جست‌وجوی استاد و پژوهشگر

Chris Fietkiewiczمشاهده پروفایل

دانشیار

• Computational Neuroscience
• High Performance Computing
• Neural Simulation
• +۷ مورد دیگر

Chris Fietkiewicz is an Associate Professor in the Department of Mathematics & Computer Science at Hobart and William Smith Colleges. He joined the faculty in 2019 and is based in Lansing Hall, with research interests in computational neuroscience and high-performance computing. Research Interests: His work focuses on Computational Neuroscience , particularly the development of neural simulators for educational and clinical applications. He leads the Applied Neural Control Toolkit (ANC Toolkit) , which enables simulation of neural and axonal responses for neuroprosthetic development. His research also spans High Performance Computing , including software optimization, parallel computing, and cluster management tools. Collaborations: He collaborates with Dr. Thomas Mortimer (Case Western Reserve University) on neural stimulation and with Dr. Chen Liu (Tianjin University) on Parkinson’s disease modeling and deep brain stimulation. His publications reflect a strong interdisciplinary focus on biomedical signal processing, control systems, and neuromorphic computing. Publication Trends: His recent work (2016–2022) centers on closed-loop control of pathological neural oscillations, computational models of Parkinson’s disease, and real-time neural simulation. These studies appear in top journals like IEEE Transactions and Biomedical Signal Processing and Control , emphasizing algorithmic innovation and clinical relevance. Scientific Contributions: Co-developer of the ANC Toolkit for neuroscience education. Researcher in neural control systems and HPC optimization. Active contributor to computational models of movement disorders. Advising and Grants: While no formal students are listed, his collaborative projects suggest mentorship of undergraduate and graduate researchers. Grant details are not provided, but his research cluster and web tools indicate funded infrastructure development. Labs and Teams: He is building a research computing cluster and developing web-based batch programming tools, indicating a focus on scalable, accessible computational neuroscience platforms.

• Distributed Computing
• High-Performance Computing
• Distributed Shared Memory
• +۷ مورد دیگر

Tore Brox-Larsen is an Associate Professor in the Department of Informatics at UiT The Arctic University of Norway. His work centers on distributed computing, high-performance systems, and large-scale visualization technologies. He is actively engaged in research involving sensor networks, Arctic observatories, and remote visualization of scientific data. His research interests span distributed shared memory systems, MPI performance, tiled display walls, and networked visualization. He has made significant contributions to improving communication efficiency in cluster computing and enabling scalable interactive visualization environments. His work bridges computer systems engineering with applications in genomics and environmental monitoring. The most recent publications reflect a strong trend toward real-world deployment of large-scale systems, particularly in Arctic observation and healthcare informatics. His work emphasizes practical system design, latency optimization, and cross-platform interoperability in distributed environments. Tore Brox-Larsen has collaborated extensively with researchers such as Otto Anshus, John Markus Bjørndalen, and Brian Vinter. While no formal advising or grant history is listed, his sustained publication record indicates active research leadership and team-based scientific inquiry. He has contributed to major projects including the development of a large-scale Arctic observatory sensor system and interactive tiled display walls. His work supports both academic research and societal applications in health and environmental science.

• Geographic Information Systems
• 3D Visualization
• Terrain Rendering
• +۵ مورد دیگر

Дејан Д. Ранчић је редовни професор на Електронском факултету у Нишу (Универзитет у Нишу), где је изабран 2015. године након дугогодишњег рада као доцент од 2005. године. Дипломирао, магистрирао и докторирао је на истом факултету у области Електротехника и рачунарство. Његово образовање укључује: Дипломирани инжењер електротехнике и рачунарства (1993) Магистар електротехнике и рачунарства (1997) Доктор електротехнике и рачунарства (2004) Ранчићев истраживачки фокус је на ГИС технологијама , 3D визуелизацији терена и обраги радарских сигнала . Кључни доприноси укључују развој алгоритама за мобилне ГИС апликације, паралелно рендеровање великих терена и радарску обраду података за сузбијање града. Његов рад комбинује теоријску рачунарску геометрију са практичним инжењерским решењима. Анализа његових радова показује еволуцију од радарских система (1997-1999) ка иновативним ГИС решењима (2000-2006), са посебним нагласком на визуелизацију терена и мобилне платформе. Најзначајнији радови објављени су у часописима као што су Computer and Geosciences и WSEAS Transactions on Computers . Тренутно учествује у 3 национална и 1 интернационални истраживачки пројекат, а као рецензент ради за WSEAS серију часописа. Иако детаљи о менторству нису наведени, његова публикацијска активност и пројекти указују на значајну улогу у развоју геопросторних технологија у Србији.

