جست‌وجوی استاد و پژوهشگر

Shohei Moriمشاهده پروفایل

پژوهشگر

• Mediated Reality
• Augmented Reality
• Diminished Reality
• +۴ مورد دیگر

Dr. Shohei Mori is a Junior Research Group Leader at the Visualization Research Center (VISUS) of the University of Stuttgart, Germany, and a Guest Associate Professor at Keio University, Japan. His research focuses on computational Mediated Reality, combining Augmented and Diminished Reality to address human-centered visual computing challenges. Key applications include education, entertainment, and cinematography. He has received numerous awards, including the IEEE ISMAR 2023 Best Journal Paper Award, IEEE VR 2022 Best Journal Paper Award, and multiple presentation/demonstration awards. His work spans grants such as the FWF-funded 3DDR project and collaborations with institutions like TU Graz, NTT Laboratories, and AVL List GmbH. Mori has taught courses on topics like Neural Rendering, Mixed Reality, and Computer Vision at institutions including TU Graz and FH Salzburg. His teaching emphasizes practical assignments and student research presentation management. His research interests include 3D reconstruction, light field displays, and perceptual aspects of mixed reality. He actively contributes to conferences like IEEE VR and ISMAR as a reviewer, chair, and committee member.

• 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.

Agnes Turnerمشاهده پروفایل

دانشیار

• Mentalization-based pedagogy
• Reflective learning and teaching
• Psychoanalytic pedagogy
• +۴ مورد دیگر

Agnes Turner is Associate Professor (Assoc.-Prof. Mag.) at the Institute for Teaching and School Development , University of Klagenfurt, Austria, and Vice-Dean of the Faculty of Interdisciplinary Research and Continuing Education . She is chairwoman of ANSE (the European umbrella organisation for supervision) and an active member of multiple transnational research networks such as the DFG network for mentalization-based pedagogy and CARN DACH. Education & Qualifications Mag. degree (equivalent to Master) – field not explicitly stated in the text. Extensive continuing professional development in psychoanalytic observation and supervision. Research Interests Turner’s work sits at the intersection of educational science and psychoanalytic theory. Her core themes include: Mentalization-based pedagogy – developing teachers’ capacity to understand their own and their pupils’ mental states. Reflective learning and teaching – designing settings that foster deep, self-reflective professional growth. Digitalisation in schools – investigating how digital tools, especially telepresence robots, can sustain inclusion for chronically-ill children. Emotional and psychodynamic aspects of classroom life, including transference dynamics and affect regulation. Publication Trends Across more than 40 peer-reviewed works (2010-2025), a clear trajectory is visible: early studies explore psychoanalytic observation as a method for teacher education; mid-period outputs integrate these insights into inclusive and special-education contexts; and the most recent work scales mentalization-based interventions to entire schools and teacher-training curricula, while simultaneously pioneering the use of telepresence robots to preserve social inclusion for pediatric patients with chronic illness. Scientific Awards & Recognitions Chairwoman, ANSE (Association of National Organisations for Supervision in Europe) Member, DFG-funded international research network on mentalization-based pedagogy Member, Curricular Commission for Teacher Training, University of Klagenfurt Active memberships: EERA, ÖFEB, DGfE, ÖVS, CARN DACH network Doctoral Supervision & Grants As Vice-Dean and core faculty in the Institute’s Doctoral School, Turner mentors doctoral candidates in the Career Counselling for Teachers (CCT) programme and several externally funded projects. She co-leads the eLABoration Wood and Emotions in Environmental and Sustainability Education initiatives, securing funding from Austrian, EU and DFG sources. Laboratories & Teams Turner heads the Research Group on Leadership Development and collaborates closely with the ICSE Academy and the IMST network . Weekly Work Discussion seminars serve as living laboratories where pre-service teachers, doctoral students and seasoned educators jointly analyse classroom interactions through a psychoanalytic lens.

• 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.

