جست‌وجوی استاد و پژوهشگر

• Agricultural Science
• Plant Physiology
• Soil Health
• +۵ مورد دیگر

Prof. Hans-Peter Kaul is a Universitätsprofessor (full professor) in Plant Production at the University of Natural Resources and Life Sciences, Vienna (BOKU). His research focuses on crop management systems, precision agriculture, invasive species control, and sustainable soil management. He leads the iPBAU Plant Production department, with affiliations to bSKO Arbitration Commission and iFTEC Forestry Technology. His work integrates advanced technologies like AI-driven crop modeling and remote sensing with traditional agronomic practices. Key research interests include optimizing nitrogen use in intercropping systems, combating invasive plants like ragweed, and developing climate-resilient crop varieties. He has pioneered studies on energy efficiency in tillage systems and soil health in long-term experiments. His lab (DiLaAg) focuses on digitalization in agricultural sciences, emphasizing data-driven farming solutions. Recent publications emphasize AI applications in agriculture, soil-plant interactions, and crop yield prediction using radiative transfer models. He collaborates on projects like Farm/IT, enhancing farming resilience to climate risks through digital tools. His work addresses both ecological sustainability and agronomic productivity in Central European agroecosystems. Notable contributions include conceptual frameworks for agroecological transformation and studies on weed allelopathy. His research bridges basic plant science with applied farming practices, aiming to improve resource-use efficiency and biodiversity in agricultural landscapes.

Peter Kritzerمشاهده پروفایل

پژوهشگر

• High-dimensional algorithms
• Information-based complexity
• Quasi-Monte Carlo methods
• +۳ مورد دیگر

Peter Kritzer is a Senior Scientist and Scientific Coordinator at the Johann Radon Institute for Computational and Applied Mathematics (RICAM), Austrian Academy of Sciences in Linz, Austria. He holds a Master's degree (2003) and a Doctoral degree (2005, 'Sub Auspiciis Praesidentis') from the University of Salzburg, followed by a Habilitation in Mathematics (2012) from Johannes Kepler University Linz. His research focuses on high-dimensional algorithms, quasi-Monte Carlo methods, discrepancy theory, and information-based complexity. Affiliations: RICAM, Austrian Academy of Sciences (since 2015); previously at University of Salzburg, UNSW Australia, and Johannes Kepler University Linz. His work emphasizes numerical integration, tractability analysis, and algorithm design for high-dimensional problems. Notable contributions include advancements in lattice rules, digital nets, and hybrid function spaces. He has received awards such as the Information-Based Complexity Young Researcher Award (2011) and the Kardinal Innitzer Förderungspreis (2013). His recent articles explore topics like reduced digital nets, QMC matrix-vector products, and tractability in Hilbert spaces. He actively contributes to Monte Carlo and quasi-Monte Carlo research communities, editing volumes like Monte Carlo and Quasi-Monte Carlo Methods 2022 .

Dominik Leherbauerمشاهده پروفایل

پژوهشگر

• Energy Consumption
• Demand Side Management
• Energy Flexibility
• +۵ مورد دیگر

Dominik Leherbauer is a Researcher at the University of Applied Sciences Upper Austria, affiliated with the Research Center Wels, Center of Excellence for Energy, and Center of Excellence for Smart Production. His work focuses on Smart Mechatronics Engineering and energy-efficient industrial systems. His educational background includes a Bachelor of Science (BSc) and the Austrian academic title Diplom-Ingenieur (DI), equivalent to a Master of Engineering. Leherbauer's research specializes in optimizing industrial energy consumption through Demand Side Management, Energy Flexibility, and holistic production modeling. He develops model-based frameworks for quantifying electricity usage in manufacturing processes, with emphasis on polymer extrusion recycling and digital twin applications for aircraft component testing. His work directly supports UN Sustainable Development Goals for sustainable industry and clean energy. Recent publications reveal a strong trend toward integrating physics-based modeling with real-time industrial data to enhance energy-aware production systems. His 2025 systematic mapping study identified critical gaps in demand-side management for non-heavy industries, while subsequent works applied model-based systems engineering to mechanical recycling and aerospace testing. His scientific recognition includes: Beste mechatronische Masterarbeiten Österreichischer Fachhochschulen (2022) Beste Präsentation der Masterarbeit (2022) TÜV Austria Wissenschaftspreis (Kategorie Publikumspreis) (2022) Young Energy Researchers Award 2021 (2022) Leherbauer secured research funding through the EnerMan project (2021-2024) for energy-efficient manufacturing management and the BF-APPSDe project (2019-2020) for agile product-service system design. His work has generated significant media attention including coverage in Der Standard, Energie Star 2021, and Oberösterreicher des Tages. He operates within the university's Centers of Excellence for Energy and Smart Production, collaborating with international research teams on industrial energy flexibility solutions and model-based production optimization.

