جست‌وجوی استاد و پژوهشگر

• Oncology
• Breast Cancer Treatment
• Medical Imaging
• +۳ مورد دیگر

Prof. Roland Reitsamer is a full Professor in the Department of Obstetrics and Gynecology at Paracelsus Medical University (PMU) Salzburg. He specializes in breast cancer research, radiation oncology, and medical imaging technologies. His work focuses on improving treatment outcomes through innovations like intraoperative electron radiotherapy (IOERT), AI-driven medical imaging analysis, and biomarker detection methods. Reitsamer has organized major conferences such as the Jahreskongress der Universitätsfrauenklinik der PMU Salzburg and participated in international studies like the INSEMA trial evaluating axillary surgery techniques. His research integrates computational methods (LSTM networks, digital PCR) with clinical applications to address challenges in chemotherapy resistance, radiation toxicity, and early cancer detection. Key contributions include developing segmentation algorithms for cone-beam CT imaging, analyzing IOERT outcomes in early-stage breast cancer, and investigating molecular mechanisms of drug resistance. He maintains active involvement in clinical trials and medical education initiatives.

• Artificial Intelligence
• Machine Learning
• Explainable Artificial Intelligence
• +۳ مورد دیگر

Sebastian Tschiatschek is an Associate Professor at the Faculty of Computer Science, affiliated with the Research Group Data Mining and Machine Learning. His work contributes to UN Sustainable Development Goals through research in artificial intelligence, machine learning, and deep generative models. Key themes include explainable AI, forest ecology applications, and data clustering optimization. His recent publications focus on: (1) information needs for algorithmic decision-making (2025), (2) centroid-based deep clustering challenges (2024), and (3) drone-assisted forest ecology management (2024). Research spans interdisciplinary applications in environmental monitoring, stakeholder engagement, and democratic AI systems. Active projects include Interpretability and Explainability as Drivers to Democracy (2021-2025). Notable collaborations involve Austrian Computer Science Day organization (2024) and contributions to web survey methodologies (2024). His academic fingerprint includes 100% expertise in artificial intelligence, with secondary concentrations in training data, deep generative models, and forest management.

• Autonomous Systems
• Computer Vision
• Sensor Technology
• +۵ مورد دیگر

Prof. Daniel Watzenig is a Full Professor at Graz University of Technology's Faculty of Electrical Engineering and Information Technology, affiliated with the Institute of Visual Computing and the Institute of Electrical Measurement and Sensor Technology. He serves as Dean of Studies for Digital Engineering (DE), overseeing academic programs in this field. His research focuses on autonomous systems, sensor fusion, and advanced control strategies for vehicles, with a strong emphasis on LiDAR technology, path planning algorithms, and real-time environmental perception systems. He holds academic qualifications including Dipl.-Ing. (FH) and Dr.techn. degrees. Research interests span robotics, computer vision, and machine learning applications in transportation systems. His work addresses challenges in autonomous vehicle navigation, sensor reliability under adverse conditions, and safety-critical system validation. Recent publications highlight innovations in thermal-LiDAR fusion, trajectory optimization, and radar-based occupancy grids. He actively contributes to interdisciplinary projects involving co-simulation frameworks and virtual validation methodologies for automated driving functions. Professional roles include leading academic programs in digital engineering and managing research collaborations at TU Graz. His technical expertise is reflected in over 100 publications (2020-2025) covering sensor technology, path planning algorithms, and autonomous system validation. Key labs/teams associated include the Institute of Visual Computing's autonomous systems group and the Electrical Measurement Institute's sensor innovation team.

