawing' and 'Human-Centered Algorithm Engineering', funded by WWTF and FWF. His research interests span algorithm design, graph drawing, and visualization techniques for networks and biological systems. Recent work includes advancements in boundary labeling, graph bundling, and metro map visualization. He has supervised over 20 graduate students, producing impactful contributions to visualization and algorithmic research. Key contributions include the development of GDmetriX (a NetworkX extension for graph metrics) and studies on dynamic map labeling and combinatorial optimization. He actively participates in academic governance, serving on TU Wien’s Faculty Council and Curriculum Commission.

• Computer Science
• Algorithm Engineering
• Computational Geometry
• +۷ مورد دیگر

Henry Ehlers is a PreDoc Researcher and PhD Candidate at the Vienna University of Technology (TU Wien), working within the Faculty of Informatics, Institute of Visual Computing & Human-Centered Technology, specifically in the Computer Graphics Group (E193-02). He holds the position of University Assistant (Univ.Ass.) and is actively pursuing his doctoral studies under the supervision of Renata Raidou since 2021, with expected completion in 2024. His research focuses on advanced visualization techniques, particularly in the areas of network and graph visualization. Ehlers specializes in biological network visualization, compound graphs, uncertainty visualization, and data physicalization. His work bridges theoretical computer science with practical applications in visual analytics, creating innovative methods for representing complex network structures and making them accessible to domain experts. Analysis of his publication record reveals a strong emphasis on improving network visualization techniques, with particular focus on biological applications, uncertainty representation, and physical data representations. His research trajectory shows increasing sophistication in addressing visualization challenges across multiple domains including biology, environmental science, and social networks. Recent publications demonstrate his leadership in developing novel interaction techniques and visualization metaphors for complex data structures. Ehlers is actively involved in multiple research projects including ArtVis (2022-2027), SANE (2024-2027), and SMGV-Esprit (2024-2027), which support his research in visualization techniques. His collaborative approach is evident in his extensive co-authorship network across international institutions and research groups at TU Wien. As a member of the Visualization Group led by Renata Raidou, Ehlers contributes to the team's mission of developing innovative visualization solutions for complex data challenges. His work particularly focuses on creating more intuitive and effective ways to represent network structures through both digital and physical means, pushing the boundaries of how we interact with complex relational data.

• Network Visualization
• Graph Visualization
• Biological Network Visualization
• +۵ مورد دیگر

Paola Bovolenta is a Research Professor at the Spanish National Research Council (CSIC) - Universidad Autónoma de Madrid (UAM), with international recognition in Developmental Neurobiology. She has held leadership roles including Chair of the Tissue and Organ Homeostasis Program (2019–present) and former Chair of the Development and Differentiation Department (2012–2019). Her research spans: Mechanisms of visual axon sorting at the chiasm Morphogen signaling in eye development Neuroinflammation in Alzheimer's disease ADAM10-SFRP1 interactions in neurodegeneration Interdisciplinary approaches to life sciences Recent publications highlight her work on zebrafish models for optic cup morphogenesis, neuroinflammatory crosstalk in Alzheimer's, and synthetic biology applications. Awards include EMBO membership (2012), two Fundaluce Awards (2009, 2012), and ERC Scientific Council membership (2017). She has mentored 21 PhD students (4 ongoing) and 20 postdocs, with active involvement in European research policy through the ERC Open Science Working Group and UE Core Group on Reform of Research Assessment.

• Developmental Neurobiology
• Neuroinflammation
• Neurodegeneration
• +۶ مورد دیگر

Kärin Nickelsen serves as Full Professor (W3 Chair) in History of Science at Ludwig Maximilian University of Munich's Department of History since 2011, following progressive appointments as Associate and Assistant Professor at University of Bern (2002-2011). Her scholarly profile integrates historical analysis with philosophical inquiry across biological sciences, emphasizing collaborative knowledge production and methodological frameworks within scientific communities. Education: Ph.D. in History & Philosophy of Science, University of Bern (2002, summa cum laude) Diploma in Biology, University of Göttingen (1999, with distinction; Botany, Microbiology, History of Science) Research Focus: Professor Nickelsen's work critically examines the epistemological foundations of biological research through historical case studies, particularly investigating how experimental practices, visual representations, and institutional contexts shape scientific understanding. Her scholarship reveals intricate connections between theoretical frameworks and material practices in fields ranging from photosynthesis research to space life-support systems, with special attention to socio-political influences on scientific development during periods like the Nazi era. Publication Analysis: Her 15-year publication trajectory demonstrates deepening engagement with 20th-century biological sciences, evolving from foundational studies of botanical illustration to complex analyses of photosynthesis controversies and space technology history. A unifying thread involves tracing knowledge transfer across disciplinary boundaries while examining how scientific collectives generate and validate knowledge under varying historical constraints. Honors: Member of Bavarian Academy of Sciences (2020) Leopoldina Academy Committee for Life Sciences (2019) Dalberg Award for transdisciplinary research (2010) Caspar Friedrich Wolff Medal (2010) Wilhelm Dettmering Award for Young Scholars (2002) Academic Leadership: As Co-opted Member of LMU's Centre for Advanced Study (2017) and active participant in international committees, Nickelsen facilitates cross-disciplinary research initiatives while mentoring emerging scholars through her departmental leadership role. Her collaborative projects with institutions like Max Planck Institute demonstrate sustained engagement with experimental history of science methodologies.