Günther Kainzمشاهده پروفایل

مدرس

• Security Studies
• Data Science
• Deep Learning
• +۲ مورد دیگر

Mag. Mag. Dr. Günther Kainz is the Study Director at the Department for Security Studies, University for Continuing Education Krems. He specializes in Security Studies, Data Science, and Education Technology. His work bridges theoretical frameworks in economics and practical applications in curriculum design for adult learners. Research Projects : He contributed to the Innovation Training Program Data Science and Deep Learning (2018–2021), funded by FFG, focusing on educational innovation. His research explores trust dynamics in economic contexts and redesigning presence in master’s curricula for extra-occupational studies. Publications : Key works include analyses of trust games in economics ( 2024 ) and studies on hybrid learning models ( 2022 ). He presented findings on curriculum design at the EDEN2022 conference in Tallinn. Grants & Collaborations : Involved in FFG-funded projects. His interdisciplinary approach connects security studies with technological and educational advancements. Labs/Teams : Active within the Department for Security Studies, focusing on applied research in digital transformation and educational methodologies.

Harald Özeltمشاهده پروفایل

پژوهشگر

• Magnetism
• Micromagnetics
• Machine Learning
• +۴ مورد دیگر

Harald Özelt is a Researcher at the Center for Modelling and Simulation within the University for Continuing Education Krems. His work focuses on computational magnet design, micromagnetics, and machine learning applications in materials science. He leads projects such as 'Data Driven Magnet Design through Combinatorial Synthesis and Micromagnetic Graph Networks' (FWF-funded) and 'Design of Nanocomposite Magnets by Machine Learning' (FWF-funded). His research emphasizes the development of advanced simulation techniques and optimization strategies for magnetic materials, particularly permanent magnets and composite systems. Key Projects: Magnetic Multiscale Modelling Suite (EU-funded, PI: Thomas Schrefl) Data Driven Magnet Design (FWF-funded, PI: Özelt) Design of Nanocomposite Magnets (FWF-funded, PI: Özelt) Özelt's research interests include the simulation of magnetic materials' microstructure-property relationships, defect manipulation for enhanced coercivity, and the integration of physics-informed machine learning into computational frameworks. He has authored numerous peer-reviewed articles in journals like Journal of Magnetism and Magnetic Materials and Frontiers in Materials , focusing on topics such as micromagnetic modeling, hysteresis optimization, and magnet design. His lectures and conference presentations highlight contributions to inverse design methodologies, multiscaling strategies in magnet design, and the use of neural networks for predicting magnetic properties. He collaborates internationally on projects addressing sustainable materials and rare-earth reduction in permanent magnets.

Markus Kittlerمشاهده پروفایل

استاد

• International Human Resource Management (IHRM)
• International Management
• Entrepreneurship
• +۵ مورد دیگر

Dr. Markus Kittler is a Professor and Academic Director of the Executive PhD programme at MCI Management Center Innsbruck (Austria), based in the Department of Management and Law. His academic career includes roles as Programme Director for MRes and DBA at the University of Stirling (2007–2017) and as a Lecturer at Friedrich-Alexander-Universität Erlangen-Nuremberg (2000–2007). He holds a doctorate from Erlangen-Nuremberg for research on cross-cultural communication misunderstandings and is a Senior Fellow of the UK Higher Education Academy. Research interests focus on International Human Resource Management (IHRM), cross-cultural communication, expatriate management, entrepreneurship, and research methodologies. He has won multiple teaching awards, including the University of Stirling’s RATE Awards (2013, 2014, 2017) and the AIB UKI Award for Innovative Research. His work also addresses healthcare management, sustainability, and organizational psychology. Professional roles include External Examiner for the Open University Validation Service and Chair of the International Management SIG at the European Academy of Management (2014–2020). He has published extensively in journals like Journal of Global Mobility , Employee Relations , and International Journal of Management Reviews , and authored textbooks on international business. Editorial Roles : Journal of Global Mobility (2013–present) Grants & Awards : Emerald Literati Network Awards (2012, 2016, 2018), Neil Hood Prize (2009) Key Contributions : Frameworks for expatriate management in hostile environments, cross-cultural training effectiveness, and JD-R theory applications His research and teaching emphasize practical relevance, bridging theory and practice in global management and organizational behavior.