• Cyber-Physical Systems
• Runtime Verification
• Formal Methods
• +۵ مورد دیگر

Dejan Nickovic is a Professor affiliated with the Department of Cyber-Physical Systems at TU Wien. His research focuses on runtime verification, formal methods for cyber-physical systems (CPS), and software testing. He leads projects such as TAIGER (2023–2027) and ARTIST (2021–2026), advancing CPS safety and AI robustness. His work bridges theoretical formalisms with practical applications in robotics, IoT, and embedded systems. Key research themes include specification mining, fault localization, and automated verification. He has developed tools like DeepRIoT for robotic-IoT integration and FIM for Simulink fault analysis. His professorial dissertation (2020) formalized runtime verification techniques for CPS. Recent publications emphasize adaptive architectures, backdoor detection in AI, and hyperproperties for security. He collaborates extensively with academia and industry, addressing challenges in CPS testing and verification through grants like ZK 35-G (2019–2024). His lab supports platforms like CPS/IoT Ecosystem for research and education. Projects: TAIGER, ARTIST, EdgeAI, ProbInG Supervised students: N. Manjunath (PhD, 2021), Florian Exenberger (2019), Markus Heindl (2017)

• Compiler Optimization
• Embedded Systems
• Robotics Software Engineering
• +۴ مورد دیگر

Dietmar Schreiner is a Senior Lecturer at TU Wien's Faculty of Informatics within the Department of Compilers and Languages. His research focuses on compiler optimization, real-time systems, robotics software engineering, and component-based automotive software. He has contributed to major projects like C3Pro (2010–2015) and ALL-TIMES (2007–2010), addressing challenges in embedded systems and automotive software. He advises students on robotics and embedded systems projects, including thesis works like 'Robotersteuerung mittels Genetic Programming für die RoboCup Standard Platform League' (2011) and 'Reasoning capabilities for a cognitive-assistive assembly system' (2017). He is actively involved in the Austrian Kangaroos robotics team and has received the Best Poster Award at SAC 2007 for work on UML-based component modeling. His teaching responsibilities include courses such as 'Introduction to Programming 1', 'Programming Principles of Mobile Robotics', and 'Fundamentals of Digital Systems'. He has also contributed to EU and national grants, advancing research in timing analysis and automotive system software.

Erik Leitingerمشاهده پروفایل

عضو هیئت علمی

• Ultrawideband Wireless Communication
• Indoor Positioning
• Estimation/Detection Theory
• +۳ مورد دیگر

Erik Leitinger is a Senior Researcher at the Graz University of Technology, Austria. He holds a Dipl.-Ing. (M.Sc.) and Ph.D. in electrical engineering from the same institution, awarded in 2012 and 2016 respectively. His work focuses on ultrawideband (UWB) wireless communication, indoor positioning systems, Bayesian inference, and factor graph-based algorithms. He has contributed to multipath-based simultaneous localization and mapping (SLAM), cooperative localization, and MIMO systems. Leitinger’s research integrates theoretical frameworks like belief propagation and variational inference with practical applications in automotive radar, RFID positioning, and 5G/6G systems. His academic contributions span over 50 peer-reviewed articles, with recent work emphasizing non-ideal reflective surfaces, scalable positioning systems, and neural-enhanced SLAM algorithms. He actively collaborates with institutions like the University of Lund (Sweden) and KTH Royal Institute of Technology, contributing to projects such as the EU-funded IPIN competitions. Leitinger teaches courses on adaptive systems, signal processing, and machine learning. His student projects include topics like neural-enhanced SLAM, acoustic source localization using reflections, and real-time multipath-assisted localization with channel sounders. He is affiliated with TUGRAZonline and ORCID, maintaining an open research profile.

