Find Academic Supervisors

• High Performance Computing
• Parallel Computing
• Energy Efficiency in Computing
• +4 more

Dr. Joanna Potiopa serves as an Assistant Professor in the Department of Information Systems Software at Maria Curie-Skłodowska University's Faculty of Mathematics, Physics and Computer Science. Her academic profile indicates active research engagement within the university's computational science framework. Her research focuses on High Performance Computing with specialization in Sparse Matrix Vector Multiplication (SPMV) , parallel programming models (OpenMP), and energy-efficient computing on architectures including Intel Xeon Phi. Key investigation areas involve CSR format optimization, scalability analysis, and power management using RAPL interfaces in multicore environments. Dr. Potiopa maintains an active research profile with 5 documented publications yielding bibliometric indicators including h-index of 3 (Web of Science), total CiteScore of 10.6, and ministerial score of 140. Her work demonstrates consistent contributions to computer science and information technology disciplines. She provides academic consultations both in-person at Akademicka Street 9/408 (building D, 4th floor) in Lublin and remotely via MS Teams platform, accommodating student needs through appointment scheduling.

• Biomedical Engineering
• Information and Communication Technology
• Signal Processing
• +3 more

Dr. Anna Gajos-Balińska serves as a Lecturer in the Department of Neuroinformatics and Biomedical Engineering at the Faculty of Mathematics, Physics and Computer Science, Maria Curie-Skłodowska University (UMCS) in Lublin, Poland. Her office is located in room 503 at the Institute of Computer Science where she conducts regular consultations with students. Her research spans the interdisciplinary intersection of Biomedical Engineering (50%) and Information and Communication Technology (50%), with particular expertise in electroencephalography (EEG) signal processing , parallel computing implementations for neuroinformatics, and quantitative analysis of brain activity in psychiatric disorders. Her methodological approaches integrate machine learning tools, CUDA programming, and multi-core architecture optimization to enhance EEG data analysis workflows. Analysis of her publication record reveals consistent contributions to high-performance computing applications in neurodiagnostics, with significant focus on independent component analysis (ICA) algorithms for EEG data processing. Her work demonstrates technical proficiency in optimizing computational frameworks (including Intel Cilk Plus, OpenMP, and BLAS libraries) while maintaining clinical relevance through applications in psychiatric disorder research. Dr. Gajos-Balińska maintains active scholarly profiles through ORCID (0000-0003-4928-5628), Google Scholar, and Scopus, with bibliometric indicators showing an h-index of 4 (Google Scholar), 3 (Scopus), and 3 (Web of Science). Her research has achieved a total ministerial score of 291 within the Polish academic evaluation system. She participates in institutional initiatives including the European Charter for Researchers and Athena UMCS, reflecting engagement with broader academic community standards. Her technical expertise supports both educational activities within her department and potential collaborations through UMCS's research infrastructure.

• Cryptography
• Computer Science
• High-Performance Computing (HPC)
• +3 more

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.

• Power Systems
• Transformers
• Short Circuit Analysis
• +7 more

Dr. Eng. Paweł Albrechtowicz is a Lecturer at the Department of Electrical Engineering within the Faculty of Electrical and Computer Engineering at Cracow University of Technology. His research focuses on power systems, transformers, phase-shifting transformers, and short circuit analysis. Key research areas: Power systems reliability, Renewable energy integration, Active power losses, Transmission line thermal behavior Recent publications demonstrate expertise in phase-shifting transformer applications for power flow control, thermal analysis of cables under fault conditions, and renewable energy system performance. Collaborations include researchers like Smugała Dariusz, Rozegnał Bartosz, and Cisek Piotr. No explicit scientific awards are documented in the provided materials.

• Computer Architecture
• High-Performance Computing
• Network-on-Chip (NoC)
• +7 more

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.

