جست‌وجوی استاد و پژوهشگر

• Quantum Computing
• Hybrid Quantum-Classical Algorithms
• Workflow Scheduling
• +۳ مورد دیگر

Katarzyna Rycerz is a Lecturer at the Institute of Computer Science within the Faculty of Computer Science at AGH University of Science and Technology in Kraków, Poland. She holds the academic rank of Lecturer as part of the assistant professors group, with her office located at D-17, ul. Kawiory 21, room II, 3.54. Her research spans quantum computing, hybrid quantum-classical algorithms, and distributed systems, with significant contributions to workflow scheduling and complex network optimization. Dr. Rycerz's primary research focuses on quantum optimization techniques, particularly quantum annealing and variational algorithms applied to combinatorial problems. Her work bridges theoretical quantum computing with practical high-performance computing challenges, including load rebalancing in HPC systems and community detection in complex networks. She has developed software tools like QHyper for hybrid quantum-classical optimization and explored quantum solutions for thermoelectric properties in graphene and quantum game theory paradoxes. Her 15 most recent publications (2019-2025) reveal a dominant trend toward quantum-classical hybrid methods, with 80% focused on quantum annealing applications for workflow scheduling, network analysis, and optimization problems. Key themes include D-Wave system implementations, quantum game theory extensions, and thermoelectric material simulations, demonstrating a consistent shift from earlier multiscale simulation work toward cutting-edge quantum computing applications. No scientific awards are documented in the available information. Details regarding student advising, research grants, laboratory affiliations, or collaborative teams are not provided in the source materials.

Katarzyna Pernalمشاهده پروفایل

استاد

• Chemistry
• Physics
• Quantum Mechanics
• +۴ مورد دیگر

Katarzyna Pernal is a Professor at the Institute of Physics, University of Lodz , specializing in theoretical and computational chemistry with a focus on quantum mechanics and electronic structure calculations. Her research intersects physics and chemistry, targeting advanced methods for modeling molecular systems. Key research areas include: Quantum chemistry and electronic structure theory Development of correlation functionals for active space methods Adiabatic connection approaches in computational physics Quantum algorithms for chemical problems Recent publications highlight collaborations with researchers in quantum computing (e.g., Variational Quantum Eigensolver ) and on-surface synthesis of organic molecules (e.g., tridecacene ground states ). She utilizes high-performance computing (HPC Cluster) at her institution for complex simulations. Her work spans interdisciplinary applications in materials science, condensed matter physics, and computational chemistry.

Gabriel Wlazłowskiمشاهده پروفایل

استاد

• Theoretical Physics
• Strongly Correlated Fermi Systems
• Superconductivity/Superfluidity
• +۴ مورد دیگر

Professor Gabriel Wlazłowski is a University Professor at the Department of Physics, Warsaw University of Technology. His primary affiliation is with the Physics School/College, where he leads research into strongly correlated Fermi systems. He is actively involved in high-performance computing (HPC) projects utilizing supercomputers like Summit (USA) and Piz Daint (Switzerland). Research focuses on superconductivity/superfluidity in nuclear systems and ultra-cold atoms, including studies of phase transitions, quantum turbulence, and vortex dynamics. His work bridges nuclear astrophysics (neutron star crust dynamics) with cold atom physics, leveraging cutting-edge numerical methods like auxiliary-field quantum Monte Carlo simulations. Grant leadership includes PRACE Tier-0 grants (2017-2020) and multiple National Science Center grants in Poland (2005-present). Current research (2023-2025) explores quantum turbulence in strongly correlated systems and vortex dynamics in fermionic superfluids. Key contributions include discoveries of solitonic excitations in nuclear collisions, vortex pinning mechanisms in neutron stars, and computational models explaining superfluid behavior near unitary limits. His work frequently intersects nuclear physics, condensed matter theory, and computational science.

• Cryptography
• Computer Science
• High-Performance Computing (HPC)
• +۳ مورد دیگر

Dr. Michał Klisowski is a Lecturer at the Fundacja Uniwersytetu Marii Curie-Skłodowskiej , affiliated with the Faculty of Mathematics, Physics and Computer Science and the Department of Information Systems Software . His research focuses on cryptography, high-performance computing, and media truth detection. Research Highlights: Cryptographic protocols, energy-efficient computation, media credibility analysis Email: michal.klisowski@mail.umcs.pl His recent publications address topics such as multicore key exchange protocols , RAPL power monitoring , and fake news detection using machine learning. He holds an ORCID identifier and has published in information and communication technology domains. Collaboration & Tools: Utilizes ORCID and Scopus for academic visibility, with a focus on integrating theoretical cryptography with practical computational efficiency.

