جست‌وجوی استاد و پژوهشگر

Przemysław Rybaمشاهده پروفایل

پژوهشگر

• Computer Science
• Networking
• Algorithms
• +۲ مورد دیگر

Przemysław Ryba is a researcher at the Faculty of Information and Communication Technology , Department of Systems and Computer Networks, Wrocław University of Science and Technology. He focuses on network engineering, anomaly detection, and medical telemetry systems. Current faculty member with active research and publications Specializes in wide area network optimization and biosignal processing Collaborates on software-defined networking and telemetry applications His research spans network resource allocation, heuristic algorithms for WANs, and biomedical signal processing systems. Recent work includes anomaly detection in server metrics and SDN experimental topologies. Publications since 2008 reflect expertise in hierarchical network design, medical telemetry, and computational methods. No formal scientific awards mentioned.

• Neural Networks
• Machine Learning
• Data Science
• +۱۱ مورد دیگر

Piotr Ciskowski is a researcher affiliated with the Department of Computer Engineering at the Faculty of Information and Communication Technology, Wrocław University of Science and Technology. His work bridges computational methods with practical applications in finance, transportation, and building systems. Research Focus : Neural networks, machine learning, and optimization for decision support Application Areas : Forex market analysis, intelligent transportation systems, and adaptive building controls His publications highlight a consistent application of neural networks to complex systems, including urban traffic modeling (2016), forex data streams (2010), and contextual mapping (2006, 2004). Key subfields include recurrent neural networks, self-organizing maps, and technical analysis of financial markets. Contact: piotr.ciskowski@pwr.edu.pl | Office: C-16 building (Technopolis), room P 2.2 | Tel: +48 71 340 7625

Jakub Klikowskiمشاهده پروفایل

استادیار

• Machine Learning
• Data Stream Classification
• Imbalanced Data
• +۱۲ مورد دیگر

Jakub Klikowski is an Assistant Professor in the Department of Computer Systems and Networks at the Faculty of Electronics, Wrocław University of Science and Technology. He has been employed since October 2018 and earned his PhD in engineering and technical sciences in March 2022 for his dissertation on ensemble methods for imbalanced data stream classification. He is actively involved in research and teaching, contributing to multiple research teams including the Machine Learning Team and Advanced Data Analysis Methods Team. Research Interests: Classification of imbalanced and streaming data Ensemble learning and one-class classification Natural language processing (NLP) Concept drift detection and adaptive learning Graph neural networks and spam/disinformation detection Multi-criteria optimization and evolutionary algorithms His research is primarily conducted within the IDSTREAM and GEOM projects, focusing on developing robust classifiers for challenging data environments. His recent work emphasizes hybrid preprocessing, ensemble weighting, and drift detection mechanisms. Publication Trends: His publications from 2019 to 2022 reveal a consistent focus on improving classification performance in imbalanced data streams using ensemble techniques, preprocessing strategies, and drift detection. Key themes include weighted bagging, Hellinger distance, centroid analysis, and genetic optimization, all applied to real-world decision-making tasks. Scientific Awards: Rector of Wrocław University of Science and Technology Award (2020) Distinction in the Secundus program for young scientists (2023) Honorable Mention for doctoral dissertation (2022) Advising and Grants: Dr. Klikowski supervises diploma theses on topics such as NLP, text summarization, hate speech detection, and graph neural networks. He is involved in research projects including IDSTREAM and GEOM, which support his work in data stream classification and optimization. He collaborates with leading researchers like Prof. Michał Woźniak and Prof. Robert Burduk. Labs and Teams: He is an active member of the Machine Learning Team, Advanced Data Analysis Methods Team, and other research groups at the Department of Computer Systems and Networks. These teams foster interdisciplinary research in AI, data science, and network optimization.

• Formal Methods
• Concurrent Systems
• Real-Time Systems
• +۷ مورد دیگر

Professor Marcin Szpyrka is a faculty member at AGH University of Science and Technology in Kraków, Poland, where he works in the Department of Applied Informatics within the Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering. He holds the position of Professor and maintains an office in building C-2, room 321. His academic work spans formal methods, concurrent systems modeling, and data mining applications. Professor Szpyrka's primary research interests focus on formal methods including the Alvis modeling language, Petri nets, and process algebras. He specializes in the modeling and verification of concurrent and real-time systems , with applications spanning industrial processes, automotive diagnostics, and cybersecurity. His work bridges theoretical computer science with practical engineering applications, particularly in embedded systems and data analysis. Analysis of Professor Szpyrka's recent publications reveals a clear research trajectory focusing on formal verification techniques applied to increasingly complex systems. His work has evolved from foundational research on the Alvis language to practical applications in automotive systems, industrial processes, and cybersecurity. The publications demonstrate consistent expertise in modeling concurrent systems while expanding into data mining and machine learning applications for anomaly detection and system diagnostics. Rector's Finance Committee Disciplinary Council for Technical Information Technology and Telecommunications Disciplinary Appeals Committee for Doctoral Students Supervised 9 PhD dissertations between 2009-2024 Developed academic resources including the aghdpl LaTeX class for thesis preparation Mentored students working on formal methods, concurrent systems, and data mining applications Professor Szpyrka leads the Formal Methods research group with projects hosted at fm.kis.agh.edu.pl, focusing on the development and application of the Alvis modeling language for system verification.

