Find Academic Supervisors

• Embedded Systems
• Artificial Neural Networks
• Signal Processing
• +3 more

Magdalena Szymczyk is a Lecturer in the Department of Biocybernetics and Biomedical Engineering at AGH University of Science and Technology, Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering. Her work bridges embedded systems, biomedical signal processing, and geophysical data analysis. Research focuses on energy-efficient sensor networks, neural networks for GPR data classification, and mathematical transforms in signal analysis Expertise in parallel computing, real-time systems, and biomedical engineering applications Her publications (2015–2025) demonstrate a trajectory from parallel neural networks and S-transform/GPR methodologies to recent work on MicroPython in embedded systems. Key themes include energy optimization in distributed architectures and AI-driven signal processing across biomedical and geophysical domains. She has authored works on deterministic chaos in simulations, GPU image processing, and cybersecurity in microcontroller systems. Her current research emphasizes embedded systems security, medical signal diagnostics, and computational methods for geological analysis. She utilizes tools like OpenCL for GPU acceleration and MATLAB for parallel computing implementations.

• Cybersecurity
• Cryptography
• Information Security
• +7 more

Dr. Viktor Melnyk serves as an Assistant Professor in the Department of Applied Computer Science at the Institute of Mathematics, Informatics and Landscape Architecture within the Faculty of Natural Sciences and Technology at John Paul II Catholic University of Lublin. His academic activities span teaching, research, and extensive student supervision across multiple years. His research interests focus on cybersecurity, cryptography, and FPGA-based systems, with particular expertise in wireless network security (especially IEEE 802.15.4), hardware acceleration, and machine learning applications in electronic design. His work bridges theoretical computer science with practical security implementations, evident in his numerous publications and student thesis topics. Analysis of Dr. Melnyk's recent publications reveals a consistent focus on hardware security implementations, particularly for low-rate wireless networks and reconfigurable computing systems. His research trajectory shows increasing integration of machine learning techniques with traditional security protocols, reflecting broader trends in the field. The publications demonstrate both theoretical depth and practical implementation focus, with many papers addressing specific hardware implementations. Dr. Melnyk has served as an Independent External Expert for evaluating grant proposals in the European COST Open Call competition, indicating professional recognition of his expertise. His contributions to the academic community extend to reviewing numerous scientific articles across various domains including biomedical data processing, cyber-physical systems, and cloud computing. His academic advising is exceptionally active, with documentation of supervising over 100 diploma theses from 2015 through 2025 across both Bachelor's and Master's levels. The thesis topics consistently align with his research interests, covering cybersecurity, cryptography, network security, and hardware implementations. He teaches courses including 'Operating Systems,' 'Network Data Protection Technologies,' and 'Multimedia Systems,' with teaching materials adapted for remote delivery during the pandemic period.

Michela TauferView profile

Associate Professor

• Heterogeneous Computing
• Cloud Computing
• Volunteer Computing
• +4 more

Michela Taufer is the David L and Beverly JC Mills Chair of Computer and Information Sciences and an Associate Professor at the University of Delaware. She earned her Masters degrees in Computer Engineering from the University of Padova (Italy) and her doctoral degree in Computer Science from the Swiss Federal Institute of Technology (Switzerland). Her research interests include scientific applications and their advanced programmability in heterogeneous computing (i.e. multi-core and many-core platforms, GPUs); performance analysis; modeling and optimization of multi-scale applications on heterogeneous computing; cloud computing and volunteer computing; numerical reproducibility and stability of large-scale simulations on multi-core platforms; and big data analytics and MapReduce. Dr. Taufer has published research on protein folding, molecular dynamics, and workflow execution on cloud and grid platforms. Her work often focuses on performance characterization and optimization of scientific applications on distributed and parallel systems. From 2003 to 2004 she was a La Jolla Interfaces in Science Training Program (LJIS) Postdoctoral Fellow at the University of California San Diego (UCSD) and The Scripps Research Institute (TSRI) From 2005 to 2007, she was an Assistant Professor at the Computer Science Department of the University of Texas at El Paso (UTEP) She joined the University of Delaware in 2007 as an Assistant Professor and was promoted to Associate Professor with tenure in 2012