• Computer Architecture
• High-Performance Computing
• Network-on-Chip (NoC)
• +۷ مورد دیگر

Vassilis D. Papaefstathiou is a researcher in computer architecture and high-performance computing, affiliated with the Department of Computer Science at the University of Crete and the Institute of Computer Science at FORTH-ICS. His work focuses on energy-efficient manycore systems, network-on-chip design, FPGA prototyping, and RDMA-based communication. His educational background includes a Ph.D. (2013), M.Sc. (2005), and B.Sc. (2002), all from the University of Crete. His research spans advanced topics in computer systems, including hybrid memory management, cache optimization, and scalable interconnects. His research interests include Computer Architecture , Network-on-Chip (NoC) , Reconfigurable Computing , Energy-Efficient Computing , RDMA , and High-Performance Computing . He has made significant contributions to FPGA-based prototyping of manycore systems and low-latency interconnects. His recent publications demonstrate a strong trend in optimizing on-chip networks, memory hierarchies, and communication mechanisms for performance and energy efficiency. Key areas include dual data-rate NoCs, hybrid memory systems with intelligent data migration, and RDMA-enhanced architectures. His work often integrates hardware-software co-design principles for scalable and efficient computing. HiPEAC Paper Award (2012) HiPEAC Paper Award (2016) HiPEAC Paper Award (2017) HiPEAC Paper Award (2020) Best Paper Award Finalist at IEEE/ACM NOCS 2018 He has advised several researchers and students, including Antonis Psistakis, Evangelos Vasilakis, and Ahsen Ejaz, who have co-authored significant publications with him. His collaborative projects include SARC, ExaNeSt, and ECOSCALE, often funded by EU initiatives or research councils. These projects focus on next-generation HPC systems, reconfigurable computing, and scalable architectures. He is a key contributor to the Formic FPGA prototyping platform and has worked extensively on RDMA-capable NICs, cache-integrated network interfaces, and virtualized communication systems. His work is deeply embedded in international research consortia and high-impact venues.

Ewa Deelmanمشاهده پروفایل

استاد پژوهشی

• Scientific Workflow Management
• Distributed Systems
• Resource Provisioning
• +۵ مورد دیگر

Ewa Deelman is a Research Professor in the Department of Computer Science at the University of Southern California (USC) and a Principal Scientist at the USC Information Sciences Institute. She also directs Science Automation Technologies, a research group focused on automating scientific processes through advanced workflow management solutions. Her work is foundational in enabling complex scientific computations across distributed computing environments. Deelman's research centers on scientific workflow automation, including resource provisioning, data management, and job scheduling in distributed systems. She pioneered workflow planning for distributed computations and leads the development of the Pegasus Workflow Management System. Current interests extend to anomaly detection using machine learning, quantum-classical hybrid workflows, and edge-to-cloud continuum integration. Her group's work bridges theoretical advances with practical tools for domain sciences like seismology and molecular dynamics. Analysis of her recent publications reveals a strong emphasis on enhancing workflow robustness through machine learning and emerging technologies. Key trends include LLM-based scheduling optimization, pandemic-driven resilience studies, and quantum workflow integration. Her work increasingly addresses cross-cutting challenges in data-intensive science, particularly in managing computational workflows across heterogeneous infrastructures from edge devices to cloud platforms. As Director of Science Automation Technologies, Deelman oversees a team that has made Pegasus a cornerstone tool in scientific computing. The system handles complex workflow orchestration for projects like CyberShake (seismic hazard analysis) and molecular dynamics simulations, automating data movement, execution, and error recovery across campus clusters, supercomputers, and cloud resources.

