جست‌وجوی استاد و پژوهشگر

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.

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.

Dariusz Jankowskiمشاهده پروفایل

پژوهشگر

• Machine Learning
• Data Stream Mining
• Data Stream Classification
• +۳ مورد دیگر

Dariusz Jankowski is a researcher at the Department of Systems and Computer Networks within the Faculty of Information and Communication Technology at Wrocław University of Science and Technology. His work focuses on machine learning, data stream mining, and big data analysis with applications in medical diagnostics and industrial processes. Email: dariusz.jankowski@pwr.edu.pl Office: Room P.2.9, Building C-16, Wrocław Office Hours: Tuesday 11-13, Thursday 13-15 Research interests include machine learning, data stream classification with concept drift, and big data analysis. He has applied these techniques to medical diagnosis (migraine) and industrial applications (dental milling, cotton textile industry). Recent publications focus on decision tree algorithms for data streams, random forest optimization with MapReduce, hyperspectral image segmentation, and ensemble classifier systems. His work spans both theoretical machine learning and practical implementations across diverse domains. Current affiliations include participation in academic conferences like IDEAL, CORES, and HAIS. While no awards are explicitly mentioned, his collaborative publications suggest active involvement in research networks.

• Limnology
• Hydrology
• Geographic Information Systems
• +۳ مورد دیگر

Dr. Maciej Markowski serves as an Adjunct Professor at the Faculty of Oceanography and Geography, University of Gdansk, with additional affiliation at the institution's GIS Center. His research focuses on freshwater ecosystems in Northern Poland, particularly the Tricity metropolitan area, employing Geographic Information Systems and remote sensing methodologies to analyze lake hydrology and ecological dynamics. His research portfolio centers on Limnology and Hydrology, with specialized expertise in lobelia lakes and post-glacial ponds. Key investigation areas include trophic state assessment, sediment resuspension mechanisms, anthropogenic pressure impacts, and climate change effects on freshwater systems. His methodological approach integrates geospatial analysis with hydrological modeling to address conservation challenges in vulnerable aquatic ecosystems. Analysis of his 15 most recent publications reveals consistent application of GIS techniques across diverse environmental contexts—from modeling wind-wave sediment dynamics in Tricity-area lakes to assessing atmospheric water exchange in river-lake systems. Notable research trends include increasing integration of satellite data for climate monitoring (2023-2024), persistent focus on Baltic coastal ecosystems, and interdisciplinary expansion into bioenergy conversion processes and aeronautical cartography applications. As an active member of the University of Gdansk's GIS Center, Dr. Markowski leverages advanced spatial analysis infrastructure to support regional environmental research. His work directly contributes to conservation strategies for Northern Poland's unique freshwater systems, particularly addressing threats from urbanization and climate variability in the Gdańsk metropolitan region.

Michał Woźniakمشاهده پروفایل

استاد

• machine learning
• pattern recognition
• classifier ensemble
• +۱۲ مورد دیگر

Michał Woźniak is a Professor at the Department of Systems and Computer Networks, Wrocław University of Science and Technology. He serves as Head of the Department and leads the Machine Learning Research Team. His research spans machine learning, pattern recognition, data stream mining, and imbalanced data classification. He actively supervises MSc theses and leads multiple research projects including those on continual learning, classifier ensembles, and fake news detection. Research Interests: Machine learning, particularly inductive and continual learning Pattern recognition and classifier ensembles Data stream mining under concept drift Imbalanced data classification Fake news and disinformation detection Cybersecurity and medical decision support His recent publications (2024–2025) focus on continual learning under concept drift, deep learning for image fusion and forgery detection, ensemble methods for imbalanced data, and AI applications in network optimization. These works reflect strong trends in adaptive machine learning, robust classification, and real-world AI deployment. Scientific Awards: BEST PAPER AWARD FOR CLVISION CVPR WORKSHOP 2024 He supervises numerous students and collaborates extensively on interdisciplinary projects. He has been involved in projects such as LM LDS (2021–2024), MOO (2020–2025), IDStream (2018–2022), and others. He is also a project manager and active in academic service, including membership in the Committee on Informatics of the Polish Academy of Sciences. His research group maintains a strong presence in AI and machine learning applications. Laboratory and Teams: He leads the Machine Learning Team and is involved in multiple research groups including the Advanced Data Analysis Methods Team and Metaheuristics Team . His lab focuses on developing robust, adaptive AI models for real-world challenges.