• Bayesian Statistics
• Mixture Models
• Computational Statistics
• +۳ مورد دیگر

Gertraud Malsiner-Walli is an Associate Professor at the Institute of Statistics and Mathematics at WU Vienna University of Business and Economics. Her research focuses on Bayesian mixture models , model-based clustering , and computational statistics , with applications in medical imaging, neurology, and psychiatry. She has contributed to advancements in sparse finite Gaussian mixtures and telescoping sampling algorithms , enabling efficient Bayesian inference in mixture models. Her work bridges theoretical developments and practical applications, addressing challenges in identifying data clusters and handling high-dimensional datasets. Notable contributions include methodologies for effect fusion in regression models and multivariate regression analysis of mixed-type panel data. She has published in top journals such as Statistics and Computing , Advances in Data Analysis and Classification , and Bayesian Analysis . Her research also extends to medical applications, including studies on Alzheimer’s disease biomarkers and glioma diagnosis using combined imaging techniques. She has received funding from the Austrian Science Fund (FWF) and WU Projects grants. Collaborations with experts like Sylvia Frühwirth-Schnatter and Bettina Grün highlight her active role in advancing Bayesian statistical methodologies globally.

• Agricultural Water Management
• Soil Hydrology
• Irrigation Systems
• +۳ مورد دیگر

Reinhard Nolz is an Associate Professor at the University of Natural Resources and Life Sciences, Vienna (BOKU) , affiliated with the Institute of Soil Physics and Rural Water Management . His work focuses on optimizing irrigation strategies, soil water monitoring, and hydrological modeling to ensure sustainable water use in agriculture. Research Highlights Developed climate-resilient irrigation frameworks Advanced lysimeter-based water balance studies Integrated sensor networks for real-time soil moisture Validated evapotranspiration models Conducted international agricultural hydrology collaborations Publications 20+ peer-reviewed articles (2009-2024) on irrigation technology Key contributions to Acta Hydrologica Slovaca and Die Bodenkultur Service Editorial Board Member: Acta Hydrologica Slovaca (2017-2020) Peer reviewer for Geoderma , Journal of Hydrology

• Soil Physics
• Water Management
• Irrigation
• +۳ مورد دیگر

Peter Cepuder is a research scientist at the Institute of Soil Physics and Rural Water Management within the Department of Landscape, Water and Infrastructure at the University of Natural Resources and Life Sciences, Vienna (BOKU). With a doctorate earned in 1989, his three-decade career focuses on soil-water dynamics, irrigation optimization, and groundwater protection through field experiments and international collaborations. He has delivered 96 lectures across 15 countries including Austria (66), Germany (6), and Spain (4), establishing himself as a key contributor to agricultural hydrology and lysimeter research methodologies. Education: PhD (1989) Research Interests: His work centers on soil physics and rural water management , specializing in lysimeter-based quantification of water balance components, nitrogen leaching reduction strategies, and sensor-driven irrigation systems. He integrates field data with models like EPIC to address groundwater contamination in agricultural landscapes, with strong emphasis on practical applications for farmers. Current projects include bilateral cooperation with Czech researchers and development of ÖWAV-Regelblatt 407 for irrigation standards. Publication Trends: Recent articles (2019-2016) reveal consistent focus on lysimeter technology for measuring soil water fluxes, nitrogen pollution control in groundwater, and crop-specific irrigation optimization . Key themes include dew formation analysis, spatial EC distribution in fertigation, and evapotranspiration partitioning, primarily applied to onions, carrots, and vineyards in Central European contexts. Scientific Awards: No awards documented in provided data Advising and Grants: While the "Supervised Theses" section confirms mentoring activity, specific student names are unavailable. He participated in the EU-TEMPUS Project EDUWAT for water engineering education in Syria and bilateral initiatives with Czech Republic institutions (e.g., OPTIMA project), though detailed grant information is absent from the scraped content. Labs and Teams: Cepuder co-founded the Lysimeter Research Group (LRG), an international consortium active since 2002 that standardizes lysimeter methodologies across 10+ countries. He leads field operations at BOKU's Groß-Enzersdorf lysimeter station, which features high-precision weighing systems for monitoring water, nutrients, and pollutants in agricultural ecosystems.

