جست‌وجوی استاد و پژوهشگر

Christoph Schäferمشاهده پروفایل

پژوهشگر

• Computational Physics
• High Performance Computing
• Smoothed Particle Hydrodynamics
• +۶ مورد دیگر

Christoph Schäfer is a German astrophysicist at the University of Tübingen, affiliated with the Institute for Astronomy and Astrophysics and its Computational Physics department. His work focuses on numerical particle methods, particularly Smoothed Particle Hydrodynamics (SPH), to model planetary formation, collisions, and protoplanetary disc dynamics. University of Tübingen, Institute for Astronomy and Astrophysics, Computational Physics Expert in SPH simulations, high-performance computing, and planet formation Developed the miluph and miluphcuda SPH codes Dr. Schäfer's research spans impact physics, binary star systems, and dust dynamics. His work has been applied to missions like DART and includes modeling Mercury's formation, circumbinary disc interactions, and collisional dust production. He teaches computational astrophysics, numerical methods, and advanced astronomy courses, with a strong emphasis on hands-on programming exercises. His lab ( Numerical Particle Methods Group ) develops GPU-optimized simulation tools, and he has contributed to comparative studies of disc-planet interactions and small body dynamics in the solar system. He maintains an ORCID profile and is recognized in the astronomical community via the asteroid (5364) Christophschafer , discovered in 1980. Contact: ch.schaefer@uni-tuebingen.de (professional) or cm.schaefer@gmail.com (private).

Amirali Baniasadiمشاهده پروفایل

استاد

• Computer Architecture
• Low-power Design
• Power-aware Architectures
• +۴ مورد دیگر

Amirali Baniasadi is a Professor and Graduate Advisor in the Department of Electrical & Computer Engineering at the University of Victoria. He holds a BS from Tehran University, an MS from Sharif University, and a PhD from Northwestern University, with professional engineering (PEng) certification. His research focuses on low-power design, power-aware architectures, VLSI interconnect, and high-performance processors, with applications extending to GPU optimization and machine learning hardware integration. Education: BS, Tehran University MS, Sharif University PhD, Northwestern University Research Interests: Development of energy-efficient processor architectures GPU architecture optimizations and performance analysis Machine learning applications in hardware design and signal processing Quantum annealing for signal processing challenges Security and reliability in network-on-chip systems Recent Trends in Publications: Dr. Baniasadi’s work increasingly integrates AI and deep learning with traditional hardware domains, such as using neural networks for phase unwrapping in SAR imaging, lightweight edge detection networks, and explainable AI frameworks for signal-based models. His research also explores GPU design space optimizations, power-aware architectures, and security against thermal attacks in NoCs. Advising & Grants: Supervised over 15 graduate students, including prominent alumni now in academic and industry roles (e.g., Assistant Professors at Lakehead and Syracuse Universities). Active in securing funding for interdisciplinary projects combining computer architecture with emerging fields like quantum computing and healthcare AI. Labs & Teams: Leads a research group focusing on high-performance computing and low-power systems, collaborating with industry partners on GPU optimization and embedded processor design.

• Parallel Computing
• High-Performance Computing (HPC)
• Programming Models
• +۶ مورد دیگر

Maria Luisa Gil Gómez is a researcher at the Universitat Politècnica de Catalunya (UPC), affiliated with the Department of Computer Architecture and the Barcelona Higher Technical School of Telecommunications Engineering. She holds a PhD in Computer Science and leads research in parallel computing, high-performance computing (HPC), and programming models. Her work focuses on optimizing computational workflows, fault tolerance in distributed systems, and leveraging multi-GPU architectures for scientific simulations. She has contributed to projects like the Programming Models group (PM) at UPC and collaborates with the Barcelona Supercomputing Center (BSC-CNS). Affiliations: UPC Department of Computer Architecture, BSC-CNS, PM Research Group Research Interests: Parallel Programming Models, HPC, GPU Computing, Cellular Automata, Education Technology Her research spans over 147 documented activities, including journal articles, conference presentations, and funded projects. Notable contributions include studies on BCI in music education, distributed algorithms for ARM-based clusters, and the OpenCAL++ framework for parallel cellular automata simulations. She has also explored educational methods integrating creativity and game-based learning in engineering.

