جست‌وجوی استاد و پژوهشگر

• Supply Chain Management
• Logistics
• Cybersecurity
• +۴ مورد دیگر

Larissa Schachenhofer is a researcher at the Institute of Production and Logistics within the Department of Economics and Social Sciences at the University of Natural Resources and Life Sciences, Vienna (BOKU). She holds a Diplom-Ingenieur degree along with BSc and MA qualifications, and maintains an active research profile in supply chain management and cybersecurity. Her research focuses on supply chain resilience, particularly examining the impacts of cyber incidents and internet outages on critical infrastructure and logistics networks. She investigates how cascading effects from digital disruptions affect physical supply chains, with special attention to food security systems and healthcare sectors. Her work employs system dynamics modeling to analyze complex interdependencies in modern supply networks. Dr. Schachenhofer's publication record shows a consistent focus on internet dependency in supply chains, with recent publications examining consequences of prolonged internet blackouts and systemic risk management approaches. Her research demonstrates strong practical application through collaborations with Austrian security agencies and industry partners. She actively contributes to the academic community through presentations at international conferences including ORAHS, CriM Cyber Security Seminars, and STS Conferences. Her work addresses critical contemporary challenges in digital supply chain security, with projects funded by the Austrian Research Promotion Agency running through 2026.

• Machine Learning for Visual Computing
• Big Data Visualization and Analytics
• Data Science and High-Performance Computing (HPC)
• +۴ مورد دیگر

Soumya Dutta is an Assistant Professor in the Department of Computer Science and Engineering (CSE) at the Indian Institute of Technology Kanpur (IITK) since 2022. He previously held positions at Los Alamos National Laboratory as a Postdoctoral Researcher (2018-2019) and Scientist II (2019-2022). Dr. Dutta earned his Ph.D. and M.S. in Computer Science from The Ohio State University (2011-2018) and a B.Tech in Electronics and Communication Engineering from the West Bengal University of Technology (2005-2009). His research lies at the intersection of Machine Learning , Visual Computing , Big Data Analytics , and High-Performance Computing (HPC) . He focuses on developing scalable solutions for extreme-scale data, such as exascale simulations, social media, IoT, and healthcare. His work emphasizes uncertainty quantification in AI models and interactive visualization techniques. Dr. Dutta’s recent publications highlight his expertise in in situ visualization for climate modeling, implicit neural representations for uncertainty-aware rendering, and statistical sampling for exascale systems. His funded projects include AI-driven data analytics frameworks and deepfake defense mechanisms supported by ISRO, SERB, and C3iHub. Scientific Awards include Best Reviewer (TVCG), Best Paper (ISAV, TopoInVis), and LAAP Award (LANL).

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).

• International Economics
• Global Value Chains
• Trade Policy
• +۳ مورد دیگر

Robert Stehrer is the Scientific Director at the Vienna Institute for International Economic Studies (WIIW) and a Lecturer in Economics at the University of Vienna. His expertise spans international integration, trade policy, technological development, and labour markets. He holds degrees from the Johannes Kepler University Linz (Economics) and the Institute for Advanced Studies (IHS) Vienna (Sociology). His research focuses on global value chains, the impact of technological change on employment, and the analysis of international production networks. He has contributed to major EU-funded projects like EU KLEMS, WIOD, and PRONTO, collaborating with institutions such as the European Commission and OECD. Key research themes include the role of China in knowledge diffusion, energy-renewables ecosystems, and the effects of automation on wages. His work bridges empirical analysis with policy-relevant insights, addressing challenges like trade barriers and global supply chain dynamics. He has advised on EU trade policies, including the EU-Japan EPA, and explored the implications of geopolitical shifts, such as the Ukraine-Russia conflict. His interdisciplinary approach integrates econometrics, structural analysis, and policy evaluation to address contemporary economic issues.

