جست‌وجوی استاد و پژوهشگر

Philip Waltherمشاهده پروفایل

استاد

• Quantum Computing
• Quantum Information
• Quantum Cryptography
• +۳ مورد دیگر

Philip Walther is a Professor at the University of Vienna's Faculty of Physics, specializing in Quantum Optics, Quantum Nanophysics, and Quantum Information. He leads cutting-edge research in quantum computing, cryptography, and photonic processing. University of Vienna – Faculty of Physics Harvard University (Postdoctoral Researcher, 2006–2008) University of Latvia (Visiting Researcher, 2024) His research encompasses quantum superposition, indefinite causal order, and secure quantum networks. Key projects include GRAVITES (gravitational interferometry) and Quantum Secure Networks Partnership. Publications span quantum machine learning, entanglement distribution, and photonic processors. Recent collaborations focus on quantum cryptography and European research networks. He holds a 2020 Fellowship from the Optical Society of America and distinctions for quantum logic gates and secure protocols. Quantum-enhanced photonic processors Secure metropolitan fiber networks Gravitational interferometry with entangled states Walther actively participates in academic events like the EPIQUE Annual Meeting and contributes to public engagement through media appearances, including Scientia Global and IEEE publications.

• Artificial Intelligence
• Machine Learning
• Data Mining
• +۳ مورد دیگر

Yuxi Xia is a researcher affiliated with the Faculty of Computer Science, specializing in data mining and machine learning. Current research activities focus on artificial intelligence validation, surrogate modeling for railway systems, and multimodal question-answering frameworks. BSc, MSc in Computer Science Active in AI Review publications (2024) Research interests span large language model calibration , digital twin technologies , and model ensembling . Recent articles address overfitting, multimodal fusion, and ethical implications of machine-generated text detection. Key publication trends include industrial AI applications for railway systems, federated learning security, and explainability in black-box models. Collaborations extend to interdisciplinary AI validation studies.

Katharina Hoedtمشاهده پروفایل

پژوهشگر

• Adversarial Examples & Robustness
• Interpretable Machine Learning
• Neural Networks
• +۳ مورد دیگر

Katharina Hoedt is a University Researcher and Assistant at the Institute of Computational Perception at Johannes Kepler University Linz (JKU), with a Vienna-based research presence. She holds a PhD in Computer Science from JKU (2020) and has been involved in research roles since 2016, including at the Austrian Research Institute for Artificial Intelligence (OFAI). Her work focuses on adversarial machine learning, model interpretability, and neural network robustness, particularly within music information retrieval domains. Education: PhD in Computer Science (2019–2020), DI (Diploma) in Computer Science (2013–2016), Bachelor of Science in Informatics (JKU Linz). She has taught courses on Machine Learning and Pattern Classification, and Artificial Intelligence at JKU. Research Interests: Adversarial examples and robustness, interpretable machine learning, neural network inner workings, and applications in music classification. Her publications explore adversarial attacks, explanation validity, and model defense strategies in audio and music contexts. Labs/Teams: Active member of the Institute of Computational Perception, collaborating on interdisciplinary projects combining AI with musicology and signal processing.

• Reconfigurable Computing
• Parallel Computing
• FPGA Accelerators
• +۴ مورد دیگر

Prasanna Viktor is a Professor of Electrical and Computer Engineering and Computer Science at the University of Southern California (USC), holding the Charles Lee Powell Chair in Engineering. He also serves as Director of the Center for Energy Informatics and has held leadership roles in interdisciplinary research centers such as the USC Infosys Center for Advanced Software Technologies. With a BE from Bangalore University, ME from Indian Institute of Science, and PhD from Pennsylvania State University, he is a globally recognized expert in reconfigurable computing, FPGA accelerators, and parallel computing. His research focuses on high-performance architectures for applications in networking, security, HPC, and machine learning. Over 25 years, he has secured research grants totaling over $50M, including $12.9M from 2016–2021. He has advised over 70 doctoral students and published over 600 papers, earning 22 best paper awards. His work has led to IP cores with improved throughput, latency, and energy efficiency. Prasanna is a Fellow of the IEEE, ACM, and AAAS, and an elected member of Academia Europaea. He has received prestigious awards such as the W. Wallace McDowell Award (2015) and the Distinguished Alumnus Award from IISc (2019). He currently serves as Editor-in-Chief of the Journal of Parallel and Distributed Computing. He leads interdisciplinary efforts in energy informatics and smart oilfield technologies, bridging computer science, engineering, and energy sectors. His contributions include foundational work in reconfigurable computing and FPGA-based accelerators for diverse applications.

