جست‌وجوی استاد و پژوهشگر

• Blockchain Technology
• Cybersecurity
• Cloud Computing
• +۳ مورد دیگر

Wei-Tek Tsai is a Professor affiliated with Arizona State University's School of Computing, Informatics, and Decision Systems Engineering, and previously with Beihang University and the University of Minnesota. His research focuses on blockchain technology, cybersecurity, cloud computing, and software engineering. He has contributed significantly to areas such as blockchain-based systems, smart contract development, distributed testing methodologies, and crowdsourcing in software development. His work emphasizes practical applications like fraud detection, supply chain supervision, and decentralized financial systems. Research interests include permissioned blockchains, anomaly detection in cryptocurrency transactions, and optimizing consensus mechanisms. He has published extensively in top-tier journals and conferences, including IEEE Transactions and international workshops on software engineering and security. His work bridges theoretical advancements with real-world challenges in distributed systems and cybersecurity.

• Multi-agent systems
• Reinforcement learning
• Trust management
• +۵ مورد دیگر

Athirai Aravazhi Irissappane is an Assistant Professor at Nanyang Technological University's College of Computing and Data Science, School of Computer Science and Engineering. With a PhD in Trust oriented decision making via POMDPs completed in 2016, they have established themselves as a prominent researcher in multi-agent systems and reinforcement learning. Their academic journey shows a clear progression from foundational work in trust management to cutting-edge research in deep reinforcement learning frameworks. Dr. Irissappane's research interests focus on multi-agent systems , reinforcement learning , trust management , and recommender systems . They have made significant contributions to the field of multi-objective reinforcement learning, developing frameworks that address complex policy distributions and cooperative behavior in multi-agent environments. Their work bridges theoretical advances with practical applications, particularly evident in their contributions to the RecSys Challenge 2023. Analysis of their recent publications (2020-2024) reveals a strong emphasis on Advanced reinforcement learning architectures for multi-agent cooperation Privacy-preserving recommendation systems Automated data quality improvement for recommendation tasks Scalable frameworks for reinforcement learning research These works demonstrate increasing sophistication in handling complex decision-making scenarios while addressing practical constraints like computational efficiency and privacy concerns. Dr. Irissappane has been actively involved in major academic initiatives including the RecSys Challenge 2023 and has contributed to comprehensive guides on multi-objective reinforcement learning that have become valuable resources for the research community. Their collaborative work spans multiple institutions and has resulted in publications in top-tier venues including IEEE Transactions, Autonomous Agents and Multi-Agent Systems journal, and conference proceedings of AAAI, IJCAI, and AAMAS.

• Quantum Computing
• High-Performance Computing (HPC)
• Optimization Algorithms
• +۳ مورد دیگر

Katarzyna Rycerz is an academic researcher specializing in quantum computing, high-performance computing (HPC), and optimization algorithms. Her work spans hybrid quantum-classical systems, complex network analysis, and multiscale simulations. Collaborating with institutions such as AGH University of Science and Technology (inferred via co-authors like Marian Bubak), her research focuses on advancing quantum algorithms for optimization problems, quantum annealing applications, and software frameworks for distributed computing environments. Her notable contributions include developing libraries like QHyper for hybrid quantum-classical optimization, analyzing quantum walk-based image segmentation, and exploring the application of quantum computing to classical problems like the Traveling Salesman Problem. She has also contributed to foundational studies in quantum game theory and functional programming paradigms in HPC. Rycerz's publications reflect a sustained focus on interdisciplinary research, bridging quantum mechanics, computer science, and applied mathematics. Her work often addresses practical challenges in computational efficiency, algorithm design, and scalable simulation frameworks for complex systems.

Michael Kochمشاهده پروفایل

استاد

• Human-Computer Interaction (HCI)
• Computer-Supported Cooperative Work (CSCW)
• Collaboration Technology
• +۳ مورد دیگر

Michael Koch is a Professor of Human-Computer Interaction (HCI) at the University of Bundeswehr Munich in Germany. He holds a doctorate (PhD) and Habilitation in Informatics from TU München. His research focuses on collaboration technologies, socio-technical systems design, and integrating user interface innovations for team and community support. He leads the Cooperation Systems Center Munich (CSCM) and chairs the HCI Special Interest Group in the German Computing Society (GI). He has held industry roles at Xerox Research Centre Europe and academic positions at TU München, University of Dortmund, and University of Bremen. Education: PhD in Informatics, TU München (1997) Habilitation in Informatics, TU München (2003) Research Interests: Designing usable systems for work and leisure contexts Computer-Supported Cooperative Work (CSCW) Socio-technical system integration for team collaboration Human-Computer Interaction innovations Professional Roles: Fellow of the German Computing Society (GI) Member of ACM SIGCHI Chapter and EUSSET boards Editorial roles in i-com Journal and Lecture Notes in Informatics Advising & Collaboration: Guided over 10 PhD/Master’s students Active in European cyber defense research through Forschungszentrum Cyper Operations His research bridges technical innovations with human-centric design principles, emphasizing real-world applicability in enterprise and community settings.