Paweł CzarnulView profile

Associate Professor

• Parallel and Distributed Processing
• High-Performance Computing
• Algorithm Optimization
• +3 more

Ph.D., D. Sc., Eng. Paweł Czarnul is an Associate Professor and Vice-Dean for Cooperation and Development at the Faculty of Electronics, Telecommunications and Informatics, Gdańsk University of Technology. His academic journey includes a PhD (2003) and habilitation (2015) from Gdańsk Tech, with additional management training at the University of Economics and Innovation in Lublin (2011-2012). He previously served as an assistant professor (2003–2016) and held a visiting research position at the University of Michigan (2001–2002). Currently, he leads the Department of Computer Architecture and holds roles in national scientific committees, including the TASK Supercomputing Centre Users’ Council and Ministry of Science advisory bodies. His research focuses on parallel/distributed processing, high-performance computing systems, algorithm optimization, and energy-efficient computational architectures. He has contributed to interdisciplinary projects and authored numerous scientific publications indexed on MostWiedzy, ResearchGate, and Google Scholar. Awarded the Bronze Cross of Merit and multiple Rector Awards for scientific and didactic achievements, Czarnul also advises on industrial PhD programs. Beyond academia, he is an avid wildlife photographer with a dedicated gallery showcasing nature from Arctic regions to European landscapes, and enjoys cycling, swimming, and bridge.

• Computer Science
• Cloud Computing
• Computer Networks
• +4 more

Jakub Gąsior is a Lecturer at the Faculty of Mathematics and Natural Sciences, School of Exact Sciences at Cardinal Stefan Wyszyński University in Warsaw, Poland. His primary research focuses on: Computer Science Cloud Computing Computer Networks Artificial Intelligence Algorithm Design Cellular Automata Parallel Processing Dr. Gąsior's research explores cellular automata, computer systems, load balancing algorithms, scheduling mechanisms, and the concept of 'edge of chaos' in computational systems. His work bridges theoretical computer science with practical applications in distributed computing environments, particularly examining critical states in highly parallel systems. He has published 15 scholarly works with an h-index of 4 according to Scopus citations and 3 according to Web of Science citations. His publications have accumulated a total SNIP of 4.99 and a ministerial score of 865, indicating substantial impact within the information and communication technology field. Dr. Gąsior maintains an ORCID profile (0000-0003-3745-8034) and is available for consultations on Mondays from 13:15 to 14:45 at Wóycickiego 1/3, Building 12, Room 1242. He can be reached via email at j.gasior@uksw.edu.pl and through MS Teams with the code jji326k.

Haojin YangView profile

Professor

• Efficient AI
• Edge AI
• Deep model acceleration and compression
• +7 more

Dr. Haojin Yang is a Professor and group leader of the Multimedia and Machine Learning Research Group at the Hasso Plattner Institute for Digital Engineering in Potsdam, Germany. He works under the supervision of Prof. Dr. Christoph Meinel and leads research in efficient AI, edge computing, and deep learning applications. His research group includes several PhD students and scientific coworkers focusing on cutting-edge machine learning problems. Dr. Yang's research interests span Efficient AI systems with emphasis on edge computing, binary neural networks, deep model acceleration and compression, computer vision applications, and multimodal data retrieval. His work bridges theoretical advancements with practical applications in medical imaging, weather forecasting, and digital humanities. He has made significant contributions to the field of binary neural networks through frameworks like BMXNet and BITorch. His recent publications demonstrate a strong focus on optimizing neural networks for efficiency, particularly in binary and low-bit implementations, while maintaining performance. His work spans computer vision, natural language processing, and multimodal learning, with particular attention to real-world deployment constraints like computational efficiency and energy consumption. BEST PAPER AWARD at the 22nd IEEE International Symposium on Parallel and Distributed Processing with Applications (IEEE ISPA 2024) for 'Low-Bit CUTLASS GEMM Template Auto-Tuning Using Neural Network' Dr. Yang actively supervises numerous PhD and Master's students, with several having completed their degrees and moved to prominent positions at companies like Amazon AI, German Aerospace Center, and MILA-Quebec AI Institute. His research is supported by collaborations with SAP, Wildenstein Plattner Institute, and various academic institutions. He also contributes to the academic community as a reviewer and program committee member for top conferences including ICML, NeurIPS, and CVPR.