Thomas Hobigerمشاهده پروفایل

استاد

• Satellite Navigation
• Inertial Navigation
• Sensor Fusion
• +۷ مورد دیگر

Thomas Hobiger is a Professor and Head of the Institute of Navigation at the University of Stuttgart, Germany, and serves as Dean of Studies for Geodesy and Geoinformatics under Faculty 6: Aerospace Engineering and Geodesy. His research focuses on satellite navigation, inertial navigation systems, sensor fusion, and geodetic applications such as precise orbit determination and GNSS meteorology. He leads a team developing high-precision positioning solutions for autonomous vehicles and airspace surveillance systems. Hobiger holds a PhD from Vienna University of Technology (2005) and has held tenured positions at institutions including Chalmers University of Technology (Sweden) and Japan’s National Institute of Information and Communications Technology (NICT). Notable awards include the AGU Geodesy Section Award (2018) and the NVIDIA Global Impact Award (2016 finalist). He is actively involved in editorial roles for journals like Journal of Geodesy and holds leadership positions in international geodetic organizations. Research interests span navigation hardware/software development, real-time kinematic positioning, and interdisciplinary projects combining GNSS with meteorology and oceanography. His work emphasizes practical applications through collaborations with industry and space agencies, such as JAXA and ESA.

• Theoretical Computer Science
• Distributed Computing
• Approximation Algorithms
• +۴ مورد دیگر

Mohit Daga is a Researcher at KTH Royal Institute of Technology, Sweden, specializing in theoretical computer science, distributed computing, and algorithmic research. He holds an MS in Computer Science from IIT Madras (2018). His current role involves research engineering and supervising master thesis projects across Machine Learning, AI, and GPU Programming. Education: MS in Computer Science, Indian Institute of Technology Madras (2018) Research Interests: His work focuses on distributed algorithms, approximation methods, and dynamic systems. He has explored applications in network analysis, optimization, and medical imaging. Recent projects include developing consensus protocols for DAG-based systems and analyzing multi-shot broadcast stability in distributed networks. Awards: Google Summer of Code Scholarship (2020) Advising & Grants: Supervised 9 master’s theses since 2020. Research internships include Cystar Labs (IIT Madras), IMDEA Networks Lab, and Xerox Research. His work on resource allocation at Xerox led to a patented solution. Labs/Teams: Contributed to projects at KTH’s Department of Computer Science and collaborated with IMDEA Networks and Cystar Labs. Part of the team developing the AciSpace CubeSat payload integration system.

• Numerical Analysis
• High-Performance Computing
• Parallel Computing
• +۵ مورد دیگر

Carl C. Kjelgaard Mikkelsen is an Associate Professor at the Department of Computing Science, Umeå University. He specializes in numerical analysis and high-performance parallel computing, focusing on robust algorithms that cannot fail. He co-authored the StarNEig library for nonsymmetric eigenvalue problems and works on parallel constraint solvers for molecular dynamics and ultra-sparse linear systems. Research Interests: Numerical analysis, parallel computing, eigenvalue problems, linear systems, algorithm design. His recent publications emphasize robust task-based algorithms, GPU acceleration, and precision requirements in Newton's method. He teaches numerical analysis and scientific computing, emphasizing finite precision arithmetic and software documentation.

Carsten Griwodzمشاهده پروفایل

استاد

• Computer Networks
• Distributed Systems
• Network Security
• +۵ مورد دیگر

Carsten Griwodz is a Professor in the Department of Informatics (IFI) at the University of Oslo, specializing in digital infrastructure and security. He leads the Distributed Infrastructure and Security (DIS) research group and contributes to several specialized labs including the Sustainable Immersive Networking Lab (SINLAB), Imagine Beyond 5G Blockchain Lab, and the AliceVision Association. Professor at Department of Informatics, University of Oslo Section leader for DIS: Distributed Infrastructure and Security Group member in Networks and Distributed Systems (ND) Active in sustainable immersive networking and blockchain labs Co-founder of AliceVision open-source photogrammetric framework His research focuses on network performance, edge computing, and immersive technologies. He has pioneered work in cloud gaming QoE, real-time 3D reconstruction, and low-latency systems. Current projects explore redirected walking in VR, GPU programming for tracking, and sustainable networking solutions. Recent publications (2021-2024) demonstrate his expertise in network delay analysis, point cloud compression, virtual reality environments, and GPU-accelerated systems. His work bridges computer science fundamentals with cutting-edge applications in multimedia, security, and health informatics. He supervises numerous master's theses covering diverse topics from wireless streaming challenges to medical imaging advancements, consistently mentoring on topics related to network optimization, immersive technologies, and GPU computing. Supervised 40+ master's theses (2004-2024) Thesis topics span network performance, GPU programming, VR systems, and multimedia processing Active in both theoretical and applied research domains Mentoring interests include HCI, distributed systems, and real-time processing Contributes to education through research-led supervision As a permanent faculty member with extensive publication records and active research groups, Griwodz maintains significant influence in academic circles through both his technical contributions and educational mentorship.