Jan CychnerskiView profile

Assistant Professor

• Medical Imaging
• Machine Learning
• Computed Tomography
• +5 more

Dr. Jan Cychnerski is an Assistant Professor at the Department of Computer Architecture within the Faculty of Electronics, Telecommunications and Informatics at Gdańsk University of Technology. His research bridges medical imaging and distributed systems, with significant contributions to AI-driven diagnostic tools and real-time communication platforms. Research Focus: His work spans: Medical imaging algorithms (CT liver segmentation, Hounsfield scale optimization) Machine learning frameworks for healthcare R&D Real-time networked systems for specialized applications like music performance Dataset construction methodologies for medical AI Recent publications demonstrate strong emphasis on adaptive AI solutions for radiology and oncology, with neural network innovations improving diagnostic accuracy. His interdisciplinary approach connects computer architecture with clinical needs. Research Team: Member of Architektura Systemów Komputerowych (Computer Systems Architecture), focusing on distributed/parallel applications and systems engineering.

Mauricio Ayala RincónView profile

Professor

• Term Rewriting Systems
• Automated Reasoning
• Theorem Proving
• +13 more

Mauricio Ayala Rincón is a Full Professor at Universidade de Brasília, affiliated with the Department of Computer Science and the Department of Mathematics. He is a leading researcher in computational logic, formal methods, and term rewriting systems, and heads the Theory of Computation research group (GTC/UnB). Research Interests: His work focuses on the formalization of mathematical and computational theories using proof assistants like PVS. Key areas include term rewriting systems, equational and rewrite-based deduction, automated reasoning, unification, nominal logic, formal verification, and applications in genomics and evolutionary algorithms. He also explores ethics in AI and mechanized mathematics. Recent Publication Trends: His recent articles (2023–2024) reflect a strong emphasis on formalizing algebraic and logical theories in PVS, advancing nominal equational reasoning, anti-unification over algebraic theories, and applying evolutionary algorithms to computational biology. The work is highly theoretical yet applied in verification and combinatorics. Scientific Awards: Best Paper Award at CICM 2023 for "Nominal AC-matching" Advising and Grants: He actively seeks PhD students in algorithmics, formal methods, theorem proving, and AI ethics. He has led numerous research projects, evidenced by extensive publications and editorial roles. He has not listed specific grants, but his continuous output suggests sustained funding. Labs and Teams: He leads the Grupo de Teoria da Computação (GTC/UnB) , which develops PVS libraries for term rewriting (TRS), nominal theories, and evolutionary algorithms. The group maintains public repositories and contributes to the NASA PVS library.

Piotr OramusView profile

Assistant Professor

• Parallel Computing
• Distributed Computing
• Glowworm Swarm Optimization
• +4 more

Piotr Oramus, PhD, is an Assistant Professor in the Department of Information Technologies at Jagiellonian University in Kraków, Poland. His research focuses on parallel and distributed computing, glowworm swarm optimization algorithms, and computational materials science. He holds a PhD in Physics from Jagiellonian University (2001) and an MSc in Physics (1995) from the same institution. Education: MSc (1995), PhD (2001) in Physics from Jagiellonian University Affiliations: Department of Information Technologies, Jagiellonian University; Juna Network Academy (Juniper Networks Academic Alliance) His research interests include optimization algorithms, Monte Carlo simulations for material systems, and distributed computing architectures. Recent work has advanced glowworm swarm optimization techniques and explored atomic ordering dynamics in intermetallic alloys. Key contributions span computational modeling of phase transitions, defect chemistry, and superstructure stability. Teaching responsibilities include courses on computer networks and object-oriented design. He has published extensively on topics ranging from parallel computing frameworks to atomic migration mechanisms in materials science. Grants include BASTION, MASTER, and VENTURES (2011/8 KBN Grant) projects. He leads the Students Computer Laboratory and collaborates with the Juna Network Academy for academic-industrial partnerships.