Sebastian Zambaniniمشاهده پروفایل

مدرس ارشد

• Computer Vision
• Image Registration
• Object Recognition
• +۲ مورد دیگر

Sebastian Zambanini is a Senior Lecturer at TU Wien's Faculty of Informatics, affiliated with the Computer Vision Lab. His research spans object recognition, image registration, remote sensing analysis, and cultural heritage applications. Zambanini develops computer vision solutions for challenging domains including historical aerial photograph analysis, archaeological artifact documentation, and environmental monitoring. His recent work focuses on deep learning approaches for detecting wartime features in archival imagery and improving 3D reconstruction of cultural objects. He actively supervises graduate research and coordinates courses in programming fundamentals and computer vision methodologies.

Clemens Heitzingerمشاهده پروفایل

دانشیار

• Machine Learning
• Artificial Intelligence
• Reinforcement Learning
• +۶ مورد دیگر

Associate Professor Clemens Heitzinger holds a position at the Technical University of Vienna (TU Wien) within the Department of Informatics (Computer Science), specifically in the Research Unit Machine Learning under the Institute of Information Systems Engineering. His research focuses on machine learning, reinforcement learning, Bayesian methods, and their applications in healthcare, energy systems, and nanotechnology. He leads the TUW Center for Artificial Intelligence and Machine Learning (CAIML) and has received prestigious awards including the START Prize 2013 and an Erwin Schrödinger Fellowship. Education and Academic Background: Clemens earned his doctoral degree (Dr.techn.) in technical mathematics and holds a Diplom-Ingenieur (Master’s equivalent). His academic career includes roles at the University of Cambridge, Purdue University, and Arizona State University. Research Interests: Combines mathematical modeling with machine learning to address challenges in nanoscale sensor design, medical decision support systems, and energy optimization. Key areas include stochastic differential equations, PDE-based modeling, and reinforcement learning for critical applications like sepsis treatment and renewable energy control. Publications: His work spans high-impact journals such as Nonlinear Dynamics , EClinicalMedicine , and Sensors , with a focus on interdisciplinary applications of AI. Recent trends show strong contributions to reinforcement learning in healthcare and energy systems, as well as novel methods in fingerprint recognition and cryogenic sensor control. Awards: Recognized for his START Prize project on PDE models for nanotechnology and his contributions to AI ethics and medical AI. The 2024 nomination for the Austrian National Technology Prize highlights his work on energy system optimization via reinforcement learning. Advising and Grants: Supervises over 20 graduate and undergraduate students, with notable projects in reinforcement learning for sepsis therapy, cryogenic sensor control, and fingerprint analysis. Leads funded initiatives like the FFG-backed RELY project on sustainable energy systems and the WWTF-funded Mathematics and Nanosensors initiative. Labs and Teams: Co-directs CAIML and collaborates with the Medical University of Vienna on AI-driven healthcare solutions. Active in international collaborations through the AIDA doctoral academy and the Vienna Center for Partial Differential Equations.

Pietro Lio'مشاهده پروفایل

استاد

• Computational Biology
• Bioinformatics
• Machine Learning
• +۲ مورد دیگر

Pietro Lio' is a Professor of Computational Biology at the University of Cambridge's Department of Computer Science and Technology, where he has held academic positions since 2003. He progressed from Lecturer to Senior Lecturer, Reader, and ultimately Professor (2018-present). His career includes prior roles as Associate Professor of Genetics at the University of Teramo and research positions at the European Bioinformatics Institute, University of Cambridge (Genetics/Zoology), and University of Southampton. Education: 1989: BSc in Electronic Engineering and Biology, University of Firenze 1995: PhD in Theoretical Genetics, University of Pavia 2007: PhD in Engineering (Non-Linear Dynamics & Complex Systems), University of Firenze Research Focus: Professor Lio' specializes in interdisciplinary approaches bridging computer science and biology. His primary research domains include computational biology, bioinformatics algorithms, machine learning (particularly graph neural networks), deep learning architectures, and complex network analysis. His work spans molecular to ecological scales, with applications in genomics, systems biology, and environmental modeling. Publication Trends: Recent work (2018-2020) demonstrates strong emphasis on graph neural networks (Graph Attention Networks, Deep Graph Infomax) and blockchain applications. Earlier publications (2015-2017) focus on ecological modeling, multi-omics integration, molecular communications, and single-cell genomics, reflecting consistent cross-disciplinary innovation. Awards and Honors: 2018: BITS Award (Bioinformatics Italian Society) 2017: Visiting Professorship at University of Padova 2016: BYRA First Prize (ISEM) & MCE Award Second Prize 2013-2015: Lagrange Fellowship 2011: European Commission Award for methodological innovation No information is available regarding student advising, grants, labs, or research teams in the provided materials.

