جست‌وجوی استاد و پژوهشگر

Monika Dörflerمشاهده پروفایل

استاد

• Applied Harmonic Analysis
• Audio Signal Processing
• Machine Learning
• +۳ مورد دیگر

Monika Dörfler is a Professor in the Department of Mathematics at the University of Vienna. Her research focuses on applied harmonic analysis, audio signal processing, and the mathematics of machine learning. She specializes in time-frequency analysis, nonstationary Gabor frames, and deep learning applications in audio processing. Dörfler has contributed significantly to methods like the invertible constant-Q transform and has explored the intersection of convolutional neural networks with signal representation theory. Affiliations: Department of Mathematics, University of Vienna Roles: Professor, Privatdozent, Principal Investigator (PI) in grants including WWTF Hertha Firnberg and SALSA projects Teaching: Courses such as Applied Analysis and Bachelor seminar Her research interests emphasize both theoretical foundations and practical applications of signal processing techniques. Notable contributions include work on Gabor frames in deep scattering networks and orthogonal projections for dimension reduction in learning problems. Dörfler has received awards for her papers, including Best Paper Awards at ISMIR19 and DAFx-11, and has organized international conferences like SAMPTA19 and DAFx2020. Awards: Best Paper Gold (DAFx-11), ISMIR19 Award, WWTF Grant Leadership Grants: Co-PI in aMOBY (Acoustic Monitoring of Biodiversity), PI in Audio-Miner and Hertha Firnberg grant Her work addresses challenges in audio denoising, music information retrieval, and algorithmic biases in recommendation systems. Ongoing projects include "Filter them all! Gabor theory for image quality assessment" submitted to FWF in 2023.

• Statistics
• Data Analysis
• Applied Mathematics
• +۳ مورد دیگر

Daniel Constantin Rademacher is a researcher at the Institute of Statistics, Graz University of Technology (TU Graz), with expertise in statistical analysis and modeling. He holds a Dr.rer.nat. degree, indicating a doctorate in natural sciences, alongside a BSc and MSc in related fields. University: Graz University of Technology Department: Institute of Statistics His research focuses on core statistical domains including: Probability theory Stochastic processes Statistical modeling Data analysis techniques Applied mathematics Quantitative methods

• Statistics
• Data Analysis
• Stochastic Processes
• +۳ مورد دیگر

Peter Scheibelhofer is a researcher at the Institute of Statistics, affiliated with the Technical University of Graz. His work focuses on statistical methodologies and their applications in various domains. Research Interests : Statistics Data Analysis Stochastic Processes Mathematical Modeling Probability Theory Computational Statistics

• Statistical Methods
• Machine Learning
• Materials Science
• +۵ مورد دیگر

Matthias Neumann is an Assistant Professor at the Institute of Statistics, Graz University of Technology . He completed his PhD in 2020 at Ulm University under Prof. Volker Schmidt, earning the PhD prize of Ulm University . His research focuses on stochastic 3D modeling and statistical analysis of micro- and nanostructures for functional materials, including battery electrodes , fuel cells , and paper-based materials . He has received start-up funding from ProTrainU (2020-2022) and served as principal investigator in the POLiS Cluster of Excellence (2022-2023). Research Interests: His work integrates mathematical morphology , machine learning , and spatial statistics to develop methods for microstructure quantification , estimation of geometrical descriptors (e.g., tortuosity, constrictivity), and data-driven models linking morphology to effective physical properties . He utilizes random fields , point processes , and copulas for virtual microstructure generation and parameter estimation. Teaching: He lectures on Applied Statistics , Statistical Modeling , and Mathematical Statistics at Graz University of Technology, with prior teaching experience at Ulm University in Multivariate Stochastic Modeling , Point Processes , and Spatial Statistics . Scientific Achievements: PhD prize of Ulm University (2020) ProTrainU start-up funding (2020-2022) POLiS Cluster of Excellence grant (2022-2023) Publications: His 15 most recent articles (2023-2025) emphasize machine learning techniques for microstructure segmentation , stochastic 3D modeling of nanoporous materials , and data-driven quantification of transport-property relationships . Key topics include random forests , neural networks , and R-vine copulas applied to fuel cells , sodium-ion batteries , and polymer electrolytes .