• Tourism Management
• Hotel Industry
• Spa and Wellness Management
• +۴ مورد دیگر

Dr. Maciej Abram serves as Associate Professor and Head of the Hotel Management Department at the Institute of Tourism within the Bronisław Czech Academy of Physical Education in Krakow. With a PhD in Economics specializing in Management Sciences, his academic career spans over two decades of research and teaching in tourism management, hotel operations, and spa/wellness center organization. His research interests focus on strategic and operational management of tourism companies, particularly examining the hotel industry, spa resort organization, tourism traffic patterns, and customer needs in specific market conditions. Professor Abram has developed expertise in strategic planning of tourism development at local levels, corporate social responsibility in the hotel industry, and factors affecting customer service quality in tourism establishments. His scholarly output demonstrates consistent research activity from 1999 through 2020, with recent publications addressing contemporary challenges in business tourism development, sustainability practices, and service quality in the Polish hospitality sector. The research shows a clear trajectory from foundational work on tourism phenomena monitoring toward more sophisticated analyses of strategic management and service quality in specialized tourism sectors. As an educator, Professor Abram supervises the Hotel Management specialization, conducts lectures and exercises on Organization and Operation of Hotel Establishments, and teaches Coaching in Recreation. He has authored the textbook 'Spa and Wellness Centers: Organization and Operation' (2016) and completed specialized training in management systems according to EuropeSpa criteria.

Paweł Ksieniewiczمشاهده پروفایل

استاد

• Pattern Recognition
• Data Streams
• Hyperspectral Image Processing
• +۷ مورد دیگر

Paweł Ksieniewicz is a Professor at Wrocław University of Science and Technology, affiliated with the Faculty of Electronics and the Department of Computer Systems and Networks. He is a member of the Computer Networks Team and the Machine Learning Team, and serves as a project manager for SWAROG (2021–2025) and contributor to IDSTREAM and GEOM projects. His research interests include: Pattern Recognition Data Streams Hyperspectral Image Processing Imbalanced Data Classification Fake News Detection Classifier Ensembles Ksieniewicz's recent publications focus on challenges in data stream mining, particularly in dynamically imbalanced environments, prior probability estimation, and ensemble methods. His work spans applications in cybersecurity (fake news, IoT attack detection) and healthcare (glaucoma diagnosis). He has contributed to open-source tools like the Stream-learn Python library, emphasizing practical and reproducible machine learning research. His scientific awards include: Minister of Education and Science Scholarship for Outstanding Young Scientists Award of the Polish Society for Artificial Intelligence for Best Doctoral Thesis Multiple Rector's Awards for scientific achievements (2019–2022) Best Paper Award at ICAISC 2021 Winner of the Secundus and Primus research incentive programs Appointment to Academia Iuvenum (2024–2026) Ksieniewicz actively supervises students and has collaborated with researchers such as Michał Woźniak, Paweł Zyblewski, and Robert Burduk. He has secured research grants through national projects and serves on the Discipline Council for Technical Computer Science and Teleinformatics. He has also participated in public outreach, including lectures during Science Week and World Information Society Day. He leads and contributes to multiple research teams, including: Machine Learning Team Computer Networks Team Advanced Data Analysis Methods Team Metaheuristics Team

• Software Engineering
• Model-Driven Engineering
• Digitization of Cultural Heritage
• +۳ مورد دیگر

Kamil Żyła is an Assistant Professor at the Lublin University of Technology , Faculty of Electrical Engineering and Computer Science, Department of Computer Science. His research focuses on software engineering , model-driven engineering , and digitization of cultural heritage using 3D technologies and mobile applications .