• History and philosophy of the modern biological sciences
• Practices of natural history
• Methodology of the experimental sciences
• +۲ مورد دیگر

Thomas Rath is a Senior Scientist at the Institute for Chemical Technology of Materials (ICTM) at Graz University of Technology, Austria. He holds a PhD in Industrial Chemistry and has conducted postdoctoral research at Imperial College London and within the Christian Doppler Laboratory for Nanocomposite Solar Cells. His work focuses on organic and hybrid solar cells, particularly lead-free perovskite systems and solution-processable nanomaterials. His research integrates X-ray scattering , interface engineering , and photovoltaic performance analysis . Key projects include PorM@S (FWF) and HALOMAT (Horizon Europe). He has co-authored over 80 peer-reviewed articles, emphasizing non-fullerene acceptors , semiconductor synthesis , and device stability . Major collaborations span Imperial College London , TU Graz , and FFG-funded initiatives . Current efforts target biocompatible solar cells , crystallization mediators for tin perovskites, and multifunctional energy systems combining storage and conversion. His 2025 publications highlight advancements in fluorene-based acceptors and nickel sulfide synthesis .

• Organic Solar Cells
• Hybrid Solar Cells
• Perovskite Solar Cells
• +۴ مورد دیگر

Stefan Badelt holds a PhD and Magister degree in Theoretical Chemistry, currently active within the Faculty of Chemistry at an Austrian institution (likely University of Vienna based on academic conventions). His research spans computational RNA biology, bioinformatics, and molecular engineering with continuous publication output from 2011 through projected 2025 activities. RNA Folding (100%) Protein Secondary Structure (67%) Transcription Processes (45%) Circular RNA Mechanics Alu Element Biology His research focuses on cotranscriptional RNA folding dynamics, developing computational tools like DrForna for visualization and DrTransformer for heuristic folding prediction. Recent work critically examines deep learning limitations in RNA structure prediction while advancing nearest-neighbor energy models. His fingerprint reveals strong specialization in RNA polymerase II dynamics and non-pseudoknotted structural systems. Publication trends show consistent output in high-impact bioinformatics journals, with 2022-2023 featuring significant algorithmic contributions. His work bridges computational methods with experimental validation, particularly in RNA folding pathways and DNA strand-displacement systems. While no specific awards are documented, his publications demonstrate substantial scholarly impact with multiple papers exceeding 10 Mendeley readers and significant citation metrics. Badelt actively mentors students through collaborative projects, evidenced by co-authored publications with Laurenz Miksch and others. His research receives support through computational biology grants enabling development of tools like the commit-and-delay model for RNA dynamics. Future work includes domain-level design of cotranscriptional folding pathways presented at upcoming 2024-2025 conferences. He operates within the Theoretical Chemistry research ecosystem, collaborating closely with Ivo Hofacker's group on RNA bioinformatics. Current activities focus on exact coarse-grained dynamics modeling and pseudoknot-free pathway design, positioning his lab at the intersection of computational biology and molecular engineering.

• RNA Folding
• Computational Biology
• Bioinformatics
• +۳ مورد دیگر

Lena Bauer is a researcher affiliated with the Faculty of Computer Science at the University of Vienna, specifically within the Research Group Data Mining and Machine Learning . Her work bridges computational methods with neuroscience, focusing on applications in mental health. She holds degrees including DI Dr.techn. (PhD in Technical Sciences) and BSc. Research Interests: Bauer’s research integrates machine learning and data mining techniques to analyze complex biological systems, particularly brain networks. She explores multimodal data integration, clustering algorithms, and their application to neuroimaging (e.g., fMRI) for understanding disorders like Major Depressive Disorder. Key themes include quantifying neural synchronization, developing autoencoder-based models, and improving clustering methodologies. Collaborations: Bauer collaborates internationally on projects involving computational neuroscience and mental health. Recent activities include presenting work on Kuramoto model applications to fMRI data at conferences. Labs & Teams: She contributes to the University of Vienna’s Data Mining Group, which focuses on clustering, causality analysis, and big data applications.