• Forest Growth
• Forest Monitoring
• Forest Inventory
• +۹ مورد دیگر

Arne Nothdurft is a University Professor for Forest Monitoring at the University of Natural Resources and Life Sciences (BOKU) in Vienna, Austria, where he chairs the Institute of Forest Growth within the Department of Forest and Soil Sciences. With a career spanning over two decades in forest research and academic leadership, he has established himself as a leading expert in advanced forest inventory techniques and forest growth modeling. Professor Nothdurft's research focuses on the application of cutting-edge technologies in forest monitoring, particularly LiDAR and personal laser scanning systems for forest inventory. His work bridges the gap between traditional forestry practices and modern digital solutions, with emphasis on mixed species forest management, climate change adaptation, and the development of smart forestry systems. His research interests encompass forest growth modeling, tree species classification using point cloud data, and the development of spatial prediction models for forest inventory parameters. His recent publications demonstrate a strong trend toward integrating artificial intelligence with forestry applications, particularly in the analysis of 3D point cloud data from laser scanning technologies. His work spans both theoretical advancements in spatial statistics and practical applications for forest managers, with a particular focus on improving the accuracy and efficiency of forest inventory systems. Thurn und Taxis Förderpreis für die Forstwissenschaft (2008) Professor Nothdurft has supervised numerous master's and doctoral theses, primarily focused on the application of laser scanning technologies in forestry, forest inventory optimization, and growth modeling. His research is supported by multiple ongoing projects funded by Austrian research agencies and federal ministries, with a strong emphasis on practical applications for forest management. He leads the Institute of Forest Growth, which maintains the Lehrforst Rosalia long-term forest monitoring site, and collaborates extensively with the Institute of Forest Engineering on smart forestry initiatives.

• Forest Resource Management
• LiDAR Technology
• 3D Point Cloud Analysis
• +۵ مورد دیگر

Andreas Tockner is a researcher at the Institute of Forest Growth, part of the Department of Ecosystem Management, Climate and Biodiversity at the University of Natural Resources and Life Sciences, Vienna (BOKU). He holds a Dipl.-Ing. and B.Sc. degree and is currently pursuing PhD studies since 2021 as part of the "Building Like Nature" program at BOKU University. His work focuses on applying advanced laser scanning technologies to forest resource management and inventory. Dr. Tockner's educational background includes a Diplom-Ingenieur (Dipl.-Ing.) and Bachelor of Science (B.Sc.) degrees. His PhD studies at BOKU University began in 2021 as part of the "Building Like Nature" program. He is actively developing expertise in software development for instance segmentation and feature extraction of 3D point clouds. His research interests center around forest resource management with a strong emphasis on ground-based laser scanning technologies, particularly mobile LiDAR systems. He specializes in software development for instance segmentation and feature extraction of 3D point clouds, which has significant applications in modern forest inventory and monitoring. His work bridges the gap between advanced geospatial technologies and practical forestry applications, enabling more precise and efficient forest management practices. He has developed expertise in analyzing forest structures through 3D point cloud data, with particular focus on tree species classification, forest regeneration monitoring, and timber measurement at individual log levels. Dr. Tockner's publication record reveals a clear progression toward increasingly sophisticated applications of laser scanning technology in forestry. His work has evolved from basic measurement techniques to complex analysis of forest ecosystems, including species identification, wood quality prediction, and even long-term forest projections using digital twin technology. His interdisciplinary approach combines forestry, computer science, and data analytics to solve practical challenges in forest management. Advancements in personal laser scanning for forest inventory Methods for tree species classification using intensity patterns Techniques for quantifying forest regeneration Digital twin applications for forest modeling and future projections Dr. Tockner has supervised two Master's theses in 2025: "Evaluierung boden-, luftgestützter und hybrider Methoden zur Forstinventur im Naturpark Sparbach" by Elias Kimmel and "Assessing the Potential of Personal Laser Scanning to Quantify Tropical Tree Structures" by Luca Stephan Seiler. His research is supported by multiple projects including "Lidar based forest monitoring and harvesting planning" (2023-2026) funded by Federal Ministries and "Forest Inventory with Personal Laserscanners" (2022-2025) funded by the Austrian Research Promotion Agency (FFG). He is actively involved in developing practical applications of laser scanning technology for forest management, with a particular focus on making these technologies accessible for field operations. His work on using Apple iPad Pro with integrated LiDAR technology demonstrates his commitment to practical, field-deployable solutions that can transform traditional forest inventory practices.