• Computer Networks
• Network Security
• Wireless Sensor Networks
• +۴ مورد دیگر

Adam Czubak serves as an Assistant Professor ( adiunkt ) in the Department of Computer Science at the University of Opole, Poland. His institutional email is adam.czubak@uni.opole.pl, and he maintains an active research profile with ORCID 0000-0003-1336-2839. His research spans multiple critical areas of modern networking and security, with primary focus on Computer Networks , Network Security , and Wireless Sensor Networks . His work addresses fundamental challenges in routing algorithms, cryptographic protocols, and vulnerability analysis. Recent publications demonstrate a clear trajectory toward practical cybersecurity applications, particularly in vulnerability assessment frameworks and attack modeling. Analysis of his publication timeline reveals an evolution from theoretical networking foundations (2009-2013) toward applied security research (2014-present). His work bridges algorithmic complexity, cryptographic implementation, and real-world network vulnerabilities, with notable contributions to SDN security, firewall analysis, and Chacha20 cryptography. The consistent focus on performance-cost tradeoffs across WAN/SDN systems demonstrates practical engineering sensibilities. Career metrics include 17 publications, 1 research project, and 1 media appearance. His bibliometric profile shows a Web of Science h-index of 2, SNIP of 0.401, and CiteScore of 0.7, with a Polish ministerial research score of 390 points. Professor Czubak maintains active scholarly presence through Google Scholar, Scopus, and LinkedIn profiles, with documented collaborations through multi-center publications. His research output reflects strong alignment with contemporary cybersecurity challenges while maintaining rigorous theoretical foundations in network science.

Joanna Wąsمشاهده پروفایل

پژوهشگر

• Geomorphology
• Biogeomorphology
• Ecology and nature conservation in urban areas

Joanna Wąs is a researcher at the Geoenvironmental Research Department of the Institute of Geography and Spatial Organization, Polish Academy of Sciences, and a doctoral student at the GeoPlanet Doctoral School since 2021. She holds a master’s degree in geography from Jagiellonian University, specializing in biogeomorphology and river renaturalization, and a bachelor’s degree in physical geography. Education: MA in Geography (Jagiellonian University, 2019), BA in Geography (Jagiellonian University, 2017) Current Role: Doctoral Researcher focusing on European beaver impacts on river ecosystems Her research spans geomorphology, biogeomorphology, and urban ecology, with a focus on beaver-driven renaturalization processes and herpetofauna conservation. Her projects include statutory research on mountainous environments under climate change, national studies on beaver activity in the Western Carpathians, and external work on social conflicts in protected areas. Joanna’s publications (2022–2024) highlight beaver-induced hydrological changes, amphibian habitat preservation, and public perceptions of reintroduction programs. She has presented at international conferences such as the EGU General Assembly and the Free Flow Conference, emphasizing interdisciplinary approaches to ecological restoration and data digitization. Her work intersects empirical field studies with policy analysis, addressing challenges in integrating conservation into urban development and transboundary river management.

• Management and Quality Studies
• Econometrics
• Data Analysis
• +۶ مورد دیگر

Magdalena Panasiuk-Kwiatek is a Researcher at the Department of Information Systems and Logistics within the Faculty of Economics at Maria Curie-Skłodowska University (UMCS) in Lublin, Poland. She holds a Master's degree in Finance and Accounting and has postgraduate qualifications in Pedagogy and Eurozone Functioning Mechanisms . Education: M.A. in Finance and Accounting, UMCS Postgraduate in Pedagogy, University of Management and Administration in Zamość Postgraduate in Eurozone Mechanisms, UMCS Her research spans Management and Quality Studies , Econometrics , Data Analysis , and Public-Private Partnerships . Recent work focuses on plastic waste management in the EU , IT systems in healthcare , and innovative public procurement tools . She has authored 21 publications and participated in interdisciplinary educational projects, including designing computer science lesson plans and business simulations (e.g., REVAS, Marketplace). Her technical expertise includes MS Office , IBM SPSS , Tableau , and Power BI . Professional roles include serving as Year Supervisor for UMCS students (2016-2019: Business Analytics; 2019-2022: Finance and Accounting; 2022-2025: Finance and Accounting). She contributes to the Analysis and Development Center (GGGAR) at UMCS.

Jerzy Stefanowskiمشاهده پروفایل

استاد

• Machine Learning
• Data Mining
• Knowledge Discovery
• +۹ مورد دیگر

Jerzy Stefanowski is a Full Professor at the Institute of Computing Science, Poznan University of Technology. He specializes in Machine Learning, Data Mining, and Knowledge Discovery, with a focus on imbalanced data, data streams, and explainable AI. His research addresses challenges in classifier learning from skewed datasets and has led to contributions like the BRACID algorithm. He has supervised multiple PhD students and holds grants such as the NCN-funded project on imbalanced data (2014–2017). A corresponding member of the Polish Academy of Sciences and Editor-in-Chief of the journal Foundations of Computing and Decision Sciences , he has organized numerous conferences and workshops in AI and data mining. Education: M.Sc./Eng. in Control Engineering (1987) Ph.D. in Computer Science (1994) Habilitation Thesis (2001) Research Interests: Machine learning, data streams, imbalanced classification, rough sets, medical informatics, and interpretable AI. His work emphasizes overcoming algorithmic biases in imbalanced datasets and developing robust classification strategies. Awards: Includes recognition from the Polish Information Processing Society, Foundation for Polish Science, and the Polish Academy of Sciences. He has also received medals and grants from national educational bodies. Grants: Led projects such as Learning Classifiers from Imbalanced and Evolving Data (NCN, 2014–2017) and Algorithms Transforming Data Representation for Machine Learning Systems (KBN, 2004–2007). Labs/Teams: Leads the Machine Learning Group at Poznan University of Technology and chairs the Scientific Council of the Institute of Computer Science, Polish Academy of Sciences.