• Bioinformatics
• Artificial Intelligence
• Computer Science
• +۳ مورد دیگر

Jie Hao is a researcher at the Information Security Center of Beijing University of Posts and Telecommunications , with a focus on interdisciplinary applications spanning Bioinformatics , Artificial Intelligence , and Medical Informatics . His work bridges computational methods with real-world challenges in healthcare, ecology, and network optimization. Recent publications highlight his contributions to Single-cell RNA sequencing deconvolution (2025) AI-driven intergenerational communication in VR (2025) Digital health applications for COPD management (2025) Deep reinforcement learning for vehicle routing (2025) His methodological innovations include adaptive attention mechanisms for object detection (2025), memory-efficient DNN accelerators (2025), and bilevel optimization algorithms with unbounded smoothness (2024). Collaborations span institutions like University of Melbourne and Chinese Academy of Sciences , reflecting his cross-disciplinary impact.

• Bioinformatics
• Computational Biology
• Machine Learning
• +۴ مورد دیگر

Yue Joseph Wang is a Professor at Virginia Tech's Department of Electrical and Computer Engineering , with a focus on bioinformatics, computational biology, and medical imaging. His work bridges machine learning with biomedical applications, particularly in cancer research, neuroimaging, and metabolomics. Research areas include: Unsupervised deconvolution of mixed gene expressions Development of radiogenomic frameworks 3D neuronal and cellular image analysis Optimization of biomarker discovery Computational tools for LC-MS and DCE-MRI data Recent publications demonstrate his expertise in: Multi-omics data integration Algorithm design for medical image segmentation Machine learning in biomedical signal processing Network-constrained statistical models Time-warping techniques for metabolomic analysis Pharmacokinetic modeling in cancer studies Collaborations span institutions like University of North Carolina, National University of Singapore, and Georgetown University Medical Center. His work often involves R-package development (e.g., debCAM) and high-impact contributions to journals such as Bioinformatics, IEEE Transactions, and Nature Machine Intelligence.

• Internet of Things
• Software Engineering
• Machine Learning
• +۵ مورد دیگر

Jorge Eduardo Ibarra Esquer is an Associate Professor in the Department of Computer Science at the School of Engineering, Universidad de Sonora, Mexico. With a publication record spanning nearly two decades from 2006 to 2023, he has established himself as an active researcher in multiple domains of computer science. His work demonstrates consistent collaboration with colleagues Brenda Leticia Flores Ríos, María Angélica Astorga Vargas, and Félix Fernando González-Navarro across numerous publications. His research interests focus on the Internet of Things , Software Engineering , Machine Learning , and Educational Technology . Recent work has explored IoT object categorization, user engagement analysis on social media for scientific dissemination, and software development education during the pandemic. Earlier research examined biosensor modeling, game playing preferences, and driving safety through gamification. His publications appear in reputable venues including IEEE Access, Sensors, and the Colombian Journal of Computing, as well as at national conferences like ENC (Encuentro Nacional de Computación). Analysis of his recent publications (2020-2023) reveals a strategic focus on applying machine learning to practical problems in IoT, educational technology, and social media analytics. His work bridges theoretical computer science with real-world applications, particularly in the Mexican higher education context as evidenced by studies on Facebook engagement at a higher education institution. The interdisciplinary nature of his research spans from healthcare applications (biosensors, physiological monitoring) to educational technology and software engineering practices. While no specific scientific awards are documented in the available publication records, his consistent publication output across multiple high-quality venues demonstrates recognition within his academic community. His research has practical implications for software development education, IoT applications, and human-computer interaction design. Dr. Ibarra Esquer's work shows strong collaborative patterns, particularly with researchers from his home institution. His recent publications suggest active involvement in research teams focusing on educational technology applications during the pandemic, social media analytics for scientific communication, and IoT applications. The continuity of his research program since 2006 indicates sustained scholarly productivity and relevance in evolving technological domains.