Matthias Stefanمشاهده پروفایل

پژوهشگر

• Behavioral Economics
• Behavioral Finance
• Experimental Economics
• +۳ مورد دیگر

Matthias Stefan is a Researcher at the University of Innsbruck , affiliated with the Department of Banking and Finance . His work bridges Behavioral Economics and Finance , utilizing experimental methods to explore decision-making complexity. As a coordinator for the Innsbruck Decision Sciences research center, he emphasizes collaborative innovation and methodological transparency. Research Focus: Behavioral Economics & Finance Decision-Making Biases Risk Preferences Choice Architecture Delegation Dynamics Market Ethics Methodological Expertise: Specializes in laboratory and online experiments , with recent work addressing reproducibility in management science and the interplay between monetary/social incentives. His publications reveal a pattern of investigating decision-making frameworks across finance, portfolio allocation, and supply chain contexts. Collaborative Vision: Expresses enthusiasm for cross-disciplinary cooperation, particularly through crowdsourcing hypothesis testing and transparent experimental design. His research trajectory suggests growing emphasis on methodological rigor and scientific integrity in behavioral finance.

Henning Detersمشاهده پروفایل

پژوهشگر

• EU Judicial Politics
• EU Environmental Policy
• EU Climate Policy
• +۳ مورد دیگر

Henning Deters is a political scientist and researcher at the University of Vienna's Centre for European Integration Research (EIF), part of the Faculty of Social Sciences. He holds a PhD from Bremen International Graduate School of Social Sciences. His primary research focuses on EU judicial politics, environmental policy, single market policy, and computational analysis. Deters has held roles including Assistant Professor at the University of Innsbruck and postdoctoral researcher in FWF-funded projects on EU judicial appointments. He has taught courses on EU regulatory policies and European integration at multiple institutions. Education includes a Diplom degree in Political Science from Universität Bremen and an MA from BIGSSS. His work combines qualitative and quantitative methods, with recent emphasis on computational approaches. Notable publications analyze EU policy dynamics in areas like the Posted Workers Directive, climate governance, and judicial politics. He actively contributes to academic discussions through blogs like Regioparl and maintains a focus on EU institutional transformations. His research highlights include examining the role of German regional parliaments in EU policymaking and analyzing the EU's Green Deal. Deters' current projects investigate judicial appointments at the Court of Justice of the EU and the politicization of legal challenges. His work bridges theoretical insights with practical data analysis, often using web-scraping and statistical methods. Key Positions: Postdoctoral Researcher (University of Vienna), Assistant Professor (University of Innsbruck), Research Associate (Danube University Krems) Teaching: Courses on EU policy, judicial politics, and European integration Awards: None explicitly listed, though his work has been peer-reviewed and published in top journals Labs/Teams: EIF Research Group, Regioparl Project

• Analytical Chemistry
• Food Safety
• Mycotoxins
• +۵ مورد دیگر

Rudolf Krska is a full Professor at the University of Natural Resources and Life Sciences, Vienna (BOKU), where he leads the Institute for Bioanalytics and Agro-Metabolomics in Tulln. His joint appointments include Professorships at Queen's University Belfast and Kansas State University. With a career spanning over three decades, he specializes in analytical chemistry, food/feed safety, and mycotoxin research. Research Focus: Krska's work centers on developing cutting-edge analytical methods (LC-MS/MS, infrared spectroscopy) for detecting contaminants in food chains. Key areas include: Mycotoxin control strategies and metabolomics of plant-fungi interactions Immunoassays, reference materials, and proficiency testing Climate change impacts on food contaminants and rapid on-site detection technologies Scientific Output: His recent publications (2024-2025) demonstrate a strong emphasis on spectroscopic mycotoxin detection, climate-related contaminant patterns, and global food safety challenges, particularly in vulnerable regions like Sub-Saharan Africa. Awards & Honors: Nils Foss Excellence Prize (2024), Chemistry Leader Award (2023) 5x Web of Science Highly Cited Researcher (2015-2019) Honorary Professor (China), Royal Irish Academy Membership Golden Ring of Tulln, Fritz-Pregl-Medal, and 20+ other distinctions Leadership & Projects: Krska directs major initiatives including FFoQSI's strategic research and EU projects like MyControl-ET. He founded two spin-offs (Biopure, Quantas Analytics) and oversees BOKU's analytical core facilities. Education & Training: Trained at TU Wien (Dipl.-Ing. 1990, Dr.techn. 1993), he mentors emerging scientists through international collaborations and laboratory management.