Sergio Pirozzoliمشاهده پروفایل

استاد

• Computational Fluid Dynamics
• Turbulence
• High Performance Computing
• +۴ مورد دیگر

Sergio Pirozzoli is a Full Professor at the Department of Mechanical and Aerospace Engineering , Sapienza University of Rome. His research focuses on Computational Fluid Dynamics (CFD) , Turbulence , High-Performance Computing , and Supersonic/Hypersonic Flow modeling. He specializes in developing advanced numerical solvers for compressible and turbulent flows, with applications to aerospace, thermal engineering, and environmental systems.

Christopher James Henryمشاهده پروفایل

دانشیار

• Machine Learning
• Deep Learning
• Domain Adaptation
• +۵ مورد دیگر

Christopher James Henry is an Associate Professor in the Department of Computer Science at the University of Manitoba , Faculty of Science . He also serves as an Adjunct Professor in the Department of Applied Computer Science at the University of Winnipeg . Roles: Associate Professor, Department of Computer Science, University of Manitoba Adjunct Professor, Department of Applied Computer Science, University of Winnipeg Research Focus: Machine learning and deep learning, particularly in digital agriculture and remote sensing Domain adaptation and generative image models General-purpose GPU computing (GPGPU) and image analysis Labs & Teams: Co-founder of the Applied Parallel Computing and Collaborative Research Laboratory Co-leader of the TerraByte research group , specializing in embedded/robotic systems for agricultural dataset creation

• Big Data Processing
• Heterogeneous Computing
• GPU Acceleration
• +۴ مورد دیگر

Maria Xekalaki is a Research Associate and PhD student in the School of Computer Science at the University of Manchester, affiliated with the Advanced Processor Technologies research group. Her work focuses on accelerating Big Data stacks using heterogeneous hardware resources while optimizing cost and energy efficiency. SDG Contributions: Sustainable Development Goals (SDGs) related to energy efficiency and poverty eradication Research Interests: Her research spans heterogeneous computing, GPU acceleration, Java application optimization, and energy-efficient Big Data processing. She explores techniques for leveraging RISC-V vectorization, improving cross-language interoperability, and advancing GPU-accelerated Fully Homomorphic Encryption (FHE) systems. Article Trends: Her publications emphasize transparent acceleration of Java programs, FHE optimization for privacy-preserving machine learning, and heterogeneous resource management. Key technologies include TornadoVM, OpenCL, and FPGA integration with Big Data frameworks.

• Fluid Dynamics
• Aerospace Engineering
• Computational Fluid Dynamics (CFD)
• +۱۱ مورد دیگر

Francesco Bonelli is an Assistant Professor at the Department of Mechanics, Mathematics & Management (DMMM) at Polytechnic University of Bari, Italy. His research focuses on fluid dynamics, computational modeling of hypersonic flows, and biomedical applications of microwave ablation technology. Academic Rank: Assistant Professor Department: Mechanics, Mathematics & Management Research Focus: Fluid Dynamics, Hypersonic Flow Simulation, Microwave Ablation Email: francesco.bonelli@poliba.it Research interests include: Thermochemical non-equilibrium in high-enthalpy flows GPU-accelerated fluid dynamics simulation Microwave applicator design for cancer therapy Active matter and liquid crystal dynamics Immersed boundary methods for hypersonic flows Turbulent jet analysis in aerospace applications Publication trends show expertise in hypersonic flow modeling, thermochemical non-equilibrium effects, and biomedical engineering applications, particularly in developing cost-effective microwave ablation devices. His work combines advanced numerical methods with practical engineering solutions. Contact : francesco.bonelli@poliba.it

• Agent-Based Simulation
• Distributed Systems
• Robotics
• +۴ مورد دیگر

Wojciech Turek is a University Professor at the Institute of Computer Science, Faculty of Computer Science, AGH University of Science and Technology in Krakow, Poland. He serves as the Faculty Innovation Broker and is a member of the Disciplinary Council for Technical Information Technology and Telecommunications. His research focuses on agent-based simulation, distributed systems, and robotics. His research interests span scalable agent-based computing, urban traffic simulation, robot coordination, and high performance computing. He has developed novel design patterns for distributed simulation and has applied his work to domains such as traffic management, pedestrian dynamics, and multi-robot systems. His approach often leverages the actor model and Erlang for building highly scalable systems. An analysis of his recent publications reveals a strong trend towards scalability and decentralization in simulation and robotics. His work integrates techniques from evolutionary computation, ant colony optimization, and signal propagation to address complex problems in urban environments and robot coordination. He has also explored applications in vehicle safety using mobile phone technology. Professor Turek holds the position of Faculty Innovation Broker at the Faculty of Computer Science, indicating an active role in technology transfer and innovation within the university. While specific details of his advising and grants are not provided in the available information, his extensive publication record suggests significant research activity.