Ewa DeelmanView profile

Research Professor

• Scientific Workflow Management
• Distributed Systems
• Resource Provisioning
• +5 more

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.

• Parallel Programming
• Distributed Systems
• Linux Systems
• +3 more

Maciej Pańczyk is a Lecturer at the Faculty of Electrical Engineering and Computer Science at Lublin University of Technology. He teaches courses such as 'Parallel and Distributed Programming' and 'Linux Daemon Programming,' emphasizing practical Linux system usage. His expertise includes distributed systems, operating systems, and software engineering education. He actively supports students with technical guidance on Linux installation, virtualization (VirtualBox), and course-related tools. His research interests extend to 3D digital technologies, as evidenced by projects like digital twin modeling for visually impaired individuals and participation in events like LubGame Conference 2025. Current projects include the 'Integrated Development Programme of Lublin University of Technology,' T1dcoach, Moodle enhancements, and collaborations with institutions like Eduroam and Visual Paradigm.

• Cybersecurity
• Military Internet of Things (MIoT)
• Wireless Sensor Networks (WSN)
• +4 more

Jan Piotr Chudzikiewicz is an Assistant Professor at the Faculty of Cybernetics of Warsaw University of Technology. His research focuses on cybersecurity, military IoT systems, wireless sensor networks (WSN), and fault tolerance mechanisms. He has extensively collaborated on projects involving trusted platform modules (TPM) for securing communication, hypercube network architectures, and reliability engineering in embedded systems. Key contributions include developing authentication protocols for WSNs, optimizing resource placement in fault-tolerant networks, and integrating security frameworks into military IoT infrastructure. His work often combines theoretical analysis with simulation-based validation, addressing challenges in both civilian and defense-oriented network systems. Notable publications span topics such as secured sensor domains, hypercube network reconfiguration, and reliability solutions for MIoT. His interdisciplinary approach bridges computer science, electrical engineering, and cybersecurity to address real-world operational challenges.

• Data Management
• Big Data Processing
• Distributed Systems
• +7 more

Artur Wilczek, PhD, is a researcher in the Department of Applied Informatics at the Faculty of Information and Communication Technology, Wrocław University of Science and Technology. His work focuses on data engineering, distributed systems, and modern data management technologies. His research interests include Big Data Processing , Data Warehousing , Stream Processing , Map-Reduce , RESTful Services , and Flash Memory Storage . These areas reflect a strong engagement with scalable and efficient data systems, particularly in distributed and real-time environments. The analysis of his publications reveals a consistent focus on data-intensive systems, including performance evaluation of database technologies, agile and flexible data warehouse design (e.g., Data Vault), and implementation of stream-based monitoring solutions. His work bridges theoretical algorithm design and practical system deployment, especially in public sector and mobile computing contexts. While no formal awards are listed, his contributions to peer-reviewed journals and conference proceedings in computer science and information systems demonstrate active scholarly engagement. Artur Wilczek has collaborated with researchers such as Maciej Penar, Adrian Najczuk, and Karol Woźniak. Although no advisees are mentioned, his technical publications suggest a role in guiding or contributing to applied research projects. No specific grants or funding sources are referenced in the provided text. No associated laboratories, research teams, or centers are explicitly mentioned in the available information.

