جست‌وجوی استاد و پژوهشگر

• Economic History
• Social History
• History of Economic Thought
• +۶ مورد دیگر

Lars Magnusson is a distinguished Full Professor of Economic History at Uppsala University, where he has held his position since 1992. He has served in significant leadership roles including Dean of the Faculty of Social Sciences (2012-2017) and Vice-Rector of Uppsala University (2005-2008). His academic influence extends internationally through visiting positions at prestigious institutions such as the École des hautes études en sciences sociales in Paris and the European University Institute in Florence. His scholarly work spans multiple interconnected fields of economic and social history. Magnusson has made significant contributions to the study of mercantilism, with particular focus on whether it remains a useful conceptual framework for understanding historical economic systems. His research on the long-term development of welfare state societies examines how Nordic models, particularly Sweden's, have evolved and responded to economic crises. He has also conducted extensive work on agricultural and industrial history, with specific analyses of sectors like the cutlery industry during industrialization. His interest in working life studies connects to broader investigations of social and economic history, while his intellectual history work explores the evolution of economic and social thought through figures like Malthus and concepts like "envy and emulation." The trends in his recent publications reveal a consistent focus on historical political economy with particular attention to Scandinavian contexts. His scholarly output demonstrates a methodological approach that combines deep historical analysis with contemporary economic theory, often examining how historical economic systems inform current policy debates. While maintaining a strong focus on Swedish and Nordic economic history, his work consistently places these national cases within broader European and global contexts. The recurring themes across his publications include the evolution of economic thought, the relationship between state intervention and market forces, and the historical development of institutional frameworks that shape economic outcomes. His major scholarly recognitions include: Full member of Royal Swedish Academy of Sciences Full member of Royal Society of Sciences, Uppsala Chair of the Board of the Swedish Collegium for Advanced Study (2004-2016) 2006 Honorary Doctor of Kyoto University Member of the Committee for the Nobel Prize in Economics (2005-2009) 2019 Full member of the Board of the Swedish Research Council Research Fellow of the Max Planck Institute for History (multiple occasions) While specific doctoral students aren't listed in the available information, Professor Magnusson's extensive editorial roles suggest significant mentorship activities. He has served as Editor of "Swedish Historical Journal" (1988-1994), co-Editor of "Economic and Industrial Democracy" (2000-present), and co-Editor of "Scandinavian Economic History Review" (2008-2012). His leadership positions, including Research Director at the National Institute for Working Life (1996-2005) and Chairman of SALTSA (1997-2007), indicate substantial grant management experience directing large-scale research initiatives focused on working life. His involvement with organizations like MISTRA and the Wallenberg Academy Fellows programme further demonstrates his role in shaping research funding priorities in Sweden. Professor Magnusson has been instrumental in establishing and leading several significant research entities. Most notably, he served as Chairman of the Swedish Collegium for Advanced Study (SCAS) from 2004 to 2016, an institution that brings together leading international scholars for advanced interdisciplinary research. His work with SALTSA (1997-2007) created a collaborative framework between labor organizations (LO, TCO, SACO) and research institutions focused on working life studies. His international collaborations, particularly through repeated visiting positions at EHESS in Paris and EUI in Florence, have fostered transnational research networks in economic and social history.

• Systems
• Concurrency
• Memory Management
• +۵ مورد دیگر

Christoph Kirsch is a Professor and Chair of the Department of Computer Science at the University of Salzburg. He also serves as Chair of the Programming Research Laboratory at the Faculty of Information Technology, CTU Prague. His research focuses on systems, concurrency, memory management, and formal methods, with notable contributions including the Selfie educational software project and work on symbolic execution. He is a prolific author with over 50 publications in top venues like LCTES and EMSOFT. Education: Ph.D. in Computer Science (details not specified). His teaching includes courses on elementary computer science concepts and curricula development. He advises students such as Anna Bolotina and has graduated over a dozen PhD students. Research highlights include the Selfie system (self-referential C compiler and emulator), work on concurrency primitives like Scal and Timestamped Stack, and contributions to real-time systems (Logical Execution Time, Variable-Bandwidth Servers). His recent focus includes teaching digital thinking and evaluating eval in R programs. He has organized conferences like MPLR’24 and served on program committees for EuroSys and RTNS. His book Elementary Computer Science emphasizes foundational concepts for broad audiences.

