Fuzzy-Rough Sets Professors and Supervisors

Andrzej Żołnierekمشاهده پروفایل

پژوهشگر

Wrocław University of Science and TechnologyPoland

Dr. Andrzej Żołnierek 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 office address is Janiszewskiego 11/17, 50-372 Wrocław (Building C-3, Room 111). He maintains regular office hours across odd/even weeks for student consultations. Academic affiliation: Faculty of Information and Communication Technology Research focus: Hybrid AI systems, medical diagnostics, and Polish language processing Contact: andrzej.zolnierek@pwr.edu.pl | +48 71 320 2972 Dr. Żołnierek's research spans multiple interdisciplinary domains including biomedical engineering applications of AI systems, Polish language processing for speech recognition, and hybrid pattern recognition methodologies combining rough sets with fuzzy logic. His work addresses both technical implementation challenges and real-world healthcare applications. Recent publications demonstrate his focus on sequential medical diagnosis frameworks (2016), neural network control systems (2014), and Polish language modeling (2013). His technical expertise includes machine learning algorithms, signal processing techniques, and rule-based decision systems. As a frequent contributor to international conferences like CORES, HAIS, and ISCBI, he has published extensively on pattern recognition (2013, 2016), medical diagnostics (2011, 2016), and computational linguistics (2011, 2013). His work often involves collaborative research with colleagues like Marcin Majak and Marek Kurzyński.

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Helga Naessensمشاهده پروفایل

دانشیار

Ghent UniversityBelgium

Helga Naessens serves as Associate Professor in the Department of Information Technology within the Faculty of Engineering and Architecture at Ghent University. She is an active researcher affiliated with the Internet Technology and Data Science Lab, where she conducts work at the intersection of theoretical computer science and practical information systems. Her research program spans two distinct but connected phases. Early in her career (1999-2002), she focused on foundational work in fuzzy logic, developing algorithms for T-transitive closures, rational similarity measures, and fuzzy preorder relations. This theoretical work established mathematical frameworks that later enabled her applied research. From 2008 onward, she shifted toward practical applications in academic information systems, investigating research paper similarity metrics, metadata utilization, and personalized recommendation systems for scholarly resources. Analysis of her publication trajectory reveals a clear evolution from pure mathematics to applied computer science, with her recent work (2010-2013) demonstrating sophisticated integration of language models, semi-structured data, and content-based filtering techniques for academic search systems. Her research consistently bridges theoretical rigor with practical implementation challenges in scholarly communication. Dr. Naessens has maintained significant collaborative relationships throughout her career, most notably with Hans De Meyer and Bernard De Baets (7 publications each), Chris Cornelis (6 publications), and Germán Hurtado Martín (6 publications). She successfully supervised Germán Hurtado Martín's 2013 PhD dissertation on intelligent information filtering methods. Within the Internet Technology and Data Science Lab, she contributes to research initiatives focused on data-driven approaches to information management, with particular emphasis on improving how researchers discover and interact with academic literature through advanced computational techniques.

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Tuğrul TAŞCIمشاهده پروفایل

استادیار

Sakarya UniversityTurkey

Tuğrul TAŞCI serves as an Assistant Professor in the Department of Information Systems Engineering at Sakarya University's Faculty of Computer and Information Sciences, where he has maintained continuous academic service since 2001. His career progression includes Research Assistant positions across multiple university units before advancing to his current faculty role in 2016. His academic credentials include: Doctorate in Computer and Information Engineering (2014) from Sakarya University Institute of Science, thesis: Real-Time Motion Tracking with Particle Filtering Based on Data Fusing Master's degree in Computer and Information Engineering (2004) with thesis: Design of an Integrated Web-Based Distance Education System Bachelor's degree in Computer Engineering (2001) with thesis: Course Scheduling with Genetic Algorithms Dr. TAŞCI's research centers on Artificial Intelligence applications, particularly Natural Language Processing for Arabic text and Computer Vision . His work integrates particle filtering , data fusion , and optimization algorithms (e.g., Artificial Bee Colony, Firefly) to solve problems in text summarization, motion tracking, and image processing. Recent publications demonstrate expansion into deep learning for industrial defect detection and time series analysis. Analysis of his 2019-2024 publications reveals three dominant research trajectories: (1) Arabic NLP with focus on extractive summarization using PageRank and word embeddings, (2) Computer vision systems for motion tracking and text detection leveraging particle filters and curvature features, and (3) Hybrid optimization techniques applied to diverse domains from emergency management to customer churn prediction. Current academic advising activities and research grant details are not publicly documented in available sources. Similarly, no institutional laboratories or research teams are explicitly associated with his profile in the provided materials.