• Machine Learning
• Computational Neuroscience
• Data Mining
• +۳ مورد دیگر

Guido Caldarelli is a Full Professor of Theoretical Physics at Ca' Foscari University of Venice , with affiliations at CNR-ISC, IMT Lucca, and the London Institute for Mathematical Sciences (LIMS). His career spans roles including President of the Complex Systems Society (2018-2020), co-founder of the Network Science Society, and director of CNR-ISC. Active in interdisciplinary research, he bridges statistical physics, network science, and applications in finance, urban planning, and biomedicine. PhD in Condensed Matter Physics, SISSA Trieste (1996) MPhil in Physics, SISSA (1994) Physics Degree, Sapienza Rome (1992) Guido's research focuses on complex systems and network theory , particularly in financial networks, urban dynamics, and biological systems. His work explores scale-free networks, systemic risk, and entropy-based models, with applications in digital twins for cities, microbiome analysis, and misinformation spread on social media. Recent publications highlight trends in network analysis for urban planning (green infrastructure), machine learning in NMR spectroscopy, and social media dynamics during political events. His interdisciplinary approach connects theoretical physics to practical challenges in healthcare, finance, and climate resilience. Scientific Awards Honorary ISI Fellow APS Fellow (2020) Member of Academia Europaea (2020) Fellow of the Network Science Society Outstanding Service Prize, Network Science Society (2020) Guido leads the Complex Networks group at CNR-ISC, co-founded Catchy s.r.l. (data-driven innovation), and serves on the Scientific Committee for Italian Police Force training . His work integrates theoretical rigor with real-world impact across disciplines.

• Complex Systems
• Network Theory
• Financial Networks
• +۲ مورد دیگر

Dr. Jessica Huss is a Postdoctoral Research Fellow at the Institute of Biophysics, Department of Natural Sciences and Sustainable Resources, University of Natural Resources and Life Sciences (BOKU), Vienna. She currently holds an FWF-ESPRIT Postdoctoral Fellowship (2022-2025) focusing on adaptations for fog and dew harvesting in cactus spines and has previously worked as a PostDoc at BOKU Vienna (2019-2021). Her educational background includes: Doctoral studies in Materials Sciences (summa cum laude), Technical University Berlin (2015-2019) Master of Science in Environmental Sciences/Biomaterials and Bioenergy, University of Freiburg, Germany (2012-2015) Bachelor of Science in Environmental Sciences/Meteorology and Climatology, University of Freiburg, Germany (2009-2012) Dr. Huss's research is multidisciplinary, focusing on the biological development, properties, and adaptations of hard plant tissues. Her work spans biomechanics, Raman and IR spectroscopy, x-ray microtomography, and fire ecology. She investigates how plant structures like nutshells and cactus spines achieve remarkable mechanical properties through their unique cellular architectures and material compositions, with applications in biomimetic materials design. Her publication record shows a consistent focus on plant biomechanics and materials science, particularly examining walnut shells, Banksia follicles, and cactus spines. Her research reveals how nature creates strong, protective structures through innovative cellular arrangements and material compositions, with applications in biomimetic materials design. Her scientific awards include: Best Paper Award, Jubiläumsfonds der Stadt Wien für die Universität für Bodenkultur (2021) Promotionspreis für Nachwuchswissenschaftlerinnen, Fakultät III (Prozesswissenschaften), TU Berlin (2021) Poster Award Prize by Deutsche Gesellschaft für Materialkunde e.V. and Springer-Verlag GmbH, EURO Bio-inspired 2016, Potsdam, Germany (2016) Grant for a short term scientific mission (COST Action FP1105); granted by the European Cooperation in Science and Technology (2013) Dr. Huss has supervised three Master's theses on topics related to walnut shells and sustainable composites. She currently leads the FWF-funded project 'Adaptations for fog and dew harvesting in cactus spines' (2022-2025) and previously contributed to the EU-funded 'Scattering and tapping on soft-hard-open nuts' project (2016-2021). Her work has been featured in media outlets including Die Presse and science.apa.at. Her research connects with several interdisciplinary teams including collaborators at the Max Planck Institute of Colloids and Interfaces, where she worked as a Guest Scientist (2019-2020), and international partners across Europe and North America, as evidenced by her presentations in Poland, France, Germany, Israel, Thailand, the UK, and the United States.

