جستجوی استاد راهنمای دانشگاهی

• Machine Learning
• Electrical Engineering
• Computer Science
• +۷ مورد دیگر

Anna Plichta is an Assistant Professor at the Department of Computer Science, Faculty of Computer Science and Telecommunications at Jagiellonian University. Her primary discipline is Information and Communication Technology (ICT), with a strong focus on interdisciplinary applications spanning electrical engineering, bioinformatics, and educational technology. Her research interests include machine learning techniques (neural networks, decision trees, genetic algorithms), motor diagnostics in electromechanical systems, bacterial classification using computational methods, and pedagogical strategies for student engagement. She has published widely on topics such as fault detection in induction motors, bacterial taxonomy through classifier systems, and the integration of CUDA technology for optimization problems. Anna’s work bridges theoretical computer science with practical applications, including robotics navigation algorithms, FPGA-based signal processing tools, and e-learning systems. She is actively involved in curriculum development, particularly in evaluating strategies like industry study visits for student professionalization. Her academic contributions span 18 documented publications, with a Hirsch index of 3 across Scopus and Web of Science. She maintains an active profile on ORCID and Scopus, reflecting her commitment to interdisciplinary research and academic collaboration.

Krzysztof Spalikمشاهده پروفایل

استاد

• Phylogenetics
• Evolutionary Biology
• Plant Taxonomy
• +۳ مورد دیگر

Prof. Krzysztof Spalik is a distinguished academic serving as Dean of the Faculty of Biology at the University of Warsaw and Head of the Scientific Council of the Biological-Chemical Research Centre. He leads the Committee of Environmental and Evolutionary Biology at the Polish Academy of Sciences (PAS). His research focuses on phylogenetics, evolution, taxonomy, and biogeography of Apiaceae, with particular emphasis on economically important plants like carrots and medicinal genera such as Ferula and Thapsia. His current project investigates ecological factors shaping secondary woodiness in Apioideae. Spalik has held numerous leadership roles, including deputy head of the Committee for Evolutionary and Theoretical Biology PAS and membership in expert panels for the National Science Centre Poland. He is a recipient of the 2013 Academic Teacher of the Year award for his contributions to education in exact and natural sciences at UW. Spalik actively engages in educational research, collaborating with the Institute of Educational Research and serving on the Central Examination Board. His teaching portfolio includes Botany, Ecological Education, Evolutionism, and Taxonomy, reflecting his commitment to both research and pedagogy. His research has led to groundbreaking taxonomic revisions (e.g., Laserocarpum in Greece) and advancements in phylogenetic methodologies, such as the Fast mvSLOUCH tool for analyzing multivariate trait evolution. Spalik’s work bridges molecular systematics with ecological adaptation, addressing topics like dispersal mechanisms, drought resistance, and inflorescence evolution in Apiaceae. Over 50 peer-reviewed publications and active roles in international collaborations underscore his influence in plant evolutionary biology.

Piotr Sankowskiمشاهده پروفایل

استاد

• Algorithms
• Machine Learning
• Graph Theory
• +۵ مورد دیگر

Piotr Sankowski is a Professor at the Institute of Informatics, University of Warsaw, specializing in algorithms and theoretical computer science with applications in economics and machine learning. He is also CEO of MIM Solutions, deploying ML solutions, and heads the IDEAS NCBR center for AI and Digital Economy. His research focuses on algorithm design, computational complexity, and interdisciplinary applications in physics and economics. Education & Affiliations: Professor at University of Warsaw's Faculty of Mathematics, Informatics, and Mechanics (MIM) Head of IDEAS NCBR Center (Artificial Intelligence & Digital Economy) CEO of MIM Solutions (AI/ML consulting) Research Interests: Piotr's work bridges theoretical computer science and practical applications, with key areas: Algorithms for matching problems, graph theory, and optimization Machine learning explainability and feature importance Quantum tunneling phenomena in semiconductor nanostructures (physics) Algorithmic game theory and network design His ERC grants highlight contributions to algorithmic foundations and interdisciplinary research. Grants & Awards: ERC Starting (2010), Proof of Concept (2015), and Consolidator (2017) Grants First Pole to secure three ERC grants Fellow of the Institute of Informatics at University of Warsaw Publications: Over 80 papers spanning CS (algorithms, ML) and physics (solid-state theory). Recent work focuses on online algorithms, dynamic graph problems, and scalable ML systems. Labs & Projects: Leads the IGAFIT initiative promoting algorithms in Europe, and the EXALT project for explainable optimization tools. Active in the IDEAS NCBR center for AI innovation.