Thomas Takacsمشاهده پروفایل

پژوهشگر

• Isogeometric Analysis
• Computational Mechanics
• Numerical Analysis
• +۳ مورد دیگر

Dr. Thomas Takacs is a Project Leader in the Geometry in Simulations research group at the RICAM (Research Institute for Symbolic Computation), part of the Austrian Academy of Sciences. His work focuses on advancing computational methods for solving partial differential equations, particularly through isogeometric analysis and spline-based numerical techniques . His research interests include smooth basis constructions, multi-patch domain coupling, and adaptive mesh refinement strategies. Key contributions involve developing C1-continuous spline spaces over planar mixed meshes and unstructured quadrilateral meshes, with applications to engineering problems like linear elasticity. He explores the integration of machine learning (e.g., CNNs) for optimizing quad meshing and employs artificial neural networks in adaptive optimization frameworks. His work bridges geometric modeling and numerical analysis, addressing challenges such as singularity treatment in isogeometric analysis and approximation properties over self-similar meshes. Dr. Takacs collaborates on multi-institutional projects, including the Geometry in Simulations group at RICAM. His publications span computational mechanics, numerical methods, and geometric algorithms, with a focus on advancing the theoretical foundations and practical implementations of isogeometric analysis.

• Cyber-Physical Systems
• Smart Grids
• Swarm Intelligence
• +۵ مورد دیگر

Prof. Wilfried Elmenreich is a Professor at the Department of Networked and Embedded Systems at Alpen-Adria-Universität Klagenfurt. He serves as a Member of the Senate and Member of the Works Council for Academic Staff. His research focuses on Cyber-Physical Systems, Smart Grids, Swarm Intelligence, and Sustainability Technologies. He leads projects involving swarm robotics, decentralized energy management, and educational technology. Key research areas include: Design of swarm-based algorithms for production scheduling and robotics Development of frameworks like SwarmFabSim for bottom-up optimization Non-Intrusive Load Monitoring (NILM) using neural networks and edge computing Integration of federated learning into smart grid systems Sustainability education and pandemic-related behavioral studies His work combines theoretical contributions with practical implementations, such as the CPSwarm project for swarm system design and the Yomopie energy monitoring tool. Recent publications emphasize interdisciplinary approaches, blending robotics, machine learning, and electrical engineering to address challenges in energy systems and autonomous systems.

• Artificial Intelligence
• Robotics
• Systems Engineering
• +۳ مورد دیگر

Peter Pavel Arthur Petráš is a Tutor at the Institute for Intelligent System Technologies within the Faculty of Technical Sciences at the University of Klagenfurt. His research focuses on interdisciplinary applications of artificial intelligence, robotics, and systems engineering, with contributions to fields like swarmalator dynamics, automated systems design, and media literacy in digital environments. He is actively engaged in collaborative projects involving industry partners such as Infineon Technologies Austria AG and the Austrian Research Promotion Agency (FFG), emphasizing practical innovations in technology and education. While not listed as a project head, his role supports cutting-edge research in areas like radar simulation frameworks, garment sorting automation, and multi-agent localization systems. His work bridges theoretical advancements with real-world implementation, particularly in edge-cloud computing and interdisciplinary methodological innovations. Recent publications highlight his expertise in AI-driven solutions, robotics, and the societal implications of digital media. Notable themes include analyzing online political microtargeting avoidance, improving multi-robot exploration algorithms, and exploring poetry workshops in migration research. His contributions align with the University of Klagenfurt’s focus on fostering innovation through its Third Mission initiatives, emphasizing knowledge transfer to regional industries and public sectors. Petráš collaborates on projects addressing societal challenges, such as promoting media literacy through the #NoFakeFacts! Citizen Science initiative and enhancing wind turbine blade inspection via multimedia drones. His work reflects a commitment to both technical innovation and addressing ethical and educational dimensions of emerging technologies.