• Sexology
• Gender Studies
• Behavioral Sciences
• +۳ مورد دیگر

Christian Graugaard is a Professor of Sexology at Aalborg University, affiliated with the Faculty of Medicine and the Department of Clinical Medicine. He is a key member of the Center for Sexology Research and leads Project SEXUS, aiming to study Danish sexual behavior comprehensively. His work emphasizes the intersection of biological, psychological, and cultural factors in human sexuality, challenging simplistic gender-based stereotypes. Research interests include gender differences in sexual behavior, societal norms influencing sexual health, and the cultural dimensions of human sexuality. He actively participates in public discourse, as seen in his DR-podcast interview on 'Ramt af kærlighed,' where he discussed the complex interplay between biology and culture in shaping sexual identities. Though no specific awards or grants are detailed here, his publications span advanced technical domains like spatiotemporal data analysis, federated learning, and trajectory modeling, suggesting interdisciplinary research collaborations. His work on systems like OneDB and SWASH highlights contributions to distributed computing and data science, which may underpin his methodologies in large-scale sexual behavior studies. He currently holds no listed students or formal advisees in the provided texts, and his involvement in labs/teams is limited to the Center for Sexology Research and Project SEXUS.

Daniel Cornelمشاهده پروفایل

پژوهشگر

• Flood Modeling
• Hydrology
• Computational Fluid Dynamics
• +۳ مورد دیگر

Daniel Cornel is a researcher affiliated with TU Wien's Department of Engineering Hydrology, part of the E222-02 research group. He holds a Dipl.-Ing. (engineering diploma) and a Dr.techn. (technical doctorate). His work focuses on integrating computational methods with environmental hydrology, emphasizing flood modeling, high-performance computing, and geospatial visualization. Cornel collaborates extensively with experts like Prof. Günter Blöschl and Prof. Jürgen Waser on projects such as the HORA 3.0 flood risk zoning initiative. His research interests span GPU-accelerated flood simulations, hydrodynamic modeling at regional scales, and decision-support systems for disaster management. Notable contributions include developing interactive visualization tools for real-time flood data and VR-based training modules for emergency response. Cornel also explores algorithm optimization for terrain modeling and subsurface network visualization. Key projects include the 'Integrated Simulation and Visualization for Flood Management' framework and the 'Master of Disaster' VR training system. His work bridges computational science with environmental engineering, addressing both technical challenges and practical applications in flood risk mitigation.

Julien Tiernyمشاهده پروفایل

استاد

• Topological Data Analysis
• Scientific Visualization
• Data Compression
• +۲ مورد دیگر

Julien Tierny is a Professor at Ecole Polytechnique and a Senior Researcher (DR2) at CNRS within the Computer Science Department (LIP6) at Sorbonne Université, part of the APR team. His research focuses on Topological Data Analysis and Visualization, with a particular emphasis on developing efficient algorithms for scientific data processing and visualization. He leads the ERC-funded project TORI, which aims to reduce scientific data through in-situ topological methods. Education & Affiliations: PhD in Computer Science (2008), Université de Lille Habilitation Thesis (HDR, 2016), Sorbonne Université Principal Investigator of ERC Project TORI Research Interests: Topological Data Analysis, Scientific Visualization, High-Performance Computing, and Algorithm Design. His work bridges theoretical foundations with practical tools like the Topology ToolKit (TTK), widely used in visualization and data science. Awards & Recognition: ERC Starting Grant (2020) Best Paper Honorable Mention (IEEE VIS 2019) Best Paper Award (IEEE LDAV 2018) Teaching: Leads courses on Scientific Visualization, Topological Data Analysis, and Computer Graphics at Ecole Polytechnique and Sorbonne Université. Popular courses include 'Introduction to Topological Data Analysis' and 'Advanced Visualization Techniques'. Labs & Contributions: Co-developer of the Topology ToolKit (TTK), a widely adopted open-source library for topological data analysis. Active in IEEE Visualization conferences, publishing award-winning papers on distributed computing and topological simplification.