• Networking
• Edge Computing
• 5G/6G Technologies
• +۵ مورد دیگر

Dr. Giang T. Nguyen is an academic researcher affiliated with Dresden University of Technology (Germany), specializing in advanced networking technologies. His primary affiliation is with the College of Computer Science and the Department of Networking and Communication Systems. He collaborates extensively with Prof. Frank H. P. Fitzek and other researchers on cutting-edge projects. Research Interests: Giang's work focuses on Network Functions Virtualization (NFV) , Edge Computing , Time-Sensitive Networking (TSN) , 5G/6G Technologies , and In-Network Computing (COIN) . He explores applications in industrial automation, tactile internet, and immersive media delivery, with a strong emphasis on latency reduction and network reliability. Publications: His recent work includes advancements in programmable network coding, TSN testbed development, and latency-optimized architectures for XR and IoT systems. Over 100+ publications since 2013 reflect his contributions to edge computing frameworks, network simulation tools (e.g., ns-3, OMNeT++), and collaborative SLAM systems. Key Projects: He leads initiatives like the TSN-FlexTest measurement testbed and the NET Playground heterogeneous network lab. His research bridges theoretical networking concepts with practical implementations in industrial robotics and emergency response systems.

• Cybersecurity
• Machine Learning
• Network Security
• +۳ مورد دیگر

Shawkat K. Guirguis is an academic researcher with a focus on cybersecurity, machine learning, and IoT technologies. His work spans across intrusion detection systems, botnet prevention, and adaptive algorithms for network security. He has contributed to advancements in deep learning applications for social media analysis and real-time trajectory compression. His research often intersects with practical implementations in smart cities and healthcare authentication systems. Key areas of exploration include the use of boosting algorithms, tree-based models, and blockchain integration to enhance IoT security. His publications highlight contributions to wireless sensor networks and stock prediction models. Despite extensive research output, affiliations such as university or department remain unspecified in available records.

• Digital Twin Technologies
• Internet of Things (IoT)
• Edge Computing
• +۵ مورد دیگر

Roberto Minerva is a researcher at Sorbonne University , Paris, France, focusing on Digital Twin Technologies , Internet of Things (IoT) , and Edge Computing . His work addresses Smart Cities , Urban Data Management , and Machine Learning Applications through advanced architectural frameworks. His recent publications highlight innovations in: Digital twin architectures for real-time urban air quality and traffic management AI-driven and scalable frameworks for large-scale sensor networks Blockchain applications in secure supply chain finance Minerva frequently collaborates with researchers like Noël Crespi , Manoj Herath , and Maira Alvi , contributing to journals such as IEEE Internet Comput. , IT Prof. , and conferences like NetSoft and CNSM . His work bridges theoretical research and practical implementations in smart city ecosystems.

• Augmented Reality
• Virtual Reality
• Computer Graphics
• +۳ مورد دیگر

J. Edward Swan II is a Professor in the Department of Computer Science and Engineering at Mississippi State University. His research focuses on Augmented Reality (AR), Virtual Reality (VR), and Human-Computer Interaction (HCI), with an emphasis on perceptual aspects of AR/VR systems, calibration techniques, and user experience optimization. He has contributed extensively to advancing AR/VR technologies through studies on depth perception, text legibility, and system accuracy. Key roles: IEEE VR Steering Committee member, conference program chair, and guest editor for top journals. Research areas include optical see-through AR systems, user performance evaluation, and spatial perception in virtual environments. His work spans over 120 publications since 1995, with recent contributions addressing font optimization for AR displays, eye-tracking-based depth measurement, and X-ray vision systems for situational awareness. Notable recognition includes the VGTC Virtual Reality Service Award (2023).

Andrey Sobolevمشاهده پروفایل

پژوهشگر

• Neuroscience
• Electrophysiology
• Data Management
• +۳ مورد دیگر

Dr. Andrey Sobolev is a PostDoc researcher at the Faculty of Biology, Ludwig Maximilian University of Munich, affiliated with the Benedikt Grothe Research Group. His work focuses on neurophysiological data management, electrophysiological data handling, and neural systems analysis. Key contributions include developing the Neo Python library for electrophysiology data handling and the G-Node Python Client for reproducible research workflows. Research interests span computational neuroscience, data management systems, and behavioral paradigms in freely moving animals. Notable publications include studies on hippocampal ensemble remapping under sensory conflicts (2021), the Sensory Island Task behavioral paradigm (2020), and metadata standards in neurophysiology (2016). Technical contributions include creating integrated platforms for electrophysiological data storage (2014) and foundational database systems for biomedical applications (2011). Collaborates widely with neuroscientists and software engineers to advance open science practices in neuroscience research.