• Speech technology
• Phonology
• Language processing
• +۴ مورد دیگر

Janet Pierrehumbert is a Professor of Language Modelling at the Oxford e-Research Centre (part of the Department of Engineering Science, University of Oxford). She holds a courtesy appointment in the Faculty of Linguistics, Philology and Phonetics and is an Associate Member of the Oxford-Man Institute of Quantitative Finance. Previously, she served as a Professor at Northwestern University (1993–2015), where she held leadership roles including department chair and director of graduate studies. Her interdisciplinary research spans experimental and computational linguistics, focusing on phonology, morphology, and computational linguistics. She is a Fellow of the American Academy of Arts and Sciences, the Cognitive Science Society, and the Linguistic Society of America, and a member of the National Academy of Sciences (USA). Education: BA in Linguistics and Mathematics (Harvard University); PhD in Linguistics (MIT). Research Interests: Pierrehumbert’s work integrates computational methods with linguistic theory to explore sound change, morphological processing, and language modeling. Her studies often address how statistical patterns in speech and lexicons influence phonological cognition. Recent projects include improving NLP models (e.g., BERT) through linguistic insights and developing benchmarks for hate-speech detection algorithms. Publications: Her work spans decades, with notable contributions to computational linguistics, phonology, and sociolinguistics. Recent articles highlight advancements in NLP ethics, morphological theory, and sound change mechanisms. Earlier foundational studies include pioneering work on Japanese tone structure and intonational pragmatics. Awards & Memberships: Her honors include the ISCA Medal for Scientific Achievement (2020) and Guggenheim Fellowship (1996). She co-founded the Association for Laboratory Phonology and is active in interdisciplinary initiatives like the Northwestern Institute on Complex Systems. Labs & Teams: Her research group at Oxford focuses on robust language technology and theoretical linguistics. She collaborates across disciplines, bridging computational and experimental approaches to language science.

Horst Posseggerمشاهده پروفایل

پژوهشگر

• Computer Vision
• Autonomous Systems
• Multiple Object Tracking
• +۳ مورد دیگر

Horst Possegger is a Computer Vision researcher at the Institute of Computer Graphics and Vision at Graz University of Technology, Austria. He holds a BSc and MSc in Software Development and Business Management (2011, 2013) and a PhD in Computer Science (2018), all from Graz University of Technology. His research focuses on multiple object tracking/detection, human behavior analysis, and video analysis with applications in autonomous systems, LiDAR data processing, and robotics. Key projects include trajectory prediction, 3D object detection, and domain adaptation techniques for real-world scenarios. Recent work emphasizes cross-modal learning (e.g., vision-language models for LiDAR data), robust localization in challenging environments, and lightweight motion prediction models. He contributes to the Learning, Recognition & Surveillance (LRS) group and has published extensively in top-tier venues like IEEE/CVF CVPR and IROS. Publications span autonomous driving benchmarks, UWB-based localization, and warehouse automation. His work often bridges theoretical advancements with practical implementations in robotics and surveillance systems.

Chellappa Ramaمشاهده پروفایل

استاد

• Computer Vision
• Machine Learning
• Artificial Intelligence
• +۵ مورد دیگر

Rama Chellappa is the Bloomberg Distinguished Professor at Johns Hopkins University (JHU), holding primary appointments in the departments of Electrical and Computer Engineering and Biomedical Engineering, under the Whiting School of Engineering and School of Medicine, respectively. He is affiliated with the Center for Imaging Science, Center for Language and Speech Processing, Institute for Assured Autonomy, and Mathematical Institute for Data Science. Previously, he spent 29 years at the University of Maryland as a College Park Professor and held roles at the University of Southern California and Purdue University. His research focuses on computer vision, machine learning, artificial intelligence, pattern recognition, and biometrics, with applications in smart cars, forensics, 2D/3D facial modeling, and medical diagnostics. Notable contributions include work on Markov random fields, 3D structure recovery, deep learning for face recognition, and gait recognition. He has published over 900 papers, achieving an h-index of 140. Rama Chellappa has been honored with prestigious awards, including the US National Academy of Engineering membership (2023), IEEE Jack S. Kilby Medal (2020), and K.S. Fu Prize (2012). He is a Fellow of multiple organizations, including IEEE, IAPR, and AAAS. His current collaborations at JHU School of Medicine involve applying computer vision to analyze facial expressions for monitoring stroke/dementia patients, autism detection in children, and digital pathology.