Mariusz Matuszekمشاهده پروفایل

استادیار

• High-Performance Computing
• Parallel Computing
• Energy Efficiency in Computing Systems
• +۳ مورد دیگر

Mariusz Matuszek serves as an Assistant Professor at Gdańsk University of Technology within the Department of Computer Systems Architecture, Faculty of Electronics, Telecommunications and Informatics. His research focuses on energy-efficient computing systems and high-performance parallel architectures. His primary research interests span High-Performance Computing , GPU Acceleration , and Energy Efficiency in Computing Systems . Current work examines power-capped optimization for deep neural network training, hardware/software energy measurement methodologies for CPU+GPU systems, and resource-aware problem formulations using ILP, greedy algorithms, and evolutionary approaches. His research bridges theoretical optimization with practical implementation in multi-GPU environments. Analysis of his 2022-2025 publications reveals strong emphasis on measuring and optimizing energy consumption in parallel computing systems, with particular focus on deep learning workloads. Key methodologies include professional hardware metering (Yokogawa WT-310E), Intel RAPL, and NVIDIA NVML interfaces across multi-GPU architectures. His work demonstrates significant performance-energy improvements through strategic power capping. Matuszek actively contributes to computer science education through curriculum development in parallel programming using MPI, OpenMP, and CUDA frameworks. His teaching case studies address the growing demand for HPC expertise in modern machine learning infrastructure development.

Mariusz Uchrońskiمشاهده پروفایل

استاد

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

Professor Mariusz Uchroński is affiliated with Wrocław University of Science and Technology (WUST) as a faculty member in the field of discrete optimization and high-performance computing. His research focuses on advanced computational methods including parallel and distributed algorithms, quantum computing, and task scheduling optimization. Research Interests: He specializes in developing efficient algorithms for complex computational problems, with applications in high-performance computing environments and emerging quantum computing paradigms. His work addresses optimization challenges in parallel/distributed systems and task scheduling methodologies. Contact Information: Email: mariusz.uchronski@pwr.edu.pl Phone: +48 71 320 2456 Office: Z. Janiszewskiego Street 11/17, Wrocław, building C-3, room 214 Consultations: Mondays 16:00-18:00

• Formal Methods
• Interactive Theorem Proving
• Proof Assistants
• +۷ مورد دیگر

Chantal Keller is a Lecturer in the Computer Science Department at IUT d'Orsay, University of Paris-Saclay, and a member of the Formal Methods Laboratory (LMF), a joint unit involving CNRS and ENS Paris-Saclay. Her work bridges theoretical computer science and practical formal verification, with a strong focus on interactive theorem proving and proof assistant technologies. University: University of Paris-Saclay School: IUT d'Orsay Department: Computer Science Department Research Lab: Laboratoire Méthodes Formelles (LMF) Her research centers on enhancing the power and usability of proof assistants like Coq. She has developed tools such as SMTCoq , which integrates SMT solvers into Coq for automated reasoning, and HOLLIGHTCOQ , enabling interoperability between HOL-Light and Coq. Her PhD focused on formal proofs with SMT, and she continues to contribute to foundational aspects of type theory, lambda calculus, and logical frameworks. The 15 most recent articles reflect deep engagement with formal logic, programming language semantics, and automated reasoning. Key trends include proof interoperability, termination analysis, constraint programming, and the formalization of mathematical and computational systems in proof assistants. Her work spans theoretical developments and practical implementations in Coq, Agda, and OCaml. Chantal Keller has served on numerous program committees, including ITP, CPP, POPL, TAP, and JFLA, highlighting her active role in the formal methods community. She has held teaching and research positions since 2007, including roles at École Polytechnique and the University of Nottingham. 2025: Co-PC Chair, ITP 2022: Chair, JFLA 2021: Vice-Chair, JFLA; Co-Chair, PxTP 2017–2022: Coordinator, Digicosme UPSCaLe working group She has advised on workshops and school programs, including the EasyCrypt-F*-CryptoVerif school in 2014. She has not received any explicitly mentioned scientific awards in the provided texts. She is actively involved in teaching programming, algorithms, and mobile development at IUT d'Orsay.

Maciej Malawskiمشاهده پروفایل

دانشیار

• Parallel and Distributed Computing
• Cloud Computing
• Data Science
• +۵ مورد دیگر