• Performance Measurement
• Operating Systems
• Virtualization
• +۳ مورد دیگر

Manuel Alejandro Pajuelo González is a researcher at the Universitat Politècnica de Catalunya (UPC), affiliated with the Department of Computer Architecture and the School of Computer Science. His research focuses on Performance measurement Operating systems Virtualization Thread assignment in multithreaded processors Recent publications show strong trends in RISC-V architectures, cybersecurity, and performance optimization. Key themes include Hardware virtualization Intrusion detection frameworks Statistical thread assignment approaches Spin-lock overhead analysis Scientific awards include BDigital Global Congress 15ª Edició Computación de Altas Prestaciones VI HiPEAC Paper Award He participated in multiple competitive R&D projects, including the DRAC project focused on RISC-V accelerators for next-generation computing.

Yue Zhangمشاهده پروفایل

دانشیار

• Scientific Visualization
• Computer Graphics
• Mathematical Modeling
• +۴ مورد دیگر

Dr. Yue Zhang is an Associate Professor in the School of Electrical Engineering and Computer Science at Oregon State University. She holds appointments in both academic research and teaching roles, with a focus on computer graphics and data visualization. Her work bridges theoretical mathematics and practical applications in material science and ecological modeling. Ph.D. in Applied Mathematics, North Carolina State University B.S. in Mathematics and Physics, University of Tennessee at Knoxville Research interests span scientific visualization , tensor field analysis , and topology-driven modeling of physical and biological systems. She has pioneered techniques for hypergraph simplification, non-Euclidean geometry visualization, and coupled acoustic-structural simulations. Recent publications demonstrate trends in hypergraph visualization (2024), 3D tensor topology (2024-2022), and environmental stressor modeling (2022). Collaborative works with Eugene Zhang and Peter Oliver dominate her publication record. Students under her advisement include: PhD candidates: Shih-Hsuan Kevin Hung MS/MEng students: Kyle Hiebel, Josiah Blaisdell, Avery Stauber Co-advised projects: Peter Oliver, Xiaofei Gao

Bartolomeo Montrucchioمشاهده پروفایل

استاد

• Computer Vision
• Quantum Computing
• Image Processing
• +۵ مورد دیگر

Bartolomeo Montrucchio is a Full Professor of Information Processing Systems (ING-INF/05) at the Department of Control and Computer Engineering (DAUIN) of the Polytechnic University of Turin. He is a member of the Interdepartmental Center Photonext - PoliTo Interdepartmental Center on Applied Photonics and serves as deputy director at the Interuniversity Center of Regional Interest for the Training of Secondary School Teachers (CIFIS) since July 2012. Additionally, he has held an adjunct professor position at the University of Illinois at Chicago during July 2008. Professor Montrucchio's research spans several cutting-edge areas with a primary focus on quantum computing, computer vision, and sensor networks. His work encompasses image processing, scientific visualization, parallel and distributed systems, and wireless sensor networks. He actively contributes to European research initiatives including the EQUO (European QUantum ecOsystems) project as Scientific Responsible. His research bridges theoretical computer science with practical applications across multiple industries. His publication record shows a strong trajectory toward quantum technologies, with numerous recent publications focusing on quantum machine learning, quantum algorithms for financial applications, and quantum applications in cybersecurity. His work demonstrates increasing emphasis on practical implementations of quantum computing in real-world scenarios, particularly in industrial settings and telecommunications. Best student paper award at BIOSIGNAL2002, conferred by EURASIP, Italy (2002) Associate Editor of IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY (2019-present) Professor Montrucchio actively supervises numerous PhD students working on quantum computing applications across various domains including finance, cybersecurity, traffic optimization, and industrial use cases. His teaching portfolio includes courses on Quantum Computing, Parallel and Distributed Computing, and Image Processing and Computer Vision across multiple degree programs including Computer Engineering, Biomedical Engineering, and Quantum Engineering. He leads multiple research projects funded by both competitive calls and commercial contracts, with a significant focus on quantum technologies since 2019. His patent portfolio includes several inventions related to tire manufacturing processes and visual rehabilitation for telemedicine.