Horvath Peterمشاهده پروفایل

استاد

• Computational Biology
• Artificial Intelligence
• Microscopy
• +۳ مورد دیگر

Peter Horvath is a distinguished academic and researcher in computational biology and artificial intelligence. He currently serves as Principal Investigator at the AI4Health Institute of Helmholtz Munich, Germany, and Director of the Institute of Biochemistry at the Biological Research Centre (BRC) in Szeged, Hungary. He holds a DSc from Hungary, a PhD in Digital Image Analysis from the University of Nice, and an MSc in Computer Science and Mathematics from the University of Szeged. His research focuses on bioimage informatics, AI-driven biological discovery, and single-cell analysis. Horvath has led major initiatives, including the Finnish Distinguished Professor Fellowship at FIMM (University of Helsinki) and founded Single-Cell Technologies Ltd. He is a prolific grant recipient, securing funds for projects like 'AI-driven machines for biological discoveries' and 'Proteogenomic map of tumor cell division'. His work bridges computational methods with biological applications, notably developing tools like nucleAIzer and Deep Visual Proteomics. Key recognitions include the Szent-Györgyi Talentum Prize (2019), Momentum Award (2018), and Finland Distinguished Professorship (2014). He actively contributes to scientific communities, organizing conferences like NEUBIAS 2018 and serving on boards for the Society of Biomolecular Imaging.

• Stochastics
• Actuarial Mathematics
• Numerical Mathematics
• +۳ مورد دیگر

Michaela Szölgyenyi is a Professor at the Institute of Statistics within the Faculty of Technical Sciences at the University of Klagenfurt. Her research focuses on stochastic processes, numerical methods for stochastic differential equations (SDEs), and applications in financial and actuarial mathematics. She specializes in analyzing SDEs with irregular coefficients, including discontinuous drift and jump-diffusion dynamics. Her work emphasizes approximation methods for such equations, with contributions to optimal transport, risk theory, and insurance mathematics. She has published extensively on convergence rates, numerical schemes like the Euler-Maruyama and Milstein algorithms, and their applications in modeling financial and actuarial scenarios. She is affiliated with interdisciplinary projects and teaches courses related to stochastic analysis and mathematical finance.

• Answer Set Programming
• Artificial Intelligence
• Cybersecurity
• +۱۲ مورد دیگر

Prof. Martin Gebser is a University Professor and Deputy Director at the Institute for Artificial Intelligence and Cybersecurity, University of Klagenfurt. His work bridges theoretical advancements in Answer Set Programming (ASP) with practical applications in industrial scheduling, semiconductor manufacturing, and explainable AI systems. Institute for Artificial Intelligence and Cybersecurity, University of Klagenfurt His research focuses on Answer Set Programming and its extensions for complex scheduling problems, particularly in semiconductor production. Key areas include: Multi-shot ASP solving for job-shop decomposition Hybrid AI systems integrating reinforcement learning and logic programming Explainable AI for battery health monitoring and semiconductor dispatching Recent publications emphasize temporal planning, constraint learning, and real-world data integration. He has developed customizable simulators and optimization frameworks for industrial applications.

• Project management
• Organizational psychology
• Educational psychology
• +۷ مورد دیگر

Karin Lackner is an Assistant Professor (retired) affiliated with the Institute for Teaching and School Development at the University of Klagenfurt. Her work focuses on educational and organizational psychology, project management, and intercultural dynamics within institutional settings. Research Areas: Organizational and educational psychology Healthcare management Team development strategies Sociodynamic design Sports research Intercultural project management Her scholarly contributions span interdisciplinary research methodologies and practical applications in educational systems. Recent work emphasizes innovation in teaching methodologies and institutional frameworks. Publications include analyses of digital media behavior ( Political Microtargeting Avoidance ), robotics applications ( Swarmalator Systems ), and sustainable business models ( Entrepreneurial Ecosystems ). These reflect her interdisciplinary approach bridging social sciences and technical fields. Grants & Projects: Collaborative research initiatives in education innovation and organizational dynamics (funding sources include Austrian Research Promotion Agency and Carinthian Economic Development Fund). She leads initiatives promoting inclusive educational practices and advises on institutional transformation strategies.