Alireza Furutanpeyمشاهده پروفایل

پژوهشگر

• Edge Computing
• Edge Intelligence
• Distributed Inference
• +۳ مورد دیگر

Alireza Furutanpey is a University Assistant (PreDoc Researcher) at TU Wien's Distributed Systems Group within the Institute of Information Systems Engineering, holding a Master's degree with distinction. His academic role combines research in distributed systems with teaching responsibilities for core computer science courses. His educational background includes: Bachelor of Science (BSc) Master of Science (Dipl.-Ing.) with distinction Furutanpey's research centers on Edge Computing and Edge Intelligence, specializing in Distributed Inference, Neural Data Compression, and AI-Systems integration. He pioneers techniques for neural feature compression in satellite/edge environments and develops frameworks for federated learning orchestration under communication constraints. His work bridges theoretical AI with practical system implementation, focusing on resource-constrained scenarios where bandwidth and computational efficiency are critical. Analysis of his 15+ publications reveals dominant trends in neural compression for distributed systems (60%), federated learning optimization (25%), and serverless edge frameworks (15%). Key contributions include solving satellite downlink bottlenecks through feature compression and enabling adaptive inference in heterogeneous edge networks, with methodologies increasingly incorporating generative modeling and robustness against adversarial attacks. Scientific Awards: None documented in available sources. He actively supervises master's theses, guiding students on adversarial machine learning, neural compression, and image retrieval systems. His research is supported through major projects: AloTwin (2023-2025) focusing on edge intelligence, INTEND (2024-2026) on industrial IoT, and TEADAL (2022-2025) on federated learning. He serves as a reviewer for 15+ IEEE/ACM venues including IEEE Transactions on Mobile Computing and ICDCS. Furutanpey operates within TU Wien's Distributed Systems Group, which specializes in edge-cloud continuum research. The team develops tools like faas-sim for serverless edge simulation and explores quantum-classical hybrid architectures, maintaining strong industry collaborations in industrial IoT and satellite communications.

• Computer Architecture
• Compilers
• Programming Languages
• +۴ مورد دیگر

Andreas Krall is an Associate Professor in the Department of Software Technology at TU Wien's Faculty of Informatics. He holds roles as Curriculum Coordinator for the Bachelor Informatics and Bachelor Software and Information Engineering programs, and serves as a Substitute Member of the Curriculum Commission for Informatics. His research focuses on compiler design, architecture description languages (e.g., VADL), and formal methods for ensuring correctness in compiler-processor co-design. Key research areas include computer architecture, compiler verification, embedded systems, and the development of tools for processor simulation and optimization. Krall has led projects such as 'Correct Compilers for Correct Processors' (2010–2015) and contributed to the CACAO JVM project. He has published extensively on topics like instruction selection, abstract state machines (CASM), and SSA-based optimizations. Notable awards include the Heinz Zemanek Preis (1987). His work spans over 30 years, with contributions to both academic research and industry-relevant tools like the VADL architecture description framework. Krall has advised numerous students in topics ranging from compiler backends to garbage collection algorithms.