Hariprasath Ganesanمشاهده پروفایل

پژوهشگر

• Atomistic Simulations
• Nanomechanics
• Materials Informatics
• +۳ مورد دیگر

Dr. Hariprasath Ganesan is a Senior Scientist at the Research Center Jülich, affiliated with the Institute for Advanced Simulation (IAS) and the Materials Data Science and Informatics (IAS-9) department. His expertise spans Atomistic Simulations, Nanomechanics, and Materials Informatics, focusing on computational modeling of materials' behavior under extreme conditions. He leads research into high-temperature deformation mechanisms in advanced alloys like TiAl, leveraging multiscale simulation techniques such as molecular dynamics and Monte Carlo methods. His work emphasizes GPU-accelerated computational approaches for atomistic simulations, improving efficiency in studying solute segregation, interface dynamics, and thermal-mechanical properties. Recent studies include ultrafast laser-material interactions and creep behavior in nanomaterials. Collaborations bridge theoretical models with practical applications in materials design and additive manufacturing. Publications highlight contributions to understanding lamellar interface stability, Cottrell atmosphere formation, and parallel computing frameworks for scale-bridging simulations. His research aligns with Helmholtz energy and materials science initiatives, advancing computational tools for next-generation materials discovery.

Thomas Wickمشاهده پروفایل

استاد

• Numerical Analysis
• Computational Mechanics
• Partial Differential Equations
• +۳ مورد دیگر

Prof. Dr. Thomas Wick is a Professor at the Institute of Applied Mathematics within the Faculty of Mathematics and Physics at Leibniz University Hannover. He holds leadership roles, including Executive Director of the Institute and membership in the Executive Board and Faculty Council. His research focuses on numerical methods for coupled nonlinear partial differential equations, multiphysics systems (e.g., fluid-structure interaction, phase-field fracture), adaptive finite element techniques, and robust solvers. Key projects include the DFG-funded SPP 1962 and SPP 1748 initiatives, the PhoenixD Cluster of Excellence, and international collaborations like the Indo-German Higher Education Partnership. He has received grants from DFG, DAAD, and the Alexander von Humboldt Foundation. His work emphasizes algorithm design, error control, and computational efficiency in engineering and scientific applications. Research Interests: Numerical modeling of coupled PDE systems, multiphysics phenomena, phase-field fracture, adaptivity, and optimization. Projects include CoMeTeNd (IRTG 2657/1), PhoenixD Task Group S4, and Strukturerhaltende Adaptive Enriched Galerkin Methods. Scientific Awards: Feodor Lynen Fellowship, DFG Projects, DAAD grants. Collaborations span Germany, Austria, India, Peru, and France. Publications highlight advancements in phase-field fracture, fluid-structure interaction, and adaptive methods. His contributions address challenges in mesh adaptivity, error estimation, and high-performance computing.

• Anesthesiology
• Hemodynamic Monitoring
• Perioperative Care
• +۵ مورد دیگر

Karim Kouz is a medical researcher specializing in anesthesiology at the University Medical Center Hamburg-Eppendorf, where he works in the Department of Anesthesiology. With an extensive publication record spanning from 2016 to 2025, Dr. Kouz has established himself as a significant contributor to perioperative medicine research, particularly in hemodynamic monitoring and blood pressure management during surgery. His research interests center on intraoperative hypotension, hemodynamic monitoring technologies, personalized blood pressure management during surgery, and the relationship between hemodynamic parameters and postoperative outcomes. Dr. Kouz has been involved in numerous clinical trials, method comparison studies, and guideline development projects, often collaborating with Professor Bernd Saugel and other prominent researchers in the field. His work bridges clinical practice with technological innovation, examining both traditional monitoring methods and emerging technologies like smartphone-based blood pressure measurement and processed electroencephalography. Dr. Kouz's publication portfolio demonstrates a consistent focus on improving perioperative care through evidence-based approaches. His recent work includes contributions to German clinical guidelines for hemodynamic monitoring during non-cardiac surgery and participation in multicenter trials examining the relationship between blood pressure management and postoperative complications. His research has appeared in leading anesthesiology journals including British Journal of Anaesthesia, Journal of Clinical Monitoring and Computing, and Anesthesiology. As an active researcher in the European anesthesiology community, Dr. Kouz has contributed to the EU-HYPROTECT registry and other collaborative projects examining hypotension prediction and management during surgery. His work represents an important contribution to the evolving understanding of optimal hemodynamic management in the perioperative period.