• Botany
• Materials Chemistry
• Spectroscopy
• +۶ مورد دیگر

Dr. Maciej Jakub Pelak is a Physician Scientist in the Department of Radiotherapy and Radiation Oncology at Paracelsus Medical University in Salzburg, Austria. His research focuses on advanced radiation therapy techniques, particularly particle therapy applications for various cancers. He maintains an active research profile with publications spanning from 2009 to 2025. Dr. Pelak's research interests center on ion therapy, with particular expertise in carbon-ion and proton therapy for treating head and neck cancers, skull base tumors, and mucosal melanoma. His work investigates relative biologic effectiveness, radiation therapy optimization, and the clinical outcomes of particle therapy. He has made significant contributions to understanding the application of PET/CT in particle therapy planning, particularly for tumors with somatostatin receptor expression. His publication record shows a clear trend toward clinical applications of particle therapy, with increasing focus on quality of life outcomes, treatment planning optimization, and comparative analyses of different radiation modalities. Recent work emphasizes patient-centered outcomes alongside technical advancements in radiation delivery. Dr. Pelak serves as a peer reviewer for prominent journals including the International Journal of Radiation Oncology Biology Physics and Frontiers in Oncology, demonstrating his standing in the radiation oncology community. His research has been referenced across multiple platforms including news outlets, policy sources, and academic social networks.

• Radiation Oncology
• Particle Therapy
• Neoplasms
• +۳ مورد دیگر

Johannes Kirchmair is a Professor in the Department of Pharmaceutical Sciences at the Faculty of Life Sciences. His research focuses on computational methods in drug discovery, particularly virtual screening, machine learning applications, and understanding drug metabolism. He is actively involved in projects such as the Anti-Infectives Drug Discovery initiative and the AIDD: Advanced Machine Learning for Innovative Drug Discovery program. His work addresses challenges in toxicity prediction, enzyme inhibition, and assay interference detection. Key areas include cytochrome P450 metabolism, small molecule drug design, and natural product analysis. Research interests span virtual screening methodologies, metabolite identification, and computational toxicology. He has contributed to the development of tools like E-GuARD for detecting assay interference and aweSOM for predicting metabolic sites. His collaborations emphasize cross-disciplinary approaches to advance drug discovery and chemical safety. He has delivered talks on computational methods for early drug discovery and assay interference prediction, reflecting his commitment to both academic research and practical applications. Current projects aim to leverage machine learning to tackle antimicrobial resistance and enhance drug development efficiency.

• Virtual Screening
• Cytochrome P450
• Small Molecule
• +۴ مورد دیگر

Dr. Filipa Sousa serves as Assistant Professor in the Department of Functional and Evolutionary Ecology at the University of Vienna's Faculty of Life Sciences, leading the Filipa Sousa Lab within the Archaea Biology and Ecogenomics Unit. Her research program integrates genomic, phylogenetic, and experimental approaches to investigate microbial evolution with emphasis on archaeal physiology, metabolic innovation, and bioenergetic transitions across Earth's history. The lab operates from room 3.042 at Djerassiplatz 1 in Vienna. Her primary research interests focus on the evolution of microbial metabolic strategies, particularly energy conservation mechanisms in Archaea. She investigates how carbon and energy metabolic systems evolved through protein complex modularity, gene fusions, and large-scale comparative genomics. Current work emphasizes automatic metabolic classification from genomic data, pan-metabolic profiling of Archaea, and reconstructing evolutionary pathways for sulfur and electron transport systems. Her group combines phylogenomics with experimental validation to bridge geological records and microbial physiology. Analysis of her recent publications reveals dominant trends in archaeal metabolism evolution, particularly dissimilatory sulfur reduction pathways and respiratory complex assembly. Her work increasingly integrates metagenomic data with phylogenetic modeling to reconstruct ancestral metabolic states, while developing computational tools for metabolic classification. Key themes include electron bifurcation mechanisms, horizontal gene transfer in metabolic innovation, and geochemical constraints on early bioenergetic systems. Major scientific recognition includes: ERC Starting Grant (2019-2025) for "Evolution of Physiology: The link between Earth and Life" WWTF Vienna Research Group Grant (2016-2025) for "Pan-metabolic profiling of Archaea: The Ecology of Genomics" Dr. Sousa actively supervises five graduate students across PhD and Master's programs while leading a 12-member research team. Her Vienna Doctoral School project "Microbial biotransformations in biogeochemical cycles" examines metal-based energy conservation in environmental microbes. She maintains significant collaborations with William F. Martin (Heinrich-Heine-Universität Düsseldorf) and Christa Schleper (University of Vienna), with funding supporting experimental work, computational analyses, and field studies in extreme environments. The Filipa Sousa Lab comprises Anwar Hiralal (PhD), Jordi Zamarreno Beas (PhD), Val Karavaeva (M.Sc.), Anastasiia Padalko (M.Sc.), Constantin Leitgeb (B.Sc.), and Marta Medic (B.Sc.). The team operates within the Archaea Biology and Ecogenomics Unit under Christa Schleper's departmental leadership, utilizing advanced genomic and bioinformatic infrastructure. Current projects integrate metagenomic data from diverse environments with phylogenetic modeling to reconstruct metabolic evolution, with particular focus on uncultivated archaeal lineages and their ecological roles.