Robert Legensteinمشاهده پروفایل

استاد

• Computational Neuroscience
• Neuromorphic Computing
• Spiking Neural Networks
• +۳ مورد دیگر

Dr. Robert Legenstein is a Full Professor and Institute Head at the Institute of Machine Learning and Neural Computation , Graz University of Technology. He serves as Speaker of the Graz Center for Machine Learning and Action Editor for Transactions on Machine Learning Research (TMLR) . His research bridges computational neuroscience and machine learning, focusing on neuromorphic computing systems that mimic biological neural networks. Research Leadership: Leads EU-funded projects like Adaptive Optical Dendrites (FET-Open) , SYNCH (FET-Proactive) , and Stochastic Assemblies in SNNs (FWF) . Scientific Contributions: Develops learning algorithms for spiking neural networks (SNNs), with applications to memristive architectures, neuroprosthetics, and energy-efficient AI systems. Key Publications: 15+ recent works on topics including dendritic computing, hardware-aware training, and context-dependent neural processing. Teaching Roles: Offers courses like Deep Learning , Principles of Brain Computation , and Data Structures & Algorithms . Contact: robert.legenstein@tugraz.at | +43 316 873 5824 | Inffeldgasse 16b/I, 8010 Graz, Austria.

• Bioprocess Engineering
• Protein Chromatography
• Continuous Manufacturing
• +۷ مورد دیگر

Jürgen Beck is a researcher in Bioprocess Engineering at the University of Natural Resources and Life Sciences, Vienna (BOKU), affiliated with the Department für Biotechnologie und Lebensmittelwissenschaften and the Institut für Bioverfahrenstechnik. He is actively engaged in research related to biopharmaceutical purification, particularly continuous chromatography and process modeling. His research focuses on advancing integrated continuous manufacturing in biopharma, with emphasis on multi-column chromatography, protein adsorption dynamics, mass transfer mechanisms, and hybrid modeling combining mechanistic equations with machine learning. His work addresses challenges in parameter estimation, flow non-uniformities, and resin performance, aiming to improve separation efficiency and scalability. The recent publications and conference presentations (2018–2024) demonstrate a strong trend in bioprocess intensification , chromatographic modeling , and continuous biomanufacturing , particularly for recombinant proteins and monoclonal antibodies. His work bridges experimental characterization with computational modeling to optimize bioprocesses. He has not received any scientific awards listed in the provided data. Jürgen Beck has delivered numerous lectures at international conferences such as PREP, Recovery of Biological Products, and ECAB. He collaborates closely with researchers including R. Hahn and E. von Lieres. No information is available about student supervision or external funding. He is involved in knowledge transfer through conference presentations and scientific dissemination. He is part of a research group focused on bioprocess development and modeling, contributing to advancements in industrial biopharmaceutical production processes.

• Network Security
• Privacy Enhancing Technologies
• Digital Identity
• +۴ مورد دیگر

René Mayrhofer is a full Professor at the Institute of Networks and Security, Johannes Kepler University Linz, leading the LIT Secure and Correct Systems Lab. With over 137 research outputs and active leadership in projects like the Christian Doppler Laboratory for Private Digital Authentication (Digidow), he is a key figure in network security and privacy research. His research focuses on practical security solutions for real-world systems, particularly in digital identity management , Tor network security , and mobile device authentication . Recent work addresses critical challenges in Android security states, biometric systems, and trusted execution environments, emphasizing deployable privacy-preserving architectures for physical-world applications. Analysis of his 15 most recent publications reveals strong trends in empirical security evaluation (e.g., Android device security studies) and system hardening (e.g., attested builds and backdoor mitigation), with growing emphasis on supply chain security and decentralized identity frameworks. Professor Mayrhofer has supervised 12 students and currently manages 6 research projects, including the active Digital Shadows initiative (funded until 2025) and the Digidow laboratory (running through 2026). His grants include significant support from federal authorities and the Austrian Research Promotion Agency. As principal investigator of the LIT Secure and Correct Systems Lab, he drives interdisciplinary research in secure communication protocols, privacy-aware authentication, and verifiable computing systems, collaborating with industry partners on real-world deployment challenges.