• Computer Science
• Network Security
• Malware Detection
• +۴ مورد دیگر

Engin Kirda is a researcher at the Department of Distributed Systems , Vienna University of Technology . His work focuses on Network Security , Malware Detection , and Web Security , with a particular emphasis on Malware Analysis , XSS Prevention , and Botnet Detection . He has led and contributed to projects such as WOMBAT , SECoverer , and SysSec , funded by entities like the Austrian Research Promotion Agency (FFG) and the European Commission . Research Areas : Network Security, Malware Analysis, Web Application Vulnerabilities Key Projects : WOMBAT (2008–2011), SECoverer (2008–2011), SysSec (2010–2014) His publications highlight advancements in automated malware analysis , phishing detection , and web spam mitigation . He has mentored students in topics including Android security , CSV Attack Prevention , and Malware Threat Landscapes .

• Cybersecurity
• Information Security
• IoT Security
• +۶ مورد دیگر

Martina Lindorfer is an Associate Professor at the Department of Security and Privacy, Faculty of Informatics, Technische Universität Wien (TU Wien). Her primary roles include academic research and teaching in cybersecurity, privacy engineering, and IoT security. She coordinates the Women in Informatics initiative and leads research projects addressing critical security challenges across mobile, IoT, and cloud ecosystems. Dr. Lindorfer holds a Dipl.-Ing. (BSc) and a PhD in Technical Informatics from TU Wien (2011 and 2015, respectively). Her research focuses on malware analysis, mobile security, and privacy-preserving technologies. Notable projects include the WWTF-funded IoTIO initiative analyzing IoT device vulnerabilities and the W4MP project exploring cross-platform malware threats. Key research interests span: Cybersecurity frameworks for IoT ecosystems Privacy implications of smart TV protocols (HbbTV) Mobile app vulnerability analysis APT campaign attribution through file forensics Academic cloud migration risks Her work bridges technical analysis with societal impacts, addressing topics like surveillance technology and academic freedom in cloud environments. Lindorfer has supervised over 20 graduate students, with recent theses focusing on rootkit detection, ART-based app diffing, and privacy in configuration repositories. Current grants include: IoTIO (2020–2025): Securing IoT ecosystems W4MP (2023–2027): Cross-platform malware research Browsec (2018–2024): Browser security analysis Her lab develops tools like C2Miner (C2 server detection) and FlowPrint (encrypted network fingerprinting), contributing to both academic and industry standards. Lindorfer actively collaborates with organizations like the European Commission and FFG on cybersecurity policy and threat mitigation strategies.

• Computer Security
• Hardware Design
• Embedded Systems
• +۳ مورد دیگر

Daniel Große serves as a full Professor at Johannes Kepler University Linz, holding primary affiliation with the Institute for Symbolic Artificial Intelligence and secondary appointments at the Institute of Complex Systems and LIT Secure and Correct Systems Lab. He currently leads 3 major research projects including Modular Real-Time Control (2023-2026) and the ENGEL Austria GmbH industry collaboration (2019-2027), while maintaining active roles in 113 professional activities through 2025. His research integrates Computer Security , Hardware Design , and Artificial Intelligence to address critical challenges in embedded systems. Key focus areas include cryptographic instruction chaining for control flow protection, RISC-V vector workload simulation, and LLM-assisted metamorphic testing of graphics libraries, with strong emphasis on practical applications for safety-critical systems. Recent publications (2025) reveal a cohesive research trajectory toward secure computing foundations, combining formal verification techniques with AI-driven development tools. His work consistently bridges hardware security primitives and software engineering innovations, particularly targeting vulnerabilities in instruction set architectures and embedded graphics pipelines. Prof. Große has supervised 4 graduate students and secured significant funding through both public grants (VerA project) and industry partnerships. His project portfolio demonstrates strategic balance between theoretical advances in arithmetic circuit verification and applied industrial solutions for real-time control systems. As a core member of the LIT Secure and Correct Systems Lab, he contributes to interdisciplinary research initiatives developing formally verified secure computing platforms, with active collaborations spanning hardware security validation, virtual prototyping frameworks, and AI-enhanced software testing methodologies.