Wojciech KmiecikView profile

Researcher

• Optical Networks
• Elastic Optical Networks
• Survivable Overlay Multicasting
• +12 more

Dr. Eng. Wojciech Kmiecik is a researcher at the Department of Computer Systems and Networks, Faculty of Electronics, Photonics and Microsystems, Wrocław University of Science and Technology. He is actively involved in multiple research teams including Machine Learning, Computer Networks, Advanced Data Analysis Methods, and Metaheuristics. He also contributes to teaching and supervises diploma theses. His research focuses on optical networks , survivable multicasting , multi-criteria optimization , and metaheuristic algorithms . He has led and contributed to projects such as Dark-Box Optimization, evolutionary multi-criteria optimization, and advanced methods for multi-layer networks. His work bridges theoretical algorithm development with practical network design. The publication trends from 2010 to 2020 show a consistent focus on network survivability , elastic optical networks , and task allocation in parallel systems . His research integrates optimization techniques into networking solutions, particularly in dual homing architectures and deadline-sensitive provisioning. Key themes include resilience, efficiency, and scalability in both optical and computational systems. Scientific Awards: Medal for long-standing service to Wrocław University of Science and Technology Dr. Kmiecik has supervised diploma theses and is involved in teaching. He has not received externally reported grants, but his sustained project involvement suggests institutional or collaborative funding. He collaborates extensively with Prof. Krzysztof Walkowiak and other researchers in the department. Research Labs and Teams: Machine Learning Team Teaching Team Computer Networks Team Advanced Data Analysis Methods Team Metaheuristics Team

• Fuzzy Systems
• Control Theory
• Neural Networks
• +5 more

Leszek Rutkowski is a Professor at the Institute of Computer Science within the Faculty of Computer Science at AGH University of Science and Technology in Kraków, Poland. His primary research focuses on fuzzy systems, control theory, and optimization with significant applications in algorithmic trading and pattern formation dynamics. His research program centers on developing advanced fuzzy control frameworks for complex systems, particularly addressing security challenges in networked environments and optimizing financial trading strategies under uncertainty. Key contributions include novel approaches to Turing pattern control in reaction-diffusion systems, reinforcement learning for multi-agent consensus, and volatility-dependent Forex trading models using multi-criteria optimization. His work consistently bridges theoretical control mechanisms with practical implementations in stochastic and constrained environments. Analysis of his recent publications (2021-2025) reveals three dominant research thrusts: (1) Security-oriented fuzzy control for cyber-physical systems under DoS attacks, (2) Bifurcation analysis and pattern dynamics in fractional-order neural networks, and (3) Interpretable algorithmic trading systems leveraging belief-plausibility uncertainty models. His publications demonstrate increasing integration of reinforcement learning with traditional control theory, particularly in multi-agent coordination problems. Scientific awards: No awards were documented in the provided information sources. Advising and grants: No doctoral students or research grants were explicitly listed in the available materials. Laboratories and teams: Research appears to be conducted within the Institute of Computer Science framework, though specific laboratory names or team structures were not mentioned in the sources.

• Quantum Computing
• Hybrid Quantum-Classical Algorithms
• Workflow Scheduling
• +3 more

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.