• Big Data
• Neuroimaging
• Model-Free Data Analysis
• +۴ مورد دیگر

Christian Beckmann is a Full Professor of Statistics in Imaging Neurosciences at Radboud University Medical Centre Nijmegen and a Principal Investigator at the Donders Institute for Brain, Cognition and Behaviour. His career spans institutions including the University of Twente, Imperial College London, and the University of Oxford, with a focus on interdisciplinary approaches integrating cognitive neuroimaging, imaging genetics, and pharmacology. Education: MSc and DPhil degrees at the University of Oxford (20014). His research centers on developing novel computational analysis methods for neuroimaging data, particularly Independent Component Analysis (ICA), applied to connectomics, imaging epidemiology, and big data analytics. He emphasizes creating sensitive, specific, and interpretable tools for neurobiological applications, such as the widely used FSL (FMRIB Software Library), which impacts over 650 institutions globally. Scientific Awards: Thomson Reuters/Clarivate Analytics Highly Cited Researcher (2014–2016) NWO VIDI Fellowship (2014) Wiley OHBM Young Investigator Award (2011) Membership, Young Academy, University of Twente (2011) Advising & Grants: He has trained over 20 PhD students (8 completed) and 9 postdoctoral researchers, securing grants from the Netherlands Organisation for Scientific Research and other international bodies. His work bridges technical innovation with clinical applications, advancing diagnostics and treatment strategies.

Olga Litvyakمشاهده پروفایل

پژوهشگر

• E-Governance
• Cybersecurity
• Political Communication
• +۴ مورد دیگر

Olga Litvyak serves as a Senior Researcher at the Center for E-Governance, University for Continuing Education Krems, Austria. Her work bridges e-governance, cybersecurity, and data-driven political communication analysis, with active contributions to Austrian federal/state-funded research initiatives focused on digital public administration. Dr. Litvyak's research centers on computational analysis of political discourse, media framing, and digital transformation in governance. She employs advanced NLP techniques (including BERTopic) to study election campaigns, parliamentary debates, and crisis communication patterns. Her expertise spans open data initiatives, cybersecurity education models, and digital product passports for sustainable industry practices, emphasizing practical applications for public sector innovation. Analysis of her 15 most recent publications (2022-2024) reveals three dominant trajectories: (1) Cybersecurity education frameworks using micro-credentials and active learning; (2) AI-driven analysis of political discourse in forestry management, election campaigns, and crisis response; (3) Digital transformation case studies in open data implementation and product passport systems. These streams consistently integrate machine learning with policy analysis across Austrian and European contexts. No scientific awards were documented in the source materials. Dr. Litvyak leads the project 'Evaluierung der Wirkung der Open Data Initiative der Stadt Wien' (funded by Austrian Bundesländer) and contributes to seven additional grants including 'Vinepredict' (mildew forecasting AI) and 'Future Skills 3'. Her collaborative projects with Gregor Eibl, Peter Parycek, and Thomas Lampoltshammer involve FFG, federal ministries, and state entities, focusing on cybersecurity, timber industry data sovereignty, and cyber-physical systems. While no formal students are listed, her principal investigator roles imply mentorship of junior researchers. As a core member of the Center for E-Governance, she operates within a multidisciplinary team advancing digital public services through partnerships with government agencies and industry stakeholders. The center serves as Austria's hub for e-governance innovation, particularly in data-driven policy evaluation and secure digital infrastructure development.