• Bayesian statistics
• Uncertainty quantification
• Expert elicitation
• +۲ مورد دیگر

Jeremy Oakley is Professor of Statistics and Head of the School of Mathematical and Physical Sciences at the University of Sheffield. His work spans Bayesian statistics, uncertainty quantification for complex computer models, expert elicitation of probability distributions, and health-economic applications. Research Interests Bayesian statistics and inference Uncertainty quantification (UQ) for computer models Expert elicitation of probability distributions Health-economic modelling He co-developed the Sheffield Elicitation Framework (SHELF) , a widely-used set of protocols and software tools for structured expert judgement. Teaching & Supervision Professor Oakley teaches undergraduate and postgraduate statistics modules and supervises PhD students within SoMaS and in collaboration with other departments, focusing on UQ and expert-elicitation topics. Contact Email: j.oakley@sheffield.ac.uk

Juan Luis Herrera Gonzalezمشاهده پروفایل

پژوهشگر

• Computing Continuum
• Microservice Orchestration
• Network Management
• +۷ مورد دیگر

Juan Luis Herrera Gonzalez is a Postdoctoral Researcher at the Distributed Systems Group within the Faculty of Informatics at Technische Universität Wien (TU Wien) . Previously affiliated with the University of Extremadura, University of Pisa, and University of Bologna, his research focuses on Computing Continuum systems, microservice orchestration, network optimization, and sustainability in distributed environments. PhD in Computer Science (University of Extremadura, 2023) Collaborator with 8 universities across 4 countries 50+ publications with 270+ citations His work addresses Quality of Service (QoS), economic cost reduction, and sustainability in domains such as IoT, 5G networks, and Digital Twins. Recent publications emphasize machine learning-driven SDN optimization, federated learning applications, and energy-efficient fog computing. He contributes to frameworks for adaptive analytics, xApp development, and latency minimization in hybrid infrastructures. His research portfolio spans from theoretical models using Mixed-Integer Linear Programming to practical implementations in testbeds for O-RAN and SDN-fog scenarios. Current projects include the Marie Skłodowska-Curie Actions fellowship, focusing on real-world deployments and developer-centric tools like EFCC (Emulation Framework for Cloud Continuum) and xSTART (xApp Simulation Environment).

• Symbolic Regression
• Genetic Programming
• Emulator Development
• +۴ مورد دیگر

Lukas Kammerer is a Research Fellow at the University of Applied Sciences Upper Austria, specifically affiliated with the Research Center Hagenberg Center of Excellence for Smart Production and the Focal area ICT - Information & Communications Technology. His work bridges computer science methodologies with astrophysical applications, particularly in symbolic regression and emulator development. His primary research areas include: Symbolic Regression and its theoretical foundations Genetic Programming efficiency analysis Development of analytic emulators for cosmological simulations Bias-variance tradeoffs in regression methods Precise modeling of matter power spectrum Nonlinear optimization techniques for function extraction Dr. Kammerer's publication record demonstrates strong interdisciplinary work connecting computer science with astrophysics. His recent publications show increasing sophistication in developing symbolic representations of complex physical phenomena, with applications ranging from machine learning benchmarks to cosmological modeling. The dual focus on methodological improvements in symbolic regression and their concrete applications in astrophysics represents a distinctive research trajectory. As a Co-Investigator on major research projects including the Josef Ressel Zentrum für Symbolische Regression (2018-2022) and EREMA Recycling 4.0 (2017-2019), he has secured significant research funding and collaborated with international teams across multiple scientific domains. His work is associated with the HEAL research group at the University of Applied Sciences Upper Austria, which focuses on computational methods for scientific applications, particularly in the domains of symbolic regression and its practical implementations.