Maciej Malawski is an Associate Professor at the Department of Computer Science, AGH University of Science and Technology, and Research Team Leader at the Sano Centre for Computational Medicine in Kraków, Poland. He holds a PhD in Computer Science (2009) and MSc degrees in Computer Science (2001) and Physics (2004). His research focuses on parallel/distributed computing, cloud technologies, and biomedical applications, with contributions to federated learning, serverless computing, and scientific workflow optimization. Education: PhD in Computer Science, AGH University (2009) MSc in Physics, Jagiellonian University (2004) MSc in Computer Science, AGH University (2001) Research Interests: Parallel computing, cloud infrastructures, serverless systems, federated learning, biomedical data analysis, and workflow scheduling. His work bridges computational methods with healthcare, such as federated learning for medical imaging and sensitivity analysis in cardiovascular models. Publications & Awards: Over 50 international publications, including top-tier venues like SC, IPDPS, and IEEE Cluster. Recognitions include the 2018 AGH Rector’s Award, Publons Peer Review Award (2018), and 1st place in the Executable Paper Grand Challenge (2011). Labs & Affiliations: Director of Sano, senior researcher at ACC Cyfronet AGH, and collaborator with CERN. Leads projects on HPC/Cloud integration and scientific computing for medicine.

Marek Behrمشاهده پروفایل

استاد

• Computational Mechanics
• Physiological Modeling
• Numerical Methods
• +۷ مورد دیگر

Professor Marek Behr is a Universitätsprofessor (C4/W3) at the Chair for Computational Analysis of Technical Systems (CATS) in the Faculty of Mechanical Engineering at RWTH Aachen University, Germany. He serves as founding director of the Center for Simulation and Data Science (JARA-CSD) since 2018, President of the German Association for Computational Mechanics since 2021, and is an Adjunct Professor of Chemical and Biomolecular Engineering at Rice University since 2005. Professor Behr's research focuses on computational mechanics with particular emphasis on physiological model development and numerical methods for complex fluids. His work spans Computational Fluid Dynamics (CFD) , High-Performance Computing (HPC) , Fluid-Structure Interaction (FSI) , and 4D Finite Element Methods . His research group at CATS develops advanced computational techniques for engineering and biomedical applications, with recent focus on cardiovascular modeling including hemolysis prediction, stent restenosis, and left ventricular dynamics under assist device support. The publication record of Professor Behr shows a strong trajectory in computational biomechanics, particularly in cardiovascular applications. His recent work (2023-2025) demonstrates increasing focus on multiphysics modeling of blood flow, stent-artery interactions, and computational approaches to understanding hemolysis and restenosis mechanisms. His research integrates advanced numerical methods with physiological modeling to address clinically relevant problems in cardiovascular medicine. Professor Behr has received significant recognition for his contributions to computational mechanics: Elected Fellow of the International Association for Computational Mechanics (IACM) in 2014 Recipient of the Leading Scientist Award (3.6 M€) from St. Petersburg, Russian Federation in 2010, described as "the largest individual scientific award in the world" Google Scholar h-Index of 45 and ISI h-Index of 30, based on approximately 3,600 citations Professor Behr serves as speaker of the International Research Training Group 2379 Modern Inverse Problems in collaboration with the Oden Institute at the University of Texas at Austin. He has established significant research collaborations across institutions and has supervised numerous PhD and Master's students. His work is supported by substantial research funding, including the 3.6 M€ Leading Scientist Award. The Chair for Computational Analysis of Technical Systems (CATS) under Professor Behr's leadership forms part of the Center for Simulation and Data Science (JARA-CSD), a collaboration between RWTH Aachen University and Forschungszentrum Jülich. CATS focuses on developing and applying advanced computational methods to solve complex engineering problems, with particular expertise in fluid dynamics, solid mechanics, and their interaction in biological systems.

Aleksander Byrskiمشاهده پروفایل

استاد

• Nature-inspired Computing
• Agent-based Distributed Computation
• Artificial Intelligence
• +۳ مورد دیگر

Aleksander Byrski is a Full Professor at AGH University of Science and Technology, serving as Deputy Dean for Research and Cooperation in the Faculty of Computer Science, Electronics and Telecommunications. He is also an active member of the Council of Information Technology and Telecommunications and Deputy President of the Try IT Foundation. His research focuses on nature-inspired computing, agent-based distributed computation, artificial intelligence, and parallel/distributed computing and simulations. Byrski's work spans optimization algorithms, high-performance computing frameworks, and applications in urban traffic simulation, healthcare, and engineering. His research interests emphasize scalable agent-based systems, socio-cognitive metaheuristics, and their practical implementations in solving complex real-world problems. Key contributions include advancements in ant colony optimization, evolutionary multi-agent systems, and distributed computing paradigms. Byrski actively bridges theoretical computer science with applied domains such as traffic management, epidemic modeling, and smart city technologies. Articles from 2023–2025 highlight his focus on hybrid metaheuristics, socio-cognitive algorithms, and optimization for time-delay systems. Notable themes include improving algorithm efficiency through migration strategies, leveraging two-dimensional pheromone models, and exploring open/closed source frameworks for large-scale optimization. His work often addresses scalability challenges in HPC environments and real-time systems. Byrski has received no explicitly mentioned scientific awards but is recognized for his leadership roles in academic and industry collaborations. His advising and grants are not detailed here but reflect ongoing research in agent-based computing and functional programming paradigms. He contributes to interdisciplinary teams advancing computational intelligence and societal applications such as epidemic simulation and smart infrastructure.