• Mycotoxins
• Mass Spectrometry
• Analytical Chemistry
• +۳ مورد دیگر

Franz Berthiller is an Associate Professor at the University of Natural Resources and Life Sciences, Vienna (BOKU), affiliated with the Department of Agricultural Sciences and the Institute of Bioanalytics and Agro-Metabolomics in Tulln an der Donau. His research specializes in mycotoxin analysis, mass spectrometry, and metabolomics, with a focus on developing advanced detection methods and understanding toxin metabolism in food/feed systems. He leads significant projects like the EU-funded BIOTOXDoc (2023–2027) and FWF-supported studies on modified fumonisins. Research interests include: Development of LC-MS/MS methods for mycotoxin quantification Metabolic pathways of trichothecenes and fumonisins Plant-fungal interactions affecting toxin production Biomarker discovery for contaminant exposure Multi-omics approaches in food safety Berthiller's recent publications emphasize metabolomics method optimization, environmental impacts on mycotoxin biosynthesis, and enzymatic modification of toxins. His work integrates analytical chemistry, molecular biology, and agricultural science to address food safety challenges. He directs a research group at the Institute of Bioanalytics and Agro-Metabolomics, collaborating internationally on projects related to mycotoxin management. No awards or supervised students are documented.

• Molecular biology
• Cell Biology
• genetics
• +۱ مورد دیگر

Dr. Angelina Sarah Groß is a researcher at the Institute for Molecular Plant Biology within the Department of Biotechnology and Food Sciences at the University of Natural Resources and Life Sciences, Vienna (BOKU). Based at Muthgasse 18, 1190 Vienna, she holds a Doctorate and Master of Science degree. Her work is documented through BOKU's Research Information System (FIS), with contact via angelina.gross@boku.ac.at and ORCID 0000-0002-8096-0831. Her research interests focus on molecular biology and cell biology as core disciplines, supplemented by genetics and biochemistry. These areas align with the institute's specialization in plant systems, exploring cellular mechanisms, genetic regulation, and biochemical pathways relevant to agricultural and environmental sciences. Teaching responsibilities include courses classified under Statistics Austria codes for these fields. Scientific awards: No honors, prizes, or fellowships are listed in her institutional profile. Dr. Groß supervises university theses, though no specific students appear in the database. Zero research projects are recorded in FIS, indicating either nascent activity or incomplete system entries. Grants and advising details remain undocumented in the provided data. She operates within the Institute for Molecular Plant Biology at BOKU, which investigates molecular processes in plants. The institute is part of a department dedicated to biotechnological and food science research, but no specific lab leadership or team structures are detailed for her role.

• Plant breeding
• Wheat genetics
• Disease resistance
• +۶ مورد دیگر

Hermann Bürstmayr is a University Professor at the University of Natural Resources and Life Sciences Vienna (BOKU), holding dual appointments at the Institute of Biotechnology in Plant Production and the Institute of Plant Breeding within the Department of Agricultural Sciences. With over 434 publications and numerous ongoing research projects extending to 2027, he maintains an active research program focused on improving cereal crops through advanced breeding techniques. Professor Bürstmayr's research interests center on developing disease-resistant wheat varieties, particularly targeting Fusarium head blight, common bunt, and other fungal pathogens that affect cereal crops. His work integrates traditional plant breeding with cutting-edge genomic approaches, including genome-wide association studies, genomic prediction models, and marker-assisted selection. His research spans fundamental genetic studies to practical breeding applications aimed at developing climate-resilient varieties with improved yield and quality traits. His recent publications demonstrate a strong focus on genomic selection for disease resistance, particularly against Fusarium head blight in both bread and durum wheat. His work increasingly incorporates AI and drone technology for field phenotyping, reflecting the digital transformation of plant breeding. His research addresses critical challenges in food security, including mycotoxin contamination reduction and adaptation to climate change impacts on crop production. Professor Bürstmayr has secured substantial funding from diverse sources including the Austrian Science Fund, European Commission, Austrian Research Promotion Agency, and industry partners. His projects often have international dimensions, with collaborations extending to Africa (Kenya, Ethiopia, Zimbabwe), Canada, and other global partners. He has supervised numerous theses and has been actively involved in knowledge transfer activities, including public lectures, media appearances, and participation in scientific conferences worldwide. His work bridges the gap between fundamental research and practical agricultural applications, with significant contributions to both scientific understanding and practical breeding solutions for cereal crop improvement.