Hans Auerمشاهده پروفایل

استاد

• Energy Economics
• Energy Market Design
• Energy System Modeling
• +۴ مورد دیگر

Hans Auer serves as Professor in Energy System Economics and Head of the Energy Economics Group (EEG) at Vienna University of Technology (TU Wien) since 2024, with additional appointment as Adjunct Professor at the Norwegian University of Science and Technology (NTNU) since 2023. His leadership spans academic research, European project coordination, and energy policy development. Education: MSc in Electrical Engineering (1996) PhD in Energy Economics (2000) Venia Docendi in Energy Economics (2012) Research Focus: Professor Auer specializes in energy market design, system modeling, and decarbonization strategies with emphasis on renewable integration, sector coupling, and grid flexibility. His work bridges theoretical modeling with practical policy applications across European energy systems, addressing challenges from local communities to continental-scale transitions through advanced computational methods and economic analysis. Publication Trends: Recent publications (2023-2026) reveal concentrated research on European decarbonization pathways, hydrogen storage economics, electric vehicle integration, and peer-to-peer energy trading. Key thematic clusters include scenario modeling for 2050+ transitions, optimization of flexible resources in congested grids, and socio-technical analysis of local energy communities within circular economy frameworks. Academic Leadership: With over 25 years of supervision experience for bachelor, master, and PhD students, Professor Auer coordinates major European initiatives including PSS2030+ (power system security), iDesignRES (renewable integration tools), and RENVELOPE (building energy retrofits). His project portfolio demonstrates sustained funding success across EU Horizon programs and national research agencies. Operational Framework: Leading the EEG research unit within TU Wien's Institute of Energy Systems and Electrical Drives, he directs a multidisciplinary team conducting policy-relevant analysis for European Commission bodies, national regulators, and industry stakeholders through evidence-based modeling of energy transitions.

• Computer Architecture
• Embedded Systems
• RISC-V
• +۵ مورد دیگر

Prof. Daniel Müller-Gritschneder is a Full Professor of Computer Architecture at TU Wien's Institute of Computer Engineering (Faculty of Informatics) since 2024. Previously, he held roles as research group leader at TU Munich's Chair of Electronic Design Automation and acting professor for Real-Time Systems at TU Munich. He earned his Dipl.-Ing. (2003), Dr.-Ing. (2009), and Habilitation (2019) from TU Munich. His research focuses on Electronic System Level Design, RISC-V domain-specific architectures, embedded ML compiler toolchains, functional safety, and hardware security. He collaborates extensively with industry partners like Infineon, Bosch, BMW, and Mercedes. Active in the RISC-V community, he co-initiated the RISC-V Summit Europe and serves on steering committees for conferences such as DAC, ICCAD, and DATE. Key Research Themes: RISC-V ISA extensions and toolchain development Edge AI/ML on embedded systems Secure and safety-critical processor design High-level synthesis and performance simulation Awards: Best Student Paper Award (2024), IEEE Winter Conference on Computer Vision Habilitationspreis (2019), TU Munich Alumni Association Senior IEEE Member (2019) Teaching includes courses like 'High-Level Synthesis', 'Computer Organization', and 'Embedded Systems Design'. Current projects involve lightweight software for IoT devices and pre-silicon validation of safety-critical RISC-V systems. His work bridges academic research with industrial application through collaborative projects and open-source tool development.

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 Vision
• Image Analysis
• Machine Learning
• +۵ مورد دیگر

Martin Kampel is a Senior Scientist at the Computer Vision department of Technische Universität Wien (E193-01), focusing on interdisciplinary research at the intersection of Visual Computing , Human-Centered Technology , and AI Ethics . His work spans 3D Vision , Image Sequence Analysis , Computer Vision for Cultural Heritage , Ambient Assisted Living , and Visual Surveillance . Current roles: Senior Scientist, Principal Investigator in EU and national projects (e.g., Blindsight, visuAAL, KIIS) Contact: martin.kampel@tuwien.ac.at Research Interests Kampel’s research explores: 3D Acquisition & Reconstruction : Camera calibration, hand-eye tracking, and range data processing. Human Behavior Analysis : Motion tracking, multi-camera networks, and action recognition from 4D point clouds. Assistive Technologies : Depth sensor applications for dementia care, privacy-aware AAL systems, and smart toilet configurations. AI Ethics : Fairness, bias, and transparency in criminal justice systems and algorithmic governance of care. Recent Projects & Publications His work includes: Blindsight : WiFi-based person localization and multimodal data synthesis for behavioral classification. visuAAL : Developing trustworthy AI for dementia care and privacy-preserving depth sensor systems. KIIS : Domain-adaptive data synthesis for supermarket product recognition. Notable publications cover 3D human pose estimation , WiFi CSI analysis , trimodal datasets , and ethical AI frameworks .