Nick Bartonمشاهده پروفایل

استاد

• Evolutionary Genetics
• Population Genetics
• Speciation
• +۹ مورد دیگر

Nick Barton is a Professor and Group Leader at the Institute of Science and Technology Austria (ISTA), where he leads research in evolutionary genetics. He is affiliated with the SFB Polygenic Adaptation at the University of Veterinary Medicine Vienna, reflecting collaborative research networks in Austria. His work bridges theoretical models and empirical data, particularly in hybrid zones and speciation. PhD in Genetics, University of East Anglia (1979) B.A. in Natural Sciences (Genetics), University of Cambridge (First Class, 1976) His research interests center on evolutionary genetics , with a focus on hybrid zones , speciation , polygenic adaptation , and quantitative genetics . He uses mathematical models to study selection on large numbers of genes and spatially continuous populations. His long-term field study of Antirrhinum majus in the Spanish Pyrenees integrates genomics, ecology, and pollinator behavior to understand how species diverge. He also investigates theoretical models of recombination, coalescence with selection, and evolutionary computation . The recent publications reflect a strong trend in genomic analysis of hybrid zones , fitness landscapes , self-incompatibility evolution , and theoretical models of information accumulation in evolution . Many studies combine field data with advanced computational methods like ancestral recombination graphs (ARGs) and population genomic inference. His scientific awards include: Royal Society Darwin Medal (2006) Linnean Society Darwin-Wallace Medal (2009) ERC Advanced Grants (2009, 2010) Erwin Schrödinger Prize (2013) Mendel Medal (2013) Royal Society/Wolfson Research Merit Award (2005–2010) Nick Barton has supervised numerous PhD students, including Parvathy Surendranadh, Oluwafunmilola Olusanya, Michal Hledik, and Eniko Edelsbrunner, whose theses cover topics like local adaptation, genetic load, and self-incompatibility. His research has been supported by major grants from the ERC (€1.9M), EPSRC, NERC, BBSRC, and FWF (€399K for Snapdragon speciation). He leads a vibrant research group involving postdocs and PhD students working on speciation, hybridization, and theoretical population genetics. The group conducts annual fieldwork in the Pyrenees, studying snapdragon hybrid zones, and fosters interdisciplinary collaboration with researchers in the UK, France, and Australia. His lab, the Research Group of Nick Barton , is based at ISTA and includes postdocs like Hilde Schneemann, Daria Shipilina, and Benjamin Wölfl, and PhD students such as Louise Fouqueau and Gemma Puixeu. The group is known for integrating theoretical models with empirical data and for its collaborative, team-oriented approach to evolutionary research.

• Composite Materials
• Computational Mechanics
• Artificial Intelligence
• +۲ مورد دیگر

Sophia Keller serves as a Researcher at the University of Applied Sciences Wels, Austria, within the Research Center Wels Center of Excellence Automotive/Mobility, specializing in Materials engineering. She holds a BSc and Dipl.-Ing. (Diplom-Ingenieur) degree, reflecting her engineering background. Her research integrates Composite Materials, Computational Mechanics, and Artificial Intelligence to advance composite manufacturing processes. Key focus areas include draping simulation optimization, finite element analysis acceleration through AI surrogates, and automation of fabric preforming using reinforcement learning. She develops novel methodologies for geometric defect detection and validation via 3D laser scanning. Recent publications (2023-2025) demonstrate a clear trajectory toward AI-enhanced engineering simulations, with increasing emphasis on real-time automation and quality control in composite production. Her work bridges computational modeling with industrial manufacturing challenges. She received significant recognition through academic awards: FH Wels InnovationAward (2022) As an active Co-Investigator on major research grants, Keller contributes to projects addressing automotive composite manufacturing challenges. Her collaborative work on AdiosRivet (2023-2026) focuses on welded joints for TP-CFRPC vehicle structures, while Pre-2-K (2025-2026) develops semi-automated preform manufacturing for complex 3D components. She operates within the Research Center Wels ecosystem, collaborating with engineering teams on laser scanning validation, robot-supported fiber angle measurement, and AI-driven process automation for the automotive mobility sector.

• Medical Image Processing
• Deep Learning
• 3D Dosimetry
• +۳ مورد دیگر

Werner Backfrieder is a Professor at the Department of Medical Engineering within the University of Applied Sciences Upper Austria. He serves as a Researcher at the Center of Excellence Medical Engineering/TIMed Center, focusing on advanced medical imaging and computational techniques. Affiliation: University of Applied Sciences Upper Austria Research Center: Center of Excellence Medical Engineering/TIMed Center Research Interests: His work spans medical image processing, deep learning applications for diagnostic domains, 3D dosimetry, and image-guided surgery. He specializes in multimodal data integration, attenuation correction in radiation dosimetry, and algorithmic enhancements for surgical precision. Recent Publications: Recent articles highlight his contributions to U-Net-based segmentation strategies, training deep learning models with limited datasets, and innovations in 3D dosimetry. These works intersect medical imaging, radiation therapy, and computational optimization. Labs & Teams: Active in the TIMed Center, he collaborates on simulation-based medical technologies and participates in conferences like IWISH and VISAPP.