Zhu Xiaoxiangمشاهده پروفایل

استاد

• Synthetic Aperture Radar
• Remote Sensing
• Global Urban Mapping
• +۴ مورد دیگر

Xiaoxiang Zhu is a Full Professor for Data Science in Earth Observation at Technical University of Munich (TUM) and Director of the International AI Future Lab (AI4EO). She leads interdisciplinary research on signal processing and machine learning applied to Earth observation (EO) data, addressing global challenges like urbanization and climate change. Her work focuses on extracting geoinformation from big EO datasets using innovative AI techniques. Education & Positions: Professor (W3) since 2019, TUM Former Head of EO Data Science Department at German Aerospace Center (DLR) Adjunct Teaching Professor (2013–2015) Research Interests: Deep learning in SAR and multispectral imagery Global urban morphology mapping Uncertainty quantification in AI models EO data fusion and big data analytics Climate change monitoring via satellite data Articles Trends: Her publications emphasize AI-driven solutions for EO challenges, including SAR tomography, benchmark datasets (e.g., So2Sat LCZ42), and uncertainty estimation in neural networks. Over 220 journal papers and 173 conference papers highlight her contributions to geosciences and remote sensing. Awards: IEEE Fellow (2021) ERC Grants (Starting & Proof of Concept) Heinz Maier-Leibnitz-Preis (2015) Member of German and Bavarian Academies of Sciences Advising & Grants: Supervised PhD students (e.g., Mou) Secured €10M+ in research funding Co-led Helmholtz AI Research Field MASTr (2019–2022) Labs & Teams: Founder of AI4EO Lab Co-leader of Munich Data Science Research School (MUDS) Member of ELLIS Society and IEEE committees

• Causal Inference
• Machine Learning
• Statistical Modeling
• +۴ مورد دیگر

Dr. Lucas Kook is a Researcher at the Department of Statistics and Mathematics, WU Vienna University of Economics and Business. His research focuses on causal inference, machine learning, and statistical modeling, with applications in sports analytics, medical data analysis, and healthcare outcomes. He actively develops R packages such as deeptrafo for neural network-based statistical inference. His work bridges theoretical advancements in distributional regression and practical implementations in healthcare and sports domains. Key research areas include algorithm development for significance testing in supervised learning, causal feature selection, and nonparametric methods for conditional independence. Recent studies explore the efficacy of thrombolytic therapies in retinal artery occlusion and the predictive power of deep learning models in stroke patient outcomes. Collaborations span interdisciplinary fields, emphasizing reproducibility and methodological rigor in simulation studies.

• Information Retrieval
• Machine Learning
• Natural Language Processing
• +۳ مورد دیگر

Prof. Allan Hanbury is a full professor at TU Wien's Faculty of Informatics, leading the E-Commerce Research Area. His work focuses on domain-specific systems for information extraction and retrieval, with expertise in machine learning, natural language processing, and medical informatics. Key projects include developing tools like CRUISE-Screening for systematic literature reviews and VoMBaT for high-recall search evaluation. He coordinates initiatives in transparent automated content moderation and image mining for patents. His research bridges theoretical advancements with practical applications in healthcare, legal domains, and digital humanities. Publications span over 240 works, emphasizing reproducibility, explainability in AI, and cross-lingual systems. Active in organizing conferences like PatentSemTech and contributing to CLEF challenges. Advises on thesis topics involving hate speech detection, legal text analysis, and graph-based methods. Collaborates internationally on projects like CSMeD (clinical trial matching) and BRISE (legal corpus development). His work integrates NLP, IR, and data mining to address real-world challenges in information access and AI transparency.