Philip Chenمشاهده پروفایل

استاد

• Multimedia Security
• Machine Learning
• Decision Sciences
• +۴ مورد دیگر

Philip Chen is a Chair Professor and former Dean (2009–2017) of the Faculty of Science and Technology at the University of Macau, China. He has held significant roles such as Editor-in-Chief of IEEE Transactions on Systems, Man, and Cybernetics: Systems (2014–present), President of the IEEE Systems, Man, and Cybernetics Society (2012–2013), and Vice President of the Chinese Association of Automation (2017–present). His career spans institutions in the U.S. and China, including leadership positions at the University of Texas, San Antonio, and Wright State University. Chair Professor, University of Macau (2009–present) Dean, Faculty of Science and Technology, University of Macau (2009–2017) Editor-in-Chief, IEEE Transactions on Systems, Man, and Cybernetics: Systems (2014–present) His research focuses on Systems and Cybernetics , Computational Intelligence , Machine Learning , and Data Science , with applications in signal processing, decision systems, and hybrid intelligence. He has contributed to over 420 publications, including 240 SCI journal papers and 120 in IEEE Transactions, alongside three U.S. patents and a book. Dr. Chen has received prestigious accolades such as the 2018 IAPR Fellow , 2009 AAAS Fellow , and 2007 IEEE Fellow . He earned the 2017 Natural Science Research Award (2nd place) in Liaoning Province and the 2016 Purdue University Outstanding Electrical and Computer Engineering Award. His 32 top 1% Highly Cited Papers (Web of Science) and recognition as one of the top 14 most cited authors in computer science (2018) highlight his global impact. As an educator, he spearheaded the accreditation of the University of Macau’s engineering and computer science programs under the Washington Accord and Seoul Accord , elevating their global rankings to top 200 (Times Higher Education) and top 161 (U.S. News and World Report). His service includes leadership in IFAC’s Technical Committee 9.1 (Economic, Business, and Financial Systems, 2015–2017).

Georgios P. Georgiouمشاهده پروفایل

استادیار

• Experimental Phonetics
• Speech Acquisition
• Language Acquisition
• +۴ مورد دیگر

Dr. Georgios (George) P. Georgiou is an Assistant Professor of Linguistics at the University of Nicosia , where he serves as Associate Head of the Department of Languages and Literature and Director of the Phonetic Lab . He was awarded the Cyprus Research Award – Young Researcher 2023 in Social Sciences and Humanities and elected a Fellow of the Young Academy of Europe (2024) . B.A. in Greek Philology (University of Cyprus, 2007–2011) M.A. in Education with distinction (University of Cyprus, 2011–2013) Ph.D. in Linguistics with distinction (University of Cyprus, 2014–2018) His research integrates experimental phonetics , language acquisition , communication disorders , and machine learning . He developed the Universal Perceptual Model (UPM) for speech perception and focuses on diagnosing neurological/communication disorders via speech elements. His recent work applies AI to classify speech patterns and identify language disorders. Article trends highlight crosslinguistic vowel classification , acoustic markers in speech disorders , and machine learning for diagnostic tools , with collaborations across Europe. He has secured grants exceeding €60,000, including projects on Developmental Language Disorder and Neurological Speech Diagnosis . Scientific accolades include: Cyprus Research Award – Young Researcher 2023 Fellow, Young Academy of Europe (2024) Seal of Excellence, Marie Skłodowska-Curie Action (2021) Georgiou has received research grants as Principal Investigator, including postdoctoral fellowships at RUDN University and Cyprus University of Technology, and a €60,000 grant from the Cyprus Research and Innovation Foundation (2024–2026). He mentors through PhD Research Methodology courses and leads the Phonetic Lab , a hub for computational linguistics and disorder diagnosis.