• Biomedical Engineering
• Computer Vision
• Medical Imaging
• +۳ مورد دیگر

Dr. Mirosław Socha is a Lecturer at the Department of Metrology and Electronics within the Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering at AGH University of Science and Technology in Kraków. His office is located in building B-1, room 206, where he conducts research and academic activities. Contact is available via phone (+48 12 617 28 28) or institutional email (socha@agh.edu.pl). His research encompasses several interconnected domains: Biomedical engineering with focus on medical imaging reconstruction and visualization techniques Computer vision applications for surgical navigation and diagnostics Deep learning methodologies for medical implant design and cranial defect solutions Metrology systems including flow calibration and friction measurement Signal processing for EEG and neural interface systems Analysis of his 15 most recent publications reveals strong emphasis on computational methods in healthcare, particularly deep learning-based medical reconstruction (2022-2023), measurement instrumentation (2019-2021), and medical visualization systems (2012-2015). His work consistently bridges theoretical concepts with clinical and industrial applications. No scientific awards, prizes, or fellowships are documented in available sources. Information regarding research grants, laboratory leadership, supervised students, or collaborative teams is unavailable in the provided materials.

Supratim Biswasمشاهده پروفایل

استاد

• Programming Languages
• Compiler Optimization
• Parallelizing Compilers
• +۲ مورد دیگر

Supratim Biswas is a Professor in the Department of Computer Science and Engineering at the Indian Institute of Technology Bombay, where he has served since 1995. His academic career spans over four decades, beginning as a Lecturer in the Computer Center in 1980, progressing to Assistant Professor in 1985, Associate Professor in 1990, and achieving full Professorship in 1995. He has held significant administrative roles including Dean of Academic Programs (2007-2010), Head of CSE Department (2000-2003), and Director of IITB-Monash Academy (2009-2010). His research interests focus on Programming Languages, Compiler Optimization, Parallelizing Compilers, Parallel and Distributed computing, and Combinatorial Optimization . Professor Biswas has made substantial contributions to compiler technology, particularly in parallelization techniques for modern architectures. His work bridges theoretical compiler design with practical applications in high-performance computing and CAD systems, demonstrating how compiler optimizations can significantly enhance computational efficiency in real-world applications. The publication record shows a consistent research trajectory spanning nearly four decades, with recent work (2012-2015) focusing on GPU-based parallel algorithms, loop parallelization techniques for non-uniform data dependencies, and mesh processing for CAD applications. His research demonstrates evolution from foundational compiler theory to contemporary parallel architectures, maintaining relevance through practical applications in computational geometry, CAD systems, and high-performance computing. Excellence in Teaching Award (2000) Professor Biswas has supervised over 60 doctoral and master's students, establishing himself as a dedicated mentor in systems software education. His sponsored research portfolio includes significant projects with CDAC (350 lacs), MIT (133 lacs), TCS (81.3 lacs), and Intel Corporation (10 lacs), demonstrating strong industry-academic collaboration. His teaching portfolio spans both undergraduate and postgraduate levels, including foundational courses like Discrete Structures and advanced topics like Parallelizing Compilers, reflecting his commitment to curriculum development across multiple generations of computer science education. His laboratory work has supported students across B.Tech, M.Tech, and Ph.D. programs, with particular emphasis on compiler construction and operating systems. Through the Continuing Education Program, he has extended his expertise to industry professionals, conducting numerous specialized courses for organizations including VSNL, TCS, DRDO, and Reliance.

Uwe Naumannمشاهده پروفایل

استاد

• Algorithmic Differentiation
• Computational Engineering
• Scientific Computing
• +۶ مورد دیگر

Uwe Naumann is a Universitätsprofessor (University Professor) for Computer Science at RWTH Aachen University, Germany, and Principal Scientist at the Numerical Algorithms Group (NAG) Ltd., Oxford, UK. His research focuses on Algorithmic Differentiation (AD) , including combinatorial problems in AD, integration of AD into numerical methods, AD software development, and AD in parallel high-performance computing. He also explores static and dynamic program analysis, transformation, optimization, and adjoint methods in computational science, engineering, and finance. Education : Dr. rer. nat. (PhD-equivalent in Mathematics, TU Dresden, 1999), Diplom in Mathematics (TU Dresden, 1996). Employment : Principal Scientist, NAG Ltd. (since 2022). Program Director, SIAM Activity Group on Applied and Computational Discrete Algorithms (2021-2022). Professor for Computer Science, RWTH Aachen (since 2004). Postdoctoral Researcher, Argonne National Laboratory (2002-2004). Research Trends : His recent publications emphasize GPU-accelerated optimization, interval arithmetic, Jacobian chaining, differential-algebraic equations, matrix-free methods, and adjoint sensitivity analysis. Contact : naumann@stce.rwth-aachen.de , +49 241 80-28920, IT Center, Room 230, RWTH Aachen.