Farzaneh Darbanianمشاهده پروفایل

پژوهشگر

• Supply Chain Management
• Data Analytics
• Predictive Maintenance
• +۳ مورد دیگر

Farzaneh Darbanian is a researcher at the LOGISTIKUM – Steyr Center of Excellence Logistics , embedded within the University of Applied Sciences Upper Austria . She holds an MSc and has acted as both Principal Investigator and Co-Investigator on multiple funded projects since 2019. Research Interests: End-to-end supply chain optimisation using advanced data analytics. Predictive maintenance and resource assignment in service industries. Deep-learning-driven demand forecasting in grocery retail. Text-mining and sentiment analysis for service-quality assessment. Her recent work explores predict-then-optimise frameworks that couple machine-learning models with operational decision-making, especially for holiday-driven retail demand and maintenance scheduling in geographically distributed networks. Projects & Funding: LOG-JRC PREVAIL (2023–2027): Josef-Ressel-Center project on predictive value-network intelligence. Predictive Service and Maintenance (2021–2022): Resource allocation under decision-dependent uncertainty. NEXT (2019–2022): Pattern-recognition and extended value-network foresight. Scientific Output: 18 peer-reviewed contributions (2019-2025) including journal articles, conference papers, and book chapters indexed in Scopus and Procedia Computer Science.

• Plant Developmental Biology
• Hormonal Networks
• Auxin Signaling
• +۵ مورد دیگر

Eva Benková is a Professor and Dean of the Graduate School at the Institute of Science and Technology Austria (ISTA). She leads the Benková Group focused on Plant Developmental Biology, investigating how plants integrate environmental signals through complex hormonal networks. Her research has significantly advanced our understanding of auxin and cytokinin signaling pathways and their roles in plant adaptation to environmental conditions. Benková received her academic training through postdoctoral positions at the Max Planck Institute for Plant Breeding in Cologne and the Centre for Plant Molecular Biology in Tübingen. She held a habilitation position at the University of Tübingen before establishing her independent research group at the Flanders Institute for Biotechnology and later at the Central European Institute of Technology. In 2013, she joined ISTA as an Assistant Professor and was promoted to Professor in 2016. Her research interests center on plant hormonal networks, with particular focus on: How plants integrate environmental signals through hormonal signaling cascades Auxin and cytokinin crosstalk in root development Nitrate-hormone interactions in nutrient-dependent growth Mechanisms of hormonal network establishment and maintenance Transport-dependent auxin distribution and its regulation Convergence points that integrate different hormonal inputs Analysis of her recent publications reveals a strong emphasis on the molecular mechanisms underlying plant adaptation, particularly through hormonal signaling networks. Her work increasingly integrates advanced imaging techniques, computational modeling, and systems biology approaches. A significant portion of her research examines the intersection of nutrient signaling (particularly nitrate) with hormonal pathways that control root development. Benková's scientific achievements have been recognized with several prestigious awards: EMBO Membership (2017) Highly Cited Scientist designation (2014) FWF-ANR Bilateral Grant (2014) FWO Grants (2011) ERC Starting Grant (2008) Margarete von Wrangell Habilitation Program (2003-2007) As an academic mentor, Benková supervises multiple PhD students and postdoctoral researchers. Her lab includes PhD students David Babic, Valentin Leitner, Stefan Riegler, Tereza Tomickova, Ljupka Trajkova Petrova, and Yiqun Wang, as well as postdocs Marina Borges Osorio and Dekel Cohen Hoch. Her research is supported by grants including an Austrian Science Fund grant for her nitrate project. The Benková Group maintains a specialized research platform including a vertical confocal microscope (LSM700) equipped with root tracker software, enabling long-term observations of root growth in real time. This technology has been instrumental in their discoveries regarding the earliest changes in root growth in response to environmental stimuli.