Wolfgang Maassمشاهده پروفایل

استاد

• Neural Networks
• Machine Learning
• Computational Neuroscience
• +۳ مورد دیگر

Wolfgang Maass is a Professor at the Institute of Machine Learning and Neural Computation at Technische Universität Graz . His research focuses on computational neuroscience, neuromorphic engineering, and machine learning, with an emphasis on understanding how biological neural networks process information and inspire artificial systems. He has contributed extensively to the development of spiking neural networks, synaptic plasticity models, and neuromorphic hardware. Education: Dipl.-Ing. (Diploma in Engineering), Dr.rer.nat. (PhD in Natural Sciences) Affiliations: Institute of Machine Learning and Neural Computation, TU Graz Key research interests include: Neural network models for cognitive functions Biologically plausible learning algorithms Neuromorphic computing and hardware implementations Computational principles of cortical microcircuits Recent work highlights the integration of biological principles into artificial intelligence, including studies on synaptic plasticity (BTSP), spiking neural networks for image recognition, and energy-efficient neuromorphic systems. His research bridges theoretical neuroscience and applied machine learning, with a focus on systems that emulate brain-like functionality. He has presented at major conferences such as the International Convention on the Mathematics of Neuroscience and AI and has authored over 200 publications. His work has been recognized for its interdisciplinary impact, advancing both neuroscience and AI fields.

• Synthetic Biology
• Artificial Cells
• Membrane Engineering
• +۱۰ مورد دیگر

Dr. Cherng-Wen Darren Tan is a faculty member at the Institute of Synthetic Bioarchitectures, Department of Biotechnology and Food Science, University of Natural Resources and Life Sciences, Vienna (BOKU). His research focuses on engineering artificial cellular systems for biomedical applications, particularly in disease treatment and drug delivery. He has been actively involved in advancing synthetic biology through the development of artificial cells, cytoplasts, and decoy systems targeting diseases such as HIV/AIDS. PhD, National University of Singapore (2009) BSc (Hons), Cell and Molecular Biology, National University of Singapore (1999) His research interests include synthetic biology, artificial cells, membrane engineering, polymersomes, targeted drug delivery, and microfluidics . He applies these to model and treat human diseases by creating biomimetic systems that replicate cellular functions. His work bridges fundamental science with translational engineering, aiming to solve real-world medical challenges. The 15 most recent publications highlight a strong trend in bottom-up synthetic biology , with emphasis on constructing functional cellular mimics using polymersomes and cell-derived vesicles. Key themes include membrane protein integration, in vitro protein synthesis, and microfluidic analysis of cell behavior. His work spans disciplines such as biophysics, nanotechnology, and biomedical engineering. President Graduate Fellowship, National University of Singapore (2005) Dr. Tan has supervised numerous master’s theses and contributed to research projects funded by the Austrian Science Fund (FWF). He has also served as a guest editor for Micromachines and performed peer review for funding agencies like the European Research Council. His lab focuses on creating functional synthetic bioarchitectures that emulate natural cell systems for therapeutic and diagnostic applications.

Neda Ghiassiمشاهده پروفایل

پژوهشگر

• Urban Energy Modeling
• GIS Applications
• Sustainable Architecture
• +۳ مورد دیگر

Neda Ghiassi is an affiliated researcher at TU Wien's E259 - Institut für Architekturwissenschaften , focusing on urban energy modeling and computational frameworks. Her work integrates Geographic Information Systems (GIS), data analysis, and interdisciplinary approaches to address urban energy challenges. Key projects include MOTIVE (vacuum glass integration in construction) and EMULATE (urban energy assessment tools). She has published extensively on topics like high-resolution energy modeling, building product data handling, and cluster analysis for urban systems. Her research emphasizes sustainable urban development through innovative computational methods, bridging technical, social, and policy dimensions. She collaborates on projects funded by Research Studios Austria and contributes to teaching via research-guided courses. Notable outputs include a doctoral thesis on an hourglass model for urban energy systems and reports detailing project advancements in energy efficiency and building technology. Her expertise spans technical documentation, multi-stakeholder data collaboration, and scenario-based modeling. Current work explores human-centric energy modeling (MAIN_STREAM) and semantic web approaches for building product data. No awards are explicitly listed, but her contributions reflect significant engagement in academic and applied research.