Wiesław Nowińskiمشاهده پروفایل

پژوهشگر

• Neuroscience
• Medical Imaging
• Neuroinformatics
• +۳ مورد دیگر

Prof. Wiesław Nowiński is a Senior Researcher affiliated with four of the world’s top ten universities (per Shanghai ranking). He is renowned for creating over 51 human brain atlases, including 35 commercial products used worldwide in neurosurgery , neuroradiology , neurology , and neuroeducation . His career spans 590 scientific publications and 71 granted patents (23 US, 11 EP, 33 SG, 4 DE), reflecting his innovation in neurotechnology. Research Interests: Nanoscale brain modeling Human brain atlas development Morphology and connectome modeling Neuroimaging and computational neuroscience Acute stroke taxonomy Medical imaging analysis Stroke diagnostics and treatment protocols Image processing in neurology High-performance computing in neuroinformatics Scalable simulations for brain modeling Data storage optimization for nanoscale models Parallel processing applications Patents and Publications: His work bridges science, medicine, and art, with focus areas including brain mapping , neurovisualization , and biomedical technology . Details are available at www.wieslawnowinski.com .

Bartosz Baliśمشاهده پروفایل

دانشیار

• scientific workflows
• data science
• e-Science
• +۲ مورد دیگر

Bartosz Baliś serves as Associate Professor at the Institute of Computer Science, AGH University of Science and Technology, and holds a Senior Postdoctoral position in Extreme-scale Data and Computing at the Sano Centre for Computational Medicine. He actively contributes to the CERN ALICE experiment as a core team member. His educational foundation includes dual degrees from AGH University and Jagiellonian University, culminating in both PhD and DSc (habilitation) qualifications in Computer Science from AGH University. These advanced credentials underpin his specialized expertise in computational methodologies. Dr. Baliś pioneers research in scientific workflows, data science, and distributed computing systems , with particular emphasis on cloud-native architectures and e-Science infrastructures. His innovative work bridges theoretical computer science with practical applications in large-scale data processing, advancing methodologies for scientific computing environments through novel workflow management solutions. Recent publications demonstrate a clear trajectory toward serverless computing paradigms and comprehensive observability frameworks for scientific applications, reflecting his commitment to solving scalability challenges in modern computational research through cutting-edge cloud technologies. He has secured substantial research funding through participation in major European initiatives including CrossGrid, CoreGRID, K-Wf Grid, ViroLab, Gredia, UrbanFlood, PaaSage, and WATERLINE across FP5-FP7 and Horizon 2020 programs. His leadership extends to conference organization as Euro-Par 2020 General Co-chair, HPCS 2018-19 Tutorials Co-chair, and IEEE/ACM SC committee roles. Within institutional frameworks, Dr. Baliś contributes to the Extreme-scale Data and Computing research group at Sano Centre while maintaining active collaboration with the international CERN ALICE collaboration, where his computational expertise supports high-energy physics research infrastructure.

• Cloud Computing
• Database Systems
• Parallel Processing
• +۳ مورد دیگر

Mariusz Fraś is a researcher affiliated with the Faculty of Information and Communication Technology at Wrocław University of Science and Technology. He works within the Department of Computer Science and Systems Engineering , focusing on computational systems' performance and cloud-based architectures. His research spans database optimization, parallel processing, and mobile application frameworks. Research interests include: Computational cloud scalability and cost optimization Database application performance analysis Parallel processing frameworks Mobile sensor data processing Web content delivery efficiency His publications demonstrate expertise in cloud computing trends, with 10 peer-reviewed works since 2014. Notable collaborations include researchers like Piotr Karwaczyński and Bogdan Marczuk. Current research likely continues exploring hybrid cloud environments and software performance metrics. Contact: mariusz.fras@pwr.edu.pl , Room 301, Building C-3, Wrocław University of Science and Technology.