Cornelia Staritzمشاهده پروفایل

دانشیار

• Development Economics
• International Trade Policy
• Global Value Chains
• +۳ مورد دیگر

Cornelia Staritz is an Associate Professor at the University of Vienna's Faculty of Social Sciences, Department of International Development. Her research focuses on development economics, global value chains, labor rights in global production networks, and commodity-based development. She is a member of the Vienna Doctoral School of Social Sciences (ViDSS) Steering Committee and the Doctoral Advisory Board. Her work critically examines power asymmetries in globalized trade and financial systems, with a regional focus on Africa and Southeast Asia. Key research areas include: Global trade, production networks, and structural transformation Labour regimes and struggles in global production Financialisation and commodity markets Recent publications analyze the EU-Vietnam Free Trade Agreement's impact on labor, critical minerals (lithium, copper) in green transitions, and supply chain resilience post-pandemic. She leads projects funded by the Austrian Science Fund (FWF) and Danida Fellowship Center, exploring socio-ecological transformation and commodity governance. Her work emphasizes policy implications for socially responsible public procurement, industrial policy, and sustainable development in global production networks.

Alexia Fürnkranz-Prskawetzمشاهده پروفایل

استاد

• Population Economics
• Demography
• Economics of Ageing
• +۳ مورد دیگر

Alexia Fürnkranz-Prskawetz is a Professor of Mathematical Economics at TU Wien (since 2008) and Deputy Director of the Vienna Institute of Demography (VID) at the Austrian Academy of Sciences (since 2020). She holds leadership roles in multiple institutions, including the Wittgenstein Centre for Demography and Global Human Capital and the International Institute for Applied Systems Analysis (IIASA). Her academic career includes roles as Head and Deputy Head of departments at TU Wien and leadership in research groups at prestigious institutions like the Max Planck Institute for Demographic Research. Education: Technical Mathematics (degree not specified) and a postgraduate economics study as a Fulbright scholar at the University of Chicago. She earned a second doctorate (Habilitation) in Population Economics and Applied Econometrics from TU Wien in 1998. Research focuses on the economic consequences of population ageing, long-run economic growth, and agent-based computational demography. Key areas include nonlinear dynamic models, life cycle models, and optimal control theory applied to demographic and economic interactions. Recent work addresses pension system equity, automation’s impact on wage inequality, and the demographic dividend from education. Awarded the Figdor Prize (2003), elected to Leopoldina (2015), and a Full Member of the Austrian Academy of Sciences (2011). She has secured grants from FP7, WWTF, FWF, and JPI, focusing on ageing’s economic impacts and demographic modeling. Labs/Teams: Director of Wittgenstein Centre and core member of VID and IIASA research groups. Active in refereeing for journals like Demographic Research and Journal of Economic Growth, and a member of societies such as the Verein für Socialpolitik and IUSSP.

• Relativistic heavy ions
• High energy nuclear physics
• Nuclear instrumentation
• +۵ مورد دیگر

Paolo Giubellino is an experimental physicist specializing in High-Energy Nuclear Collisions, with significant contributions to relativistic heavy-ion research at CERN SPS and LHC. Since 2006, he has been a Research Director at INFN Torino (currently on leave), and since 2011, a Visiting Professor at CERN's Experimental Physics Division. ALICE Collaboration Spokesperson (2011-present) Deputy Spokesperson for ALICE (2004-2010) Chaired GSI's G-PAC committee Member of IN2P3's Conseil Scientifique and Spanish infrastructure commission His work explores ultra-dense matter created in heavy-ion collisions, focusing on quark-gluon plasma characterization through flow measurements, jet quenching, and detector development. He has led ALICE's Upgrade Proposal (2020-2028) approved in 2012. Recent publications (2010-2016) span heavy-ion collisions, detector performance, and particle correlations. These studies employ ALICE's advanced instrumentation at CERN LHC to investigate plasma properties and test QCD predictions. Lise Meitner Prize (2014) Enrico Fermi Prize (2013) Commendatore honor (2012) Mexican Physical Society Medal (2010) Actively involved in international collaborations, he contributed to EU/NATO-funded projects and sits on scientific advisory committees globally. His research integrates experimental nuclear physics with cutting-edge detector technologies.