Marek WodaView profile

Lecturer

• IT Security
• Cloud Computing
• E-Learning
• +4 more

Marek Woda, PhD, is an academic staff member at the Department of Computer Engineering within the Faculty of Information and Communication Technology at Wrocław University of Science and Technology. His work bridges practical and theoretical aspects of modern computing systems, with a focus on cloud infrastructure, security, and e-learning technologies. His research interests include IT Security , Cloud Computing , E-Learning , Parallel Computing , Web Application Performance , Resource Allocation , and Heterogeneous Systems . These domains reflect both academic rigor and real-world applicability, particularly in scalable and secure computing environments. The recent publications highlight a consistent focus on optimizing cloud-based systems, analyzing performance trade-offs, and leveraging modern hardware architectures. Trends show a strong emphasis on cost-effectiveness in IaaS, responsiveness in SaaS applications, and innovative use of web browsers as platforms for high-performance computing. Marek Woda has not been listed with any scientific awards in the available text. He has collaborated on research projects resulting in peer-reviewed publications but no information is available regarding graduate student supervision or external research grants. His work is closely tied to the research activities of the Department of Computer Engineering, particularly in areas related to dependable and complex computer systems, as evidenced by frequent contributions to the international DepCoS-RELCOMEX conference series.

Cezary CzaplewskiView profile

Professor

• Coarse-grained molecular modeling
• Protein structure prediction
• Molecular dynamics simulations
• +3 more

Professor Cezary Czaplewski of the University of Gdańsk is a leading researcher in computational chemistry and coarse-grained molecular modeling. Affiliated with the Faculty of Chemistry and the Department of Theoretical Chemistry , he heads the UNRES server for protein simulations and contributes to projects like Multi-GPU UNRES and MAGENTA . His work bridges physics-based simulations with experimental data integration. Key roles : Professor, Computational Biophysics, University of Gdańsk Projects : EuroHPC PL, Harmonia9, Enerliq, Parylens Research Focus : His research spans coarse-grained modeling , protein structure prediction , and hydrophobic interaction studies , with applications in virology (SARS-CoV-2), antimicrobial peptide design, and large-scale biomolecular simulations. He specializes in GPU-accelerated algorithms and multi-GPU implementations for scalable systems. Teaching : Currently teaches Molecular mechanics & dynamics , Introduction to Python programming , and Parallel programming (Bioinformatics III) . Past courses include Electronic chemical diagnostics and Software in biomacromolecular calculations for PhD students. Scientific Contributions : Developed the UNRES server for polypeptide simulations, extended the UNRES force field to nucleic acids and membrane proteins, and participated in multiple CASP/CAPRI experiments for protein structure prediction. His 2025 publications focus on time-averaged restraints and multi-GPU scalability. Contact : cezary.czaplewski@ug.edu.pl Location : Room B328, Faculty of Chemistry, University of Gdańsk

• Power Electronics
• DC-DC Converters
• Inverters
• +3 more

Robert Stala is a Professor at the Department of Power Electronics and Automation of Energy Conversion Systems, Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering, AGH University of Science and Technology in Kraków, Poland. He serves on the Senate and other collegial bodies of the university including the Discipline Council for Automation, Electronics, Electrical Engineering and Space Technologies and Senate Committee on Statutes and Regulations. His research focuses on power electronics, particularly DC-DC converters, inverters, and energy conversion systems. Key interests include voltage stress reduction, loss minimization, switched-capacitor topologies, resonant converters, and multilevel inverter systems. He actively investigates the application of GaN and SiC semiconductors for high-efficiency and high-frequency operation in power conversion. Recent publications (2022-2025) reveal strong emphasis on modular DC-DC converter architectures for 48V-to-1V conversion in data centers and 400V-to-48V in telecommunications infrastructure. Trends include parallel converter configurations, natural voltage balancing techniques in multilevel systems, and thermal management optimization. His work consistently addresses conduction/switching loss reduction through innovative circuit topologies and wide-bandgap semiconductor integration. Professor Stala is affiliated with the Power Electronics Laboratory (PEL) at AGH University ( http://www.pelab.agh.edu.pl ), where experimental validation of his theoretical models occurs.