Friedrich Leischمشاهده پروفایل

استاد

• Statistical Computing
• Cluster Analysis
• Bioprocess Modeling
• +۳ مورد دیگر

Friedrich Leisch was a Professor at the Institute of Statistics, University of Natural Resources and Life Sciences, Vienna. He held leadership positions including Head of the Department of Landscape, Spatial and Infrastructure Sciences and was a core developer for the R programming language. His career included positions at Ludwig-Maximilians-Universität München and Vienna University of Technology, where he earned his doctorate and habilitation. Education includes: PhD in Applied Mathematics, Vienna University of Technology (1999) Habilitation in Statistics, Vienna University of Technology (2005) Leisch's research focused on statistical computing methodologies with applications across diverse scientific domains. His primary interests included: Development of resampling methods for cluster analysis and validation Bioprocess modeling for pharmaceutical manufacturing Causal modeling frameworks for scientific inference Statistical computing and R package development His recent publications demonstrate a strong focus on biotechnological applications of statistical learning, developing methods for real-time process monitoring in pharmaceutical production. Articles frequently address machine learning explainability, temporal clustering, and environmental impact assessment of agricultural practices. Scientific awards include: Peter Keller Award for tourism research Supervised numerous doctoral and master's students across statistics and biotechnology domains. Led multiple research projects including: Mobile Field Phenotyping for Agronomy and Breeding Statistical evaluation of downstream processing data Market Segmentation Methodology projects Collaborated extensively with bioprocessing research groups including the Austrian Centre of Industrial Biotechnology (ACIB), focusing on statistical modeling of fermentation processes and purification systems.

Diogo Campos Sasdelliمشاهده پروفایل

پژوهشگر ارشد

• AI and Law
• Legal Logic
• Normative Diagrams
• +۶ مورد دیگر

Dr. Diogo Campos Sasdelli, M.A. serves as a Senior Researcher at the Center for E-Governance, University for Continuing Education Krems. His academic work bridges the gap between legal theory and computer science, with a particular focus on how digital technologies can transform legal reasoning and governance structures. Dr. Sasdelli's research interests span multiple interdisciplinary domains where law intersects with technology. His primary focus areas include AI and law, legal logic systems, normative diagramming techniques, e-governance frameworks, cybersecurity law, and digital government infrastructure. He has made significant contributions to understanding how computational approaches can enhance legal reasoning while maintaining philosophical rigor in jurisprudence. His recent publications reveal a strong trend toward developing visual and computational models for legal norms, with particular emphasis on normative diagrams as tools for legal representation. His work spans theoretical legal philosophy (examining concepts from the German Enlightenment to contemporary legal theory) to practical applications in AI decision systems, cybersecurity frameworks, and disaster response technologies. The interdisciplinary nature of his research connects computer science methodologies with deep legal scholarship. Dr. Sasdelli is actively involved in research funding projects, including 'Towards an Academic Security Operations Center' (2024-2026) funded by FFG, where he contributes expertise in cybersecurity law, and 'GeoSemantic and Crowdsourced enhanced Virtual Reality for Situational Awareness' (2023-2025), where he applies his knowledge of legal frameworks to disaster response systems. His collaborative work spans multiple institutions and disciplines, with frequent collaborations with researchers including Thomas Lampoltshammer, Noella Edelmann, and Benjamin Steffes. Dr. Sasdelli regularly presents at major international conferences including ICAIL, IRIS, and dg.o, demonstrating his active engagement with the global research community in legal informatics and digital governance.