José Carlos Cabaleiro Domínguezمشاهده پروفایل

استاد

• High performance computing
• Parallel systems architecture
• Parallel algorithms
• +۶ مورد دیگر

Dr. José Carlos Cabaleiro Domínguez is a Full Professor in the Department of Electronics and Computing at the University of Santiago de Compostela's Faculty of Computing, Spain. He has been a member of CiTIUS (Centro singular de investigación en tecnoloxías da información e comunicación) since 2010 and was promoted to Full Professor in 2022 after serving as an Associate Professor since 1994. His academic journey began with a BS and PhD in Physics from the University of Santiago de Compostela in 1989 and 1994 respectively, with initial teaching experience at the University of A Coruña from 1990-1994. His research focuses on high performance computing, particularly in parallel systems architecture, development of parallel algorithms for irregular problems with sparse matrices, performance prediction and improvement of parallel applications, memory hierarchy optimization, and applications for grid and cloud computing. He has developed significant expertise in 3D point cloud processing from remote sensors like LiDAR, with applications in urban infrastructure analysis, powerline detection, and route planning. Analysis of his recent publications reveals a strong emphasis on optimizing resource allocation for big data frameworks, developing deep learning applications for point cloud classification, and creating efficient algorithms for powerline detection in LiDAR surveys. His work bridges theoretical computer science with practical applications in geospatial analysis and infrastructure monitoring. His research has been published in top-tier journals including IEEE Transactions, ISPRS Journal of Photogrammetry and Remote Sensing, and Future Generation Computer Systems, reflecting his significant contributions to the field of high performance computing and its applications. Dr. Cabaleiro actively collaborates with researchers across multiple institutions, as evidenced by his extensive publication record with co-authors from various universities and research centers. His work demonstrates a consistent trajectory of advancing parallel computing techniques while applying them to increasingly complex real-world problems involving large-scale geospatial data.

Kayhan AYARمشاهده پروفایل

استادیار

• Virtual Reality
• Information Security and Cryptology
• 3D Computer Graphics
• +۳ مورد دیگر

Kayhan AYAR is an Assistant Professor at Sakarya University's Faculty of Computer and Information Sciences, Department of Computer Engineering. His expertise spans Virtual Reality, Information Security, Cryptology, and 3D Computer Graphics, with a focus on simulation-based educational technologies and haptic interaction systems. Doctorate: 2010–2020, Sakarya University (Thesis: 3D Image of MIG-MAG Welding Seam using Voxified Paraboloid) Master's: 2008–2010, Sakarya University (Thesis: DirectX-based 3D Game Engine Design) Bachelor's: 2000–2007, Sakarya University His research explores virtual welding simulators, voxelization techniques, and real-time haptic applications. Key publications include 15 recent articles (2010–2024) on topics like 3D modeling, neural networks in welding training, and VR-based security applications for energy infrastructure. He has contributed to international conferences and journals such as the Turkish Journal of Electrical Engineering and Computer Sciences and Journal of Materials Education . His work includes a 2014 patent for a virtual welding simulator and participation in TÜBİTAK-funded projects. Teaching responsibilities include courses in Game Programming, Data Structures, Computer Graphics, and Parallel/Distributed Systems, alongside advising graduation projects and specialization areas.

• Social Data Science
• Digital Humanities
• Quantitative and Computational Social Science
• +۴ مورد دیگر

Panagiotis Michailidis is a Professor at the Department of Balkan, Slavic and Oriental Studies, School of Economic and Regional Studies, University of Macedonia. His academic work focuses on Computational Methods and Informatics, integrating technological expertise with regional studies. BSc (1998) and PhD (2004) in Applied Informatics from University of Macedonia Academic career progression: Lecturer (2004-2013), Assistant Professor (2014-2019), Associate Professor (2019-2023), now Professor Research spans computational approaches to social science and humanities, with significant contributions to: Social Data Science Digital Humanities Quantitative Social Science Parallel/Distributed Computing String Matching Algorithms Scientific Computing Recent publications reveal interdisciplinary focus combining: Augmented Reality applications for cultural heritage Machine Learning for Greek language sentiment analysis High-performance computing implementations Metaheuristic optimization techniques Scientometric analyses of research fields Active in academic service through: IEEE memberships Conference program committee roles Guest editor for Algorithms special issue Research program participation Reviewing for multiple journals Teaching portfolio includes: DIGITAL SOCIAL RESEARCH METHODS INFORMATION, TECHNOLOGY AND SOCIETY QUANTITATIVE METHODS OF SOCIAL SCIENCES SPACE AND CULTURAL MANAGEMENT COMPUTER SCIENCE TOPICS

• Multidimensional Scaling
• Geometric Optimization
• Data Visualization
• +۳ مورد دیگر