Paweł Zyblewskiمشاهده پروفایل

استادیار

• machine learning
• deep learning
• pattern recognition
• +۷ مورد دیگر

Dr. Paweł Zyblewski is an Assistant Professor in the Department of Computer Systems and Networks at the Faculty of Electronics, Wrocław University of Science and Technology. He is actively involved in research and teaching, contributing to teams such as the Machine Learning Team and Advanced Data Analysis Methods Team. His research is supported by projects including IDSTREAM and GEOM, focusing on advanced machine learning techniques for complex data analysis. Research Interests: His primary research areas include machine learning, deep learning, pattern recognition, classifier ensembles, dynamic classifier selection, data stream mining, handling imbalanced data, and multimodal data analysis. His work emphasizes robust and adaptive models for real-world decision-making tasks, especially under data drift and scarcity conditions. Publication Trends: His recent publications focus on dynamic ensemble methods for imbalanced data streams, geometric fusion of classifiers, and open-source tools for stream learning. These works reflect a strong trend toward practical, deployable machine learning systems that handle challenging data conditions with high accuracy and adaptability. Scientific Awards: Winner of the Secundus program (2020, 2021, 2022, 2024) Appointment to Academia Iuvenum (2024–2026) Minister of Education and Science Scholarship for Outstanding Young Scientists (2022) Polish Society for Artificial Intelligence Best Doctoral Thesis Award (2021) Best Paper Award at ICAISC 2021 Primus program award (2020–2021) Rector's Award for scientific achievements (2019/2020, 2020/2021, 2021/2022) Advising and Grants: He supervises diploma theses and is involved in significant research projects such as IDSTREAM and GEOM, which support his work in data stream classification and ensemble methods. These projects provide the foundation for his publications and student supervision. Labs and Teams: He is a key member of the Machine Learning Team and the Advanced Data Analysis Methods Team at Wrocław University of Science and Technology, where he collaborates on developing innovative optimization and classification techniques.

Szymon Wojciechowskiمشاهده پروفایل

استادیار

• Machine Learning
• Multi-Objective Optimization
• Imbalanced Data Classification
• +۴ مورد دیگر

Szymon Wojciechowski is an Assistant Professor at the Department of Computer Systems and Networks, Faculty of Electronics, Wrocław University of Science and Technology. He has been actively contributing to research and teaching since October 2019. He is a member of several research teams, including the Machine Learning Team, Metaheuristics Team, and Advanced Data Analysis Methods Team. Faculty of Electronics, Wrocław University of Science and Technology Department of Computer Systems and Networks Machine Learning Team Teaching Team Computer Networks Team His educational background includes a Bachelor of Engineering in Medical Information Systems (2018) and a Master of Engineering in Advanced Informatics and Control (2019), both from Wrocław University of Science and Technology. Dr. Wojciechowski's research focuses on machine learning , particularly in imbalanced data classification , multi-objective optimization , and data stream clustering . He explores data preprocessing techniques and evolutionary algorithms to enhance classifier performance in challenging decision-making scenarios. His work often integrates optimization methods into machine learning pipelines. The recent publications demonstrate a strong trend in applying evolutionary and hybrid AI techniques to solve problems in imbalanced data and network optimization . The research spans domains such as optical networking, semi-supervised clustering, and ensemble classification, indicating a cross-disciplinary approach combining computer networks and intelligent systems. He is actively involved in research projects including IDSTREAM and MOO , focusing on data stream analysis and multi-objective optimization. He completed a research internship at Universidad de Granada, Spain, where he worked on semi-supervised clustering with k-means. He supervises diploma theses and contributes to teaching in computer science and informatics. Dr. Wojciechowski is affiliated with the following research teams: Machine Learning Team Teaching Team Computer Networks Team Advanced Data Analysis Methods Team Metaheuristics Team