Łukasz ChabudzińskiView profile

Assistant Professor

• Hydrology
• Geographic Information Systems (GIS)
• Climatology
• +4 more

Dr. Łukasz Chabudziński serves as Assistant Professor at the Department of Hydrology and Climatology within the Faculty of Earth Sciences and Spatial Management at Maria Curie-Skłodowska University in Lublin. Employed since October 1, 2008, he earned his Doctor of Earth Sciences in Geography on March 30, 2016, following progressive roles from Assistant in the GIS Laboratory (2008-2016) to Assistant Professor positions. His educational background includes postgraduate studies in 'Management of research projects and development works' (2011-2012) and 'Research Project Manager' (2012-2013) at the University of Economics and Innovation in Lublin. Dr. Chabudziński's research focuses on hydrology, GIS applications, and climatology, with particular emphasis on groundwater resource analysis in southeastern Poland's Roztocze region and Lublin Upland. Analysis of his publication record reveals a strong interdisciplinary approach combining hydrology, geomorphology, and computational methods. His recent work increasingly integrates high-performance computing with traditional hydrological analysis, particularly examining spring dynamics, small water bodies, and geological influences on water resources in loess landscapes. Rector's Award (team, third degree) for organizing GIS Challenge (2017) Rector's Award (individual, third degree) for outstanding work for the University (2020) Dr. Chabudziński has supervised 22 diploma theses (21 bachelor's and 1 master's) with notable student successes in competitions like 'GIS Team' and 'GIS Challenge.' He serves as principal investigator for NCN grants and contributes to numerous research projects examining landscape evolution, hydrological processes, and archaeological site relationships in loess regions. He actively shapes geospatial education through leadership roles in academic conferences, competition organization, and curriculum development for geoinformatics programs, bridging theoretical research with practical applications in water resource management and environmental protection.

• Operations Research
• Quantum Computing
• Optimization Algorithms
• +3 more

Prof. Wojciech Bożejko is a Professor at the Department of Control Systems and Mechatronics within the Faculty of Information and Communication Technology at Wrocław University of Science and Technology. His research focuses on optimization algorithms, scheduling theory, and quantum computing applications in discrete optimization problems. He has contributed extensively to the development of metaheuristics for solving complex scheduling challenges, including cyclic job shop, flow shop, and single-machine scheduling under probabilistic or uncertain conditions. Notably, his recent work explores quantum annealing techniques on D-Wave systems for tackling knapsack problems and flow shop scheduling. Prof. Bożejko has also co-edited special issues on discrete systems and authored over 50 peer-reviewed articles in journals like *Computers & Industrial Engineering* and *Archives of Control Sciences*. His methodologies emphasize parallel computing approaches to enhance solution efficiency. Research Interests: - Quantum Computing Applications in Optimization - Metaheuristic Algorithms (Tabu Search, Simulated Annealing) - Cyclic and Flow Shop Scheduling - Stochastic and Robust Scheduling - Parallel Computing for Discrete Optimization Advising & Grants: While no specific grants or advisees are listed, his research outputs indicate significant contributions to collaborative projects in scheduling optimization and quantum computing applications. His work often involves interdisciplinary collaborations, such as with the Wrocław Centre for Networking and Supercomputing. Labs/Teams: Affiliated with the Department of Control Systems and Mechatronics, contributing to research groups focused on automation, discrete systems, and advanced optimization techniques.

• artificial intelligence
• knowledge engineering
• intelligent control and management systems

Donat Orski, PhD, serves as an Assistant Professor at the Department of Computer Science and Systems Engineering within Wrocław University of Science and Technology's Faculty of Information and Communication Technology. His active teaching role is evidenced by published office hours (Wednesdays 11:00-13:15, Thursdays 13:15-15:00) and direct contact channels including email (donat.orski@pwr.edu.pl) and phone (+48 71 320 3583). Dr. Orski's research centers on artificial intelligence applications for managing uncertainty in complex systems. His work specializes in knowledge engineering and intelligent control/management systems, with particular emphasis on resource allocation methodologies using uncertain variables and systemic approaches. This focus enables innovative solutions for operation systems where traditional deterministic models fail. Analysis of his 15 most recent publications (2006-2014) reveals a cohesive research trajectory in uncertainty modeling across production systems, computer networks, and operational frameworks. His work consistently bridges cybernetic theory with practical optimization, frequently appearing in journals like Kybernetes and the Journal of the Operational Research Society. Key contributions include developing C-uncertain variable frameworks and neural network applications for adaptive control under parameter uncertainty. No scientific awards or fellowships are documented in available sources. Information regarding student advising, research grants, or sponsored projects is not provided in current academic profiles. Details about laboratory facilities, research teams, or collaborative projects remain unspecified in publicly accessible institutional records.