• Privacy in Smart Grids
• Machine Learning
• Differential Privacy
• +۶ مورد دیگر

Günther Eibl is a Senior Lecturer and Senior Researcher at the Salzburg University of Applied Sciences , affiliated with the Department Information Technologies and Digitalisation . He serves as Head of Research Group and Deputy Head of the Center for Secure Energy Informatics , combining 50% teaching and 50% research responsibilities. Education: MSc in Mathematics (Numerics Thesis) MSc in Physics (Plasma Physics Simulation Thesis) PhD in Machine Learning (Multiclass Boosting Thesis) Research Interests focus on Privacy in Smart Grids , including: Privacy Analyses – Using machine learning and statistics to extract information from load profiles. Privacy-Enhancing Technologies (PETs) – Historically focused on homomorphic encryption, masking, differential privacy, and wavelet analysis; current research emphasizes privacy-preserving price calculation and proving privacy properties of protocols. Scientific Contributions span 15+ years, with recent work (2025–2021) addressing: Privacy threat modeling for renewable energy communities Smart meter data anonymization Blockchain-based secure aggregation Game-theoretic privacy proofs Differential privacy in load forecasting Intrusion detection in power grids Skills include cryptography, data mining, and energy informatics, with a strong emphasis on visualization and applied statistics . He teaches applied mathematics , applied statistics , and data mining in bachelor and master programs.

Adithya Vadapalliمشاهده پروفایل

استادیار

• Cryptography
• Secure Multi-Party Computation
• Oblivious RAM
• +۳ مورد دیگر

Adithya Vadapalli is an Assistant Professor at the Department of Computer Science and Engineering (IIT Kanpur, India). His research focuses on constructing systems that prevent data leaks through cryptographic methods, with broader applications in secure computation and privacy preservation. Education: Ph.D. in Computer Science from Indiana University Bloomington. Prior Role: Postdoctoral Fellow at the University of Waterloo (CrySP group). His research interests include: Secure Multi-Party Computation (SMPC) Oblivious RAM (ORAM) design Metadata protection techniques Privacy-preserving machine learning Recent publications highlight advancements in cryptographic primitives like distributed point functions, bandwidth-efficient distributed ORAM, and round-efficient 3-party MPC for dynamic data structures. These works span theoretical foundations and practical implementations. Currently, no scientific awards or student records are explicitly listed in the provided materials.

Munindar Singhمشاهده پروفایل

استاد

• Artificial Intelligence
• Service-oriented computing
• Sociotechnical systems
• +۶ مورد دیگر

Munindar Singh is an Alumni Distinguished Graduate Professor in the Department of Computer Science at North Carolina State University , where he also serves as Co-Director of the DoD-sponsored Science of Security Lablet . His research spans Artificial Intelligence , Multiagent Systems , and Service-Oriented Computing , with applications in Cybersecurity , Privacy , and Social Computing . His research interests focus on ethical and sociotechnical dimensions of AI, including moral reasoning in social contexts , resilient multiagent systems , and responsible computing for sustainability . His work integrates formal methods with machine learning to address challenges in decentralized systems , agent communication , and cyber deception . Recent publications highlight trends in AI ethics , cybersecurity , and social simulation , with subfields like moral judgment analysis , domain adaptation , and metaverse services . These works often bridge technical and societal concerns, emphasizing trustworthy AI and ethical governance . Fellow, American Association for the Advancement of Science (AAAS) (2020) ACM/SIGAI Autonomous Agents Research Award (2020) IBM Shared University Research Award (2018) NCSU Research Leadership Academy Membership (2017) IFAAMAS Influential Paper Award (2016) National Science Foundation CAREER Award (1996) Munindar has held leadership roles, including editor-in-chief of ACM Transactions on Internet Technology and IEEE Internet Computing . His research is funded by sponsors such as DARPA , NSF , and IBM . He co-directs the Science of Security Lablet , a DoD-funded initiative advancing cybersecurity research.