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TUĞBA HAN ŞİMŞEKLER DİZMANمشاهده پروفایل

دانشیار

Gaziantep UniversityTurkey

Associate Professor Tuğba Han Şimşekler Dizman is affiliated with Gaziantep University as a faculty member in the Faculty of Education , specifically the Department of Mathematics and Science Education . She holds a PhD in Mathematics from Selçuk University (2014) and has authored 23 articles, primarily focusing on Mathematics Education , Topology , and Fuzzy Soft Topological Spaces . Her research bridges mathematical theory with applications in Medical Diagnosis and STEM Education . Doctorate: Mathematics, Selçuk University (2010-2014) Master’s: Mathematics, Selçuk University (2007-2009) Bachelor’s: Mathematics, Selçuk University (2003-2007) Her recent work includes 2025 articles on Optimal Parameter Identification and Algebraic Thinking Levels , alongside 2023 research comparing Turkish and Singaporean preschool mathematics curricula. She has supervised 10 master’s theses on topics like geometric reasoning, algebraic thinking, and curriculum analysis. Notable projects include TÜBİTAK-funded research (2023-2024) on AI-supported fuzzy logic for real-world problems and international collaborations like STREAM It Up (2021-2022). Her teaching portfolio spans courses in Analysis , Abstract Mathematics , and Introduction to Metric Spaces , reflecting her expertise in foundational and advanced mathematics.

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Archie Singh Khumanمشاهده پروفایل

مدرس ارشد

De Montfort UniversityUnited Kingdom

Dr. Archie Singh Khuman serves as Associate Head of Education and Senior Lecturer at De Montfort University's School of Computer Science and Informatics. An award-winning academic and proud DMU alumnus (BSc 2009, MSc 2011, PhD 2017), he specializes in Artificial Intelligence, Computational Intelligence, and Uncertainty Modelling with extensive leadership in curriculum development and Universal Design for Learning. His educational background demonstrates deep institutional commitment: PhD in Computer Science (2017, De Montfort University) MSc in Intelligent Systems (2011, De Montfort University) BSc (Hons) in Computer Science (2009, De Montfort University) Dr. Khuman's research pioneers hybrid uncertainty frameworks, notably the R-fuzzy grey analysis framework (RfGAf), bridging Grey Theory, Fuzzy Logic, and Rough Sets. His work focuses on quantifying perception-based uncertainty for applications in healthcare diagnostics, robotic swarm intelligence, and risk assessment systems, emphasizing real-world implementation through industry partnerships. His publication trajectory reveals increasing interdisciplinary convergence, particularly in healthcare AI applications since 2021. Recent outputs integrate Grey-Fuzzy methodologies for medical diagnostics (diabetes, heart disease), sentiment analysis of pandemic communications, and adaptive systems in automotive/industrial contexts, demonstrating strong translation from theoretical foundations to societal impact. Major recognitions include: Five consecutive Students' Choice Teaching Awards (2018-2024) De Montfort Teacher Fellowship (2022) Senior Fellow of the Higher Education Academy (2022) Leverhulme Trust-funded international Grey Systems network (£124,997) Best Paper Award at Grey Systems and Uncertainty Analysis (2016) As academic lead for the Data Analytics Project, he mentored students in developing machine learning solutions that generated £2.5m savings for retail partners. His grant portfolio includes Royal Society funding for IoT-based scheduling (£12,000) and leadership of the Race Equality Network. Current initiatives focus on transnational education partnerships and SI-PASS peer learning programs. Dr. Khuman co-leads DMU's Institute of Artificial Intelligence research group and serves as School Governor for Inglehurst Junior School, maintaining active collaborations with institutions in China, Canada, Romania, and Spain through the International Network on Grey Systems.

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Oliver Momčilovićمشاهده پروفایل

استاد

University of Business AcademySerbia

Oliver Momčilović serves as Full Professor and Vice-Dean for Teaching at the University of Economics Academy in Novi Sad, Faculty of Applied Management, Economics and Finance in Belgrade. His academic career spans multiple Serbian institutions including UNION Nikola Tesla University and Megatrend University, with visiting professorships at Romanian and Croatian institutions. Education: Doctorate in Industrial Engineering and Engineering Management, University of Kragujevac (2015) Doctorate in Management and Business, University of Economics Academy in Novi Sad (2008) Master's in Development Management, University of Novi Sad (2003) Specialization in Development Management, University of Novi Sad (2000) Bachelor's in Development Management, University of Novi Sad (1998) Professor Momčilović's research bridges management science with engineering applications, focusing on decision support systems, sustainability in business operations, and organizational change. His work demonstrates particular strength in applying mathematical models like DEMATEL and rough set theory to real-world management problems across energy, manufacturing, and educational sectors. Recent publications show increasing emphasis on sustainable business practices and digital transformation. His publication analysis reveals strong interdisciplinary connections between engineering management and business strategy, with consistent contributions to both theoretical frameworks and practical applications. The research trajectory shows evolving focus from technical management systems toward broader sustainability considerations and human resource dimensions in business excellence. Project Leadership: Principal investigator in EU-funded cross-border cooperation projects between Serbia and Romania Coordinator of USAID-funded municipal development projects in Žabari municipality Researcher in Ministry of Education-funded projects on water resource management and IT applications Participant in aircraft design management projects with international universities Professor Momčilović maintains active engagement with international academic networks through Lehigh University's Iacocca Institute and European training programs, while leading institutional initiatives in teaching innovation and professional development at his home faculty.

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