Michał PrzewoźniczekView profile

Professor

• Evolutionary Computation
• Multi-objective Optimization
• Many-objective Optimization
• +12 more

Michał Przewoźniczek is a Professor at Wrocław University of Science and Technology (PWr), actively contributing to the fields of evolutionary computation, optimization, and artificial intelligence. He is a key member of multiple research teams, including the Metaheuristics Team, Machine Learning Team, and Advanced Data Analysis Methods Team, reflecting his broad interdisciplinary impact. His research focuses on Evolutionary Computation , Multi- and Many-objective Optimization , Linkage Learning , Problem Decomposition , and Hybridization of metaheuristic methods, with applications in industrial process planning, network optimization, and real-world decision-making. He leads significant research projects such as greybox optimization (2023–2026) and multi-objective evolutionary methods with linkage learning (2021–2026), demonstrating sustained grant support and scientific leadership. The analysis of his recent publications reveals a consistent trend in advancing parameter-less evolutionary algorithms, empirical linkage learning, and scalable distributed implementations using containerization (e.g., Docker). His work bridges theoretical algorithm development with practical applications in optical networks, manufacturing, and distributed computing. His scientific honors include: Best Paper Nomination at the Genetic and Evolutionary Computation Conference (GECCO) Associate Editor, IEEE Transactions on Evolutionary Computation (since January 2023) Prof. Przewoźniczek supervises graduate students as a thesis advisor and collaborates extensively with researchers such as Piotr Dziurzanski, Marcin Komarnicki, Krzysztof Walkowiak, and Leandro Soares Indrusiak. He is actively involved in major conferences like GECCO, CEC, and CORES, and his work is indexed in Google Scholar, ResearchGate, and ORCID (0000-0003-2446-6473). He is affiliated with research groups focusing on Machine Learning, Computer Networks, Advanced Data Analysis, and Metaheuristics, indicating a strong collaborative and team-based research environment.

• Distributed Data Management
• Cloud Computing
• Digital Cultural Heritage
• +4 more

Renata Słota is a Professor at the Institute of Computer Science within the Faculty of Computer Science at AGH University of Science and Technology in Kraków, where she serves as Vice-Dean of the Faculty of Development. Her office is located at D-17, ul. Kawiory 21, room II, 3.34, with contact details including phone +48 12 328 33 35 and email rena@agh.edu.pl. She also contributes to academic governance as a member of the Disciplinary Council for Technical Information Technology and Telecommunications. Her research centers on distributed data management and cloud computing , with pioneering work in digital cultural heritage systems , blockchain-based decentralized authority , and scientific workflow automation . Notable contributions include integrated frameworks for 3D Cultural Heritage objects management, consensus mechanisms for collaborative data sharing, and multi-cloud data access solutions. Her work bridges theoretical advances with practical applications in cultural preservation and scientific computing. Analysis of her 2020-2026 publications reveals dominant trends in decentralized data governance , cultural heritage digitization , and hybrid cloud workflow management . Key themes include blockchain applications for organizational structures, semantic interoperability for quality-oriented data access, and reproducibility frameworks for computational experiments. Her research consistently addresses real-world challenges in global data accessibility and fault tolerance. Professor Słota actively participates in major research initiatives including the Onedata project for global data federation and the Scalarm platform for distributed parameter studies, demonstrating leadership in data-intensive computing environments and collaborative infrastructure development.

• Agent-Based Simulation
• Distributed Systems
• Robotics
• +4 more

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.