Martynas Sabaliauskas is an Associate Professor and Researcher at the Cognitive Computing Group , Institute of Data Science and Digital Technologies , Vilnius University , Lithuania. His research focuses on multidimensional scaling, geometric optimization, data visualization, and prime number theory. His research interests include: Multidimensional Scaling (MDS): Developing geometric approaches for efficient data dimensionality reduction and visualization. Prime Number Theory: Investigating properties of the Riemann zeta function, prime sequences, and fractal structures. Computational Mathematics: Designing algorithms for complex mathematical problems with applications in data science. Recent publications reflect a strong focus on geometric MDS techniques, visualization of complex mathematical structures, and computational approaches to number theory. Notable works include studies on the Riemann zeta function's zeros, fractal visualizations, and efficient algorithms for large-scale data analysis. Contact Information: Address: Akademijos St. 4, room 617, Vilnius, Lithuania Phone: +370 5 210 9305

Lisovenko Iryna Dmytrivnaمشاهده پروفایل

استادیار

• Parallel and Distributed Computing
• GPU Computing
• Automatic Program Parallelization
• +۳ مورد دیگر

Lisovenko Iryna Dmytrivna serves as Assistant Professor in the Department of Computer Systems and Networks at Yuriy Fedkovych Chernivtsi National University since 2002, following her 2000 diploma in Computer Systems and Networks from the same institution. Her professional trajectory includes software engineering at a municipal medical institution (2000–2002) and ongoing contractual collaboration with Elogic Commerce since 2018. Her academic credentials include: Yuriy Fedkovych Chernivtsi State University, Faculty of Physics, Department of Computer Science, specialty "Computer Systems and Networks" (2000) Dr. Lisovenko's research centers on parallel and distributed computing, emphasizing automatic parallelization techniques, GPU-accelerated non-graphical computing, and structural analysis of program intermediate representations. She concurrently investigates specialized computer systems for data stream processing and develops methodologies for enterprise accounting automation, bridging theoretical computer science with business process optimization. Her scholarly output demonstrates sustained innovation in high-performance computing architectures. Analysis of her 15 most recent publications (2012–2021) reveals three dominant research thrusts: GPU-based parallelization (40% of works, including Kalyna encryption and bitonic sorting implementations), algorithmic optimization for diverse hardware (33%, covering sorting networks and structural matrices), and applied systems for real-world problems (27%, spanning smart home control, social media analysis, and enterprise automation). This evolution reflects increasing focus on practical GPU applications while maintaining core expertise in parallel algorithm design. She actively contributes to academic development through teaching Parallel and Distributed Computing, Economic and Legal Aspects of Enterprise Automation, and DevOps/DevNet courses, while authoring 12+ methodological manuals including "Parallel and Distributed Computing: Laboratory Workshop" (2022) and "System Administration of Linux OS" (2021). Her professional development includes certifications in Constitutional Law, Finance and Investment, DevNet Associate, and All Digital Week initiatives (2020–2021).

• Computational Chemistry
• Quantum Chemistry
• Theoretical Chemistry
• +۲ مورد دیگر

Theo Juncker von Buchwald serves as a Guest Researcher in the Department of Chemistry at the University of Copenhagen, located at Universitetsparken 5 in Copenhagen Ø. His research focuses on advanced computational methods in quantum chemistry, particularly developing and implementing cluster perturbation theories for molecular excitation energies and ground-state properties. His primary research interests center on Computational and Theoretical Chemistry, specializing in electronic structure theory. He develops high-accuracy quantum chemical methods including coupled cluster theory, variational excitation-energy functions, and core-valence separation techniques. His work bridges theoretical chemistry with high-performance computing, implementing parallel algorithms for large-scale molecular systems. Analysis of his four recent publications reveals a consistent research trajectory in Cluster Perturbation Theory (CPT), with increasing computational sophistication. His work demonstrates expertise in both theoretical development (variational formulations, Lagrangian approaches) and practical implementation (parallelization, GPU acceleration). Key trends include targeting CCSD/CCSDT accuracy with reduced computational cost, developing diagnostics for model reliability, and extending CPT to core-excited states for X-ray spectroscopy applications. Research Collaborations and Infrastructure: Collaborates extensively with Kurt V. Mikkelsen, Poul Jørgensen, and Jeppe Olsen Utilizes Frontier supercomputer at Oak Ridge National Laboratory Employs hybrid MPI/OpenMP parallelization with GPU acceleration Receives funding from Danish Council for Independent Research (Grants DFF-0136-00081B, DFF-10.46540/3103-00261B)