Mei Hongمشاهده پروفایل

استاد

• Software architecture
• Program analysis and testing
• Software System for Cloud Computing and Big Data
• +۵ مورد دیگر

Mei Hong is a Professor and Vice President for HR and International Collaboration at Beijing Institute of Technology. Previously held roles include Professor and Vice President at Shanghai Jiao Tong University (2013-2016), Director of key national research centers at Peking University, and leadership positions in software engineering education and research. Holds dual academic leadership and technical expertise in software engineering. Education: BSc/MSc (Nanjing University of Aeronautics & Astronautics, 1984/1987); PhD (Shanghai Jiao Tong University, 1992). Research focuses on software architecture, cloud computing systems, component-based engineering, and software testing. Has pioneered the 'Internetware' paradigm and contributed to national standards for software development. Publications span software engineering methodologies and tools, with recent work emphasizing mobile computing optimization and automated testing techniques. Over 20 awards including IEEE Fellow (2014), Member of Chinese Academy of Sciences (2011), and multiple best paper awards. Advisory roles include Alibaba DAMO Academy's Academic Board, China's National Key R&D Program, and leadership in 863 High-Tech Program committees. PI of 40+ grants totaling over 200 million CNY. Editorial leadership includes SCIENCE CHINA-Information Sciences (Editor-in-Chief since 2018), ACM Computing Surveys, and top-tier journals/conferences. Active in conference organization (General Chair for ICSME 2017, SPLC 2016).

Markus Neubauerمشاهده پروفایل

پژوهشگر

• Regenerative Medicine
• Orthopedics
• Stem Cell Research
• +۴ مورد دیگر

Dr. Markus Neubauer is a researcher at the University for Continuing Education Krems, affiliated with the Center for Regenerative Medicine. His work focuses on regenerative therapies for musculoskeletal disorders, particularly osteoarthritis. Key areas of research include stem cell biology, extracellular vesicle applications, and surgical techniques for cartilage repair. He has contributed to projects such as the Motor Learning in Knee Osteoarthritis Therapy initiative, supported by the Life Science Call NFB funding program. His research integrates clinical and experimental approaches, emphasizing translational medicine. Recent studies explore the use of blood-derived products and mesenchymal stem cells in tissue regeneration. Dr. Neubauer also investigates the role of artificial intelligence in improving diagnostic accuracy for knee osteoarthritis. Publications highlight advancements in surgical techniques, bioreactor-based cell culture systems, and comparative analyses of knee arthroplasty outcomes. His work bridges basic science and clinical practice, aiming to enhance therapeutic strategies for musculoskeletal conditions. No formal awards are listed, but his contributions to conferences such as the OARSI World Congress and ICRS World Congress reflect active engagement in the scientific community. Advising roles or student mentorship details are not explicitly mentioned. The Center for Regenerative Medicine serves as his primary lab environment, fostering interdisciplinary collaboration in biomedical innovation.

Imola Wilhelmمشاهده پروفایل

پژوهشگر ارشد

• Neurovascular unit
• Blood-brain barrier
• Cerebral circulation
• +۴ مورد دیگر

Imola Wilhelm serves as a senior research associate at Hungary's Biological Research Centre in Szeged, where she leads pioneering investigations into the neurovascular unit, blood-brain barrier dynamics, and cerebral circulation. Her work specifically examines pericyte function in pathological contexts including brain metastasis, neuroinflammation, and aging processes. As a leading scholar in neurovascular biology, Wilhelm's research integrates molecular and physiological approaches to unravel blood-brain barrier mechanisms under disease conditions. Her dual expertise spans both neurovascular pathology and advanced photonics, with significant contributions to silicon nitride waveguide technologies for biosensing applications. Her 15 most recent publications (2021-2025) reveal a strategic convergence of machine learning and photonic engineering, featuring optimization of silicon nitride platforms, loss-minimization techniques, and biosensor development. This work demonstrates consistent methodological innovation across fabrication, characterization, and application domains. Wilhelm's exceptional contributions have earned prestigious recognition: Bolyai János Research Fellowship from the Hungarian Academy of Sciences L’Oreal-UNESCO Women in Science national scholarship Junior Award for early-career research excellence She actively mentors BSc, MSc, MD, and PhD students while directing multiple scientific grants as principal investigator. Since 2020, she has served as a Szent-Györgyi mentor for the National Academy of Scientist Education and currently holds an executive board position at the Hungarian Young Academy (joined 2021). Her science communication outreach includes Researchers’ Night lectures since 2014 and Brain Awareness Week participation since 2018. Wilhelm leads a multidisciplinary research team at the Biological Research Centre that bridges neurovascular biology with photonic sensor development, maintaining active collaborations across both domains while supervising graduate trainees and postdoctoral researchers.