• Operations Research
• Quantum Computing
• Optimization Algorithms
• +۳ مورد دیگر

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 Przewoźniczekمشاهده پروفایل

استاد

• Evolutionary Computation
• Multi-objective Optimization
• Many-objective Optimization
• +۱۲ مورد دیگر

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
• +۴ مورد دیگر

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
• +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.

• High Performance Computing
• Parallel Computing
• Energy Efficiency in Computing
• +۴ مورد دیگر

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.

• Software Engineering
• Modeling of Information Systems
• Scientific Computing
• +۴ مورد دیگر

Dr. Andrzej Stefan Daniluk is a lecturer (Adiunkt) at Maria Curie-Skłodowska University in Lublin, Poland, affiliated with the Department of Cybersecurity and Computational Linguistics within the Faculty of Mathematics, Physics and Computer Science. His academic work spans both theoretical and practical aspects of computer science and physics, with particular emphasis on scientific computing applications. Dr. Daniluk's research interests focus on software engineering for scientific purposes, modeling of information systems, and wired/wireless data transmission protocols including RS 232C, MODBUS, USB, and Bluetooth. His scholarly work demonstrates a unique intersection between computer programming and materials science, particularly in the development of simulation software for RHEED (Reflection High-Energy Electron Diffraction) analysis. His publications reveal a consistent progression from practical programming guides to sophisticated computational physics models. Analysis of his publication record shows a clear evolution from early practical programming guides (USB, Bluetooth, C++Builder, Delphi) to increasingly specialized scientific computing work focused on RHEED simulations. His most recent publications (2020-2025) concentrate on developing sophisticated software frameworks (particularly rheed++) for modeling crystal growth processes using Python and C++, with applications in semiconductor research and nanotechnology. The interdisciplinary nature of his work bridges computer science, physics, and materials engineering. Dr. Daniluk has published 32 scholarly works with an h-index of 7 across multiple citation databases (Google Scholar, Scopus, Web of Science), accumulating a total ministerial score of 1,270. His publications include both academic papers and practical programming guides, with notable books such as 'USB. Praktyczne programowanie z Windows API w C++' (multiple editions) and 'Bluetooth. Praktyczne programowanie.' As an academic instructor, Dr. Daniluk offers consultations on Mondays from 11:30-13:30 in room D422 of the Institute of Computer Science building. His teaching appears to emphasize practical programming skills and their application to scientific computing problems, reflecting his dual expertise in software development and computational physics.

• Biomedical Engineering
• Information and Communication Technology
• Signal Processing
• +۳ مورد دیگر

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)
• +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.

• Power Systems
• Transformers
• Short Circuit Analysis
• +۷ مورد دیگر

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.

Tytus Pikiesمشاهده پروفایل

استادیار

• Scheduling Algorithms
• Graph Theory
• Operations Research
• +۳ مورد دیگر

Dr. Tytus Pikies is an Assistant Professor at the Department of Algorithms and Modeling Systems within the Faculty of Electronics, Telecommunications and Informatics at Gdańsk University of Technology. His research focuses on theoretical aspects of computer science, particularly in the domain of scheduling algorithms and graph theory applications. Dr. Pikies' research interests span across several areas of theoretical computer science and operations research: Scheduling algorithms for parallel computing systems Graph theory applications in job scheduling Complexity analysis of scheduling problems Optimization techniques for machine scheduling Incompatibility relations modeling using graph structures Approximation algorithms for NP-hard scheduling problems His recent publications demonstrate a consistent research trajectory in scheduling theory, with particular emphasis on problems involving incompatibility constraints between jobs. Dr. Pikies has made significant contributions to understanding scheduling problems where jobs have compatibility constraints modeled as various graph structures including block graphs, bipartite graphs, and complete multipartite graphs. Dr. Pikies has received recognition for his work in theoretical computer science, with publications appearing in reputable journals such as Computers & Operations Research and Artificial Intelligence. His research bridges theoretical computer science with practical applications in parallel computing systems. He collaborates with other researchers in the field, including H. Furmańczyk, K. Turowski, and M. Kubale, contributing to the advancement of scheduling theory and its applications.