Matthias Raddantمشاهده پروفایل

پژوهشگر

• Financial Risk
• Asset Pricing Models
• Financial Integration
• +۳ مورد دیگر

Dr. Matthias Raddant is a researcher at the University for Continuing Education Krems, affiliated with the Department for Knowledge and Communication Management, and a resident scientist at the Complexity Science Hub in Vienna. He holds a PhD in quantitative economics from Kiel University. Previously, he served as an assistant professor at Kiel University and a post-doctoral researcher at the Kiel Institute for the World Economy. His research focuses on financial risk, asset pricing models, corporate governance, economic networks, and sustainability. He has explored topics such as interdependencies in financial markets, corporate board dynamics, and the application of network theory to economic systems. His work bridges econophysics and traditional financial economics, emphasizing systemic risk and interconnectedness. Key publications include analyses of global financial market interconnectedness, corporate board networks, and the use of trade data for mineral resource flow studies. He is an associate editor for SN Business and Economics and contributes to policy advice on sustainability and financial systems. Labs/Teams: Platform for Sustainable Development (Krems), Complexity Science Hub Vienna.

• Machine Learning
• Computer Vision
• Robust Learning
• +۷ مورد دیگر

Christoph H. Lampert is a Professor at the Institute of Science and Technology Austria (ISTA), leading the Machine Learning and Computer Vision Group. His research focuses on creating robust, fair, and verifiable machine learning systems with strong theoretical foundations. Academic Rank: Professor (ISTA) Research Focus: Machine Learning, Computer Vision, Robustness, Fairness, Formal Verification Editorial Roles: Action Editor (JMLR), Former Editor (IJCV), Associate Editor-in-Chief (TPAMI) His recent publications explore robust deep learning architectures, formal verification of neural networks, and fairness in multi-source learning environments. Research keywords span neural network design, algorithmic accountability, and structured data modeling. Scientific achievements include: DARPA Disruptive Ideas award (2023) ISTA Alumni Award (2023) He has mentored numerous PhD students including: Bernd Prach (2022 thesis: Robust image classification with 1-Lipschitz networks) Egor Zverev, Nikita Kalinin, Hossein (Qualifying Exam passed 2023-2025) Alex Peste (2023 thesis: Robustness and Fairness in Machine Learning) Mary Phuong (2021 thesis: Underspecification in Deep Learning) Amelie Royer (2020 thesis: Computer Vision applications) Alexander Kolesnikov (2018 thesis: Weakly-Supervised Segmentation) Alex Zimin (2018 thesis: Dependent data learning)

• Software Engineering
• Programming Languages
• Static Analysis
• +۴ مورد دیگر

Michael Schröder is a Researcher at TU Wien's Faculty of Informatics, affiliated with the Institute of Software Technology. He holds a BSc and a Dipl.-Ing. (Master's equivalent) in Informatics. His research focuses on software engineering, static analysis, and programming languages, with notable contributions to probabilistic program analysis, security, and empirical studies on developer workflows. Education : Bachelor of Science in Informatics Diplom-Ingenieur (Dipl.-Ing.) in Informatics from TU Wien Research Interests : His work spans static analysis of probabilistic programs, security in software repositories, grammar inference for ad hoc parsers, feature flag dependency analysis in large systems, and empirical studies on command-line tool customization. He has also contributed to medical research in pediatric oncology through a 2019 study on leukemia genetics. Recent Trends in Publications : Recent efforts emphasize language-agnostic static analysis frameworks (2024), lateral movement detection in source code (2023), and grammar inference techniques for parsers (2022). Earlier work includes neural ranking models (2020) and transactional memory systems (2015). Grants & Advising : No explicitly listed grants or student advisement, though recent theses supervised include static grammar inference projects (2025). Labs/Teams : Not explicitly mentioned in available records.