Marcin Paszkutaمشاهده پروفایل

مربی

• Climate Science
• Satellite Remote Sensing
• Geophysics
• +۳ مورد دیگر

Marcin Paszkuta is a Tutor at the Institute of Oceanography, University of Gdańsk, specializing in satellite remote sensing of Earth's climate systems and Baltic Sea environmental dynamics. He holds a doctorate from Sorbonne University in Paris and has been affiliated with the University of Gdańsk since 2006. His research focuses on radiation budgets, cloud cover patterns, and geophysical processes in the Baltic region, utilizing the SatBałtyk satellite system. He integrates artificial intelligence into educational frameworks to enhance student skills and academic competencies. Affiliations : Faculty of Oceanography and Geography, University of Gdańsk Key Projects : SatBałtyk environmental monitoring system His research interests combine climate science with innovative pedagogy, addressing both environmental data analysis and AI-driven educational methodologies. He collaborates with students on coursework in mathematics, physics, and specialized topics, emphasizing skill development through tutorials since 2015. Recent studies highlight trends in Baltic Sea radiation budgets, cloud dynamics, and the application of AI in academia. His work bridges geophysical observations with technological advancements in education and environmental monitoring.

Byung Suk Leeمشاهده پروفایل

استاد مهمان

• Data Management
• Data Mining
• Data Science
• +۹ مورد دیگر

Byung Suk Lee is a Visiting Professor of Computer Science at the University of Vermont. He holds a B.S. from Seoul National University, an M.S. from KAIST, and a Ph.D. from Stanford University. His research focuses on data and database management, data mining, and machine learning, with applications in healthcare, transportation, and environmental systems. Education: B.S., Seoul National University M.S., KAIST Ph.D., Stanford University Lee has led or co-led nearly 20 research projects and authored over 80 peer-reviewed publications. His work emphasizes practical applications in citizen science and smart infrastructure. He actively contributes to academic communities as an organizer and committee member for international conferences. His recent research explores data-driven solutions for public health crises, such as a literature-based knowledge graph framework for predicting combination therapeutics during the COVID-19 pandemic. No specific awards or grants are listed in the provided text.

Marcin Szmydtمشاهده پروفایل

پژوهشگر

• Artificial Intelligence
• Digital Transformation
• Business Informatics
• +۵ مورد دیگر

Poznań University of Economics and Business's Department of Information Systems focuses on Artificial Intelligence , Digital Transformation , and Business Informatics . While Marcin Szmydt's name does not appear in the provided texts, the department's work includes analyzing the impact of global crises on Maritime Traffic , Big Data applications, and Generative AI in Data Analysis . Research Trends : Szmydt's publications (as per Google Scholar) emphasize Artificial Intelligence , Business Informatics , and Data Analysis , with sub-fields like Maritime Logistics , Recommender Systems , and Customer Behavior Prediction . His work spans crises impact analysis, mobile application personalization, and banking technology.

Andrzej Kasprzakمشاهده پروفایل

استاد

• Machine Learning
• Computer Science
• Network Optimization
• +۳ مورد دیگر

Professor Andrzej Kasprzak is a faculty member at the Faculty of Information and Communication Technology, Wrocław University of Science and Technology, serving as Head of the Department of Systems and Computer Networks. His research spans machine learning, network optimization, and data stream processing, with applications in telecommunications, healthcare, and industrial systems. University: Wrocław University of Science and Technology School: Faculty of Information and Communication Technology Department: Department of Systems and Computer Networks Email: andrzej.kasprzak@pwr.edu.pl Kasprzak’s research focuses on integrating machine learning with network optimization, particularly in elastic optical networks and data stream environments. His work addresses challenges in multi-agent pathfinding, fake news detection, and 3D printing automation, emphasizing practical experimentation systems. Recent publications highlight trends in ensemble learning for real-time data streams, domain adaptation in AI systems, and innovative optimization algorithms for network traffic and scheduling problems. These contributions bridge theoretical advancements with industrial applications. As Head of Department, Kasprzak leads initiatives in systems and computer networks, fostering interdisciplinary collaboration in artificial intelligence and telecommunications. His career reflects a commitment to advancing computational methodologies in complex environments.