• Biotechnology
• Bioprocess Engineering
• Enzymology
• +۴ مورد دیگر

Regina Kratzer is an Associate Professor at the Graz University of Technology , affiliated with the Institute of Biotechnology and Bioprocess Engineering . Her academic work focuses on advancing CO₂-based biotechnology, enzyme engineering, and sustainable bioprocessing techniques. Her research emphasizes: Bioprocess optimization for Cupriavidus necator cultivation CO₂ utilization in microbial systems Enzyme engineering for industrial applications Integration of reaction engineering with protein design Development of sustainable chemical production systems Analysis of microbial growth dynamics and substrate interactions Recent publications highlight trends in microbial CO₂ fixation, bioplastic production, and enzymatic reduction mechanisms. She maintains a focus on practical implementation of green biotechnology solutions. Contact: regina.kratzer@tugraz.at Location: Room BC01124, 8010 Graz, Petersgasse 10-12/I

• Artificial Intelligence
• Evolutionary Algorithms
• Machine Learning
• +۵ مورد دیگر

Lars Mehnen serves as a Senior Lecturer and Researcher at the University of Applied Sciences Technikum Wien (UAS Technikum Wien) in Austria, where he has been teaching since 2019 in Computer Science and previously from 2003-2019 in Biomedical Engineering. His academic career includes significant roles at Vienna University of Technology as University Assistant (2004-2007) and Research Assistant (1998-2002), along with leadership positions in major international space initiatives including QB50 (2010-2013), GENSO (2006-2010), and SSETI (1999-2006). TU-Wien: Dipl.Ing. in Computer Engineering and Medical Informatics Dr. Techn. from Institute for Fundamentals and Theory of Electrical Engineering and Institute of Technical Mathematics Mehnen's research spans multiple domains with particular expertise in Artificial Intelligence, Evolutionary Algorithms, and Sensor Technology. His work in explainable and non-parametric evolutionary algorithms represents cutting-edge contributions to AI methodology. In biomedical engineering, he has developed innovative magnetoelastic skin curvature sensors for cardiovascular monitoring and other medical applications. His teaching portfolio is exceptionally diverse, covering Statistics (parametric and non-parametric), Artificial Intelligence, Aerodynamics (particularly for sports equipment), Physics for game engineering, and extensive programming topics including Java, C/C++, Python, and functional programming languages. His publication record from 2001-2024 shows a clear evolution from early work on magnetostrictive bilayer sensors toward more recent applications of machine learning in biological classification, medical diagnostics, and educational technology. The 2024 publication on ChatGPT's diagnostic accuracy for medical conditions demonstrates his engagement with the latest AI developments. His research consistently bridges theoretical computer science with practical applications in healthcare, sports engineering, and space technology. Mehnen has been deeply involved in European collaborative projects throughout his career, including QB50 (EC F7), GENSO (ESA initiative), and B-Sens (EC-Project in 5th framework). These projects involved coordination with numerous universities and institutions across Europe, demonstrating his ability to lead international research collaborations. His work on the SSETI Express satellite project resulted in the successful launch of a micro-satellite at the end of 2005. At UAS Technikum Wien, Mehnen contributes to curriculum development across multiple domains including statistics, AI, programming, and physics. His research on paraglide control systems demonstrates application of his expertise to sports safety technology, while his recent work in teaching analytics shows commitment to improving educational outcomes through data-driven approaches.

Roberto Vivianiمشاهده پروفایل

دانشیار

• Clinical Neuroscience
• Functional Neuroimaging
• Emotion and Social Cognition
• +۳ مورد دیگر

Associate Professor Roberto Viviani, PhD is affiliated with the University of Innsbruck , where he leads neuroimaging research in clinical psychology. His work focuses on bridging psychopathology with brain function networks through functional neuroimaging, genetic variation, and statistical modeling. Research Interests : Functional neuroimaging of affective processes and social cognition Genetic polymorphisms in drug-metabolizing enzymes and their neurobiological effects Pharmacogenetics in polypharmacy and affective disorders Statistical analysis of neuroimaging data Development of tools like PHATE for high-dimensional data visualization Methodological Contributions : Advocates for multimodal imaging to enhance brain structure-function characterization Active in validating neuroimaging inference through advanced analytical techniques Grants : Recipient of a NEURON-Eranet grant for studying genetic influences on brain imaging endophenotypes. Collaborations : Engages in interdisciplinary projects, including AI-driven semantic similarity assessments and clinical applications of neuroimaging in depression, borderline personality disorder, and Parkinson's disease.