• Microbial Evolution
• Archaea Physiology and Ecology
• Metabolic Evolution
• +۳ مورد دیگر

Wolfgang Maass is a Professor at the Institute of Machine Learning and Neural Computation at Technische Universität Graz . His research focuses on computational neuroscience, neuromorphic engineering, and machine learning, with an emphasis on understanding how biological neural networks process information and inspire artificial systems. He has contributed extensively to the development of spiking neural networks, synaptic plasticity models, and neuromorphic hardware. Education: Dipl.-Ing. (Diploma in Engineering), Dr.rer.nat. (PhD in Natural Sciences) Affiliations: Institute of Machine Learning and Neural Computation, TU Graz Key research interests include: Neural network models for cognitive functions Biologically plausible learning algorithms Neuromorphic computing and hardware implementations Computational principles of cortical microcircuits Recent work highlights the integration of biological principles into artificial intelligence, including studies on synaptic plasticity (BTSP), spiking neural networks for image recognition, and energy-efficient neuromorphic systems. His research bridges theoretical neuroscience and applied machine learning, with a focus on systems that emulate brain-like functionality. He has presented at major conferences such as the International Convention on the Mathematics of Neuroscience and AI and has authored over 200 publications. His work has been recognized for its interdisciplinary impact, advancing both neuroscience and AI fields.

• Neural Networks
• Machine Learning
• Computational Neuroscience
• +۳ مورد دیگر

Renata Raidou is an Associate Professor in Biomedical Visualization and Visual Analytics at the Research Unit of Computer Graphics, Institute of Visual Computing & Human-Centered Technology, TU Wien, Austria. She previously held positions at the University of Groningen and TU Wien as a postdoc. Her research focuses on medical visualization, uncertainty visualization, and data physicalization for healthcare applications. Raidou has received prestigious awards including the Dirk Bartz Prize (2017) and EuroVis Young Researcher Award (2022). She coordinates TU Wien's BSc in Digital Health and MSc in Medical Informatics. Education: PhD in Medical Visualization (Eindhoven University of Technology, 2017), MSc in Biomedical Engineering (TU Delft), Diploma in Electrical and Computer Engineering (NTUA). Professional Roles: Editorial Board member of Computer & Graphics , Steering Committee member of EG VCBM, and member of EASAC's AI in Healthcare working group. Research Interests: Medical visualization strategies for P4 medicine, anatomical edutainment through physicalization, and uncertainty-aware visual analytics in radiotherapy. Her work bridges visual computing, machine learning, and medical applications, emphasizing clinical decision support and public health education. Awards: Over 10 awards including Best Paper recognitions at IEEE Vis and EuroVis, and the EuroVis Best PhD Award. Her contributions span visualizing anatomical variability, ensemble data exploration, and interactive medical training tools. Grants & Projects: Leads the Health Virtual Twins project (2024–2028) for personalized stroke management. Active in interdisciplinary collaborations, including the Shonan Meeting on Formalizing Biological Visualization. Labs/Teams: Head of the Visualization Group at TU Wien, developing tools like Vologram (holographic medical data physicalization) and Slice and Dice anatomical crafts. Collaborates on edutainment systems and AI-driven healthcare visualization.

• Medical Visualization
• Visual Analytics
• Uncertainty Visualization
• +۳ مورد دیگر