جست‌وجوی استاد و پژوهشگر

• Game Theory
• Decision Making
• Social Network Analysis
• +۷ مورد دیگر

Katarina Kostelić, Ph.D., serves as an Assistant Professor at the Faculty of Informatics in Pula, part of Juraj Dobrila University of Pula. She earned her doctorate in 2017 and maintains an active role in both undergraduate and graduate education, teaching courses including Social Network Analysis, Quantitative Methods of Business Decision Making, Operations Research, Statistics, and Business Analytics. Her office is located at room 13 (Negrijeva ulica 6; university campus). Dr. Kostelić's research spans multiple interconnected domains, with a strong emphasis on game theory applications in decision-making processes, social network analysis, and cybersecurity. Her work frequently examines how awareness (or lack thereof) influences strategic interactions, with particular attention to emotional intelligence in organizational contexts. She has made significant contributions to understanding business networks, tourism economics, and statistical methodologies. Analysis of her recent publications reveals a clear trajectory toward increasingly complex applications of game theory in cybersecurity contexts, alongside continued exploration of social networks in tourism and business environments. Her research demonstrates interdisciplinary reach, connecting computer science, economics, psychology, and management studies. The integration of neutrosophic sets in satisfaction measurement and the application of TOPSIS frameworks to cybersecurity risk assessment highlight her methodological innovation. Dr. Kostelić serves in multiple editorial capacities, including Managing Editor of Applied Sciences and Business Economics, Member of the Editorial Board of Journal of Interdisciplinary Sciences, and Member of the Editorial Team for Symmetry. She has also contributed to the popularization of science through accessible explanations of strategic situations, game theory applications in cybersecurity, and business network dynamics. Her research leadership is evident through projects including 'Analysis of social networks in Croatian tourism' (2019-2022), 'Role of emotions in strategic decision-making' (2019-2023), and contributions to international collaborations like MEGASFORA and SMART INNO. Dr. Kostelić has also developed educational resources, most notably her 2024 publication 'Introduction to R and RStudio,' supporting statistical education.

Rens Bodمشاهده پروفایل

استاد

• History of Humanities
• Digital Humanities
• Computational Linguistics
• +۵ مورد دیگر

Rens Bod is Professor of Digital Humanities and History of Humanities at the University of Amsterdam, where he is also Co-director of Amsterdam's Vossius Center for the History of Humanities and Sciences. His academic work bridges computational linguistics, digital humanities, and the global history of knowledge. His research focuses on pattern recognition across different knowledge domains throughout human history. Bod has pioneered the field of history of humanities through his influential books including A New History of the Humanities (2013) and the groundbreaking World of Patterns: A Global History of Knowledge (2022), which examines knowledge development across five continents over 40,000 years. Bod's recent publications show a continued focus on global perspectives in humanities, with particular attention to African intellectual traditions and questions of diversity in the field. His 2024 publications on the Classics of the Humanities in Africa represent significant contributions to decolonizing humanities scholarship. His work demonstrates consistent interdisciplinary engagement, moving fluidly between computational linguistics, musicology, history of science, and philosophy. The publication timeline shows sustained scholarly productivity from the late 1990s through the present, with increasing focus on global history of knowledge in recent years. Bod has been instrumental in establishing the history of humanities as a legitimate academic field, organizing the influential 'Making of the Humanities' conference series and editing the resulting volumes that have shaped the field's development. His research methodology combines traditional historical scholarship with digital humanities approaches, demonstrating how computational methods can reveal patterns in large-scale historical data that might otherwise remain unnoticed. This interdisciplinary approach reflects his fundamental argument that pattern-seeking unites diverse intellectual traditions across time and space.

Petr Hájekمشاهده پروفایل

استاد

• Machine Learning
• Neural Networks
• Fuzzy Logic
• +۷ مورد دیگر

Petr Hájek is a Professor at the University of Pardubice in the Institute of System Engineering and Informatics, Czech Republic. With 236 publications, 71,463 reads, and 5,595 citations, he has established himself as a prominent researcher in computational intelligence and machine learning applications. His research interests span multiple domains of computational intelligence, with particular focus on: Machine learning applications in financial forecasting and risk management Neural networks and fuzzy logic systems for time series prediction Sentiment analysis for financial markets and social media Fraud detection and fake news identification systems Cryptocurrency price forecasting and market analysis ESG analytics and sustainable finance applications Analysis of his recent publications (2023-2025) reveals an expanding research scope that increasingly integrates sustainability considerations with financial technology. His work demonstrates sophisticated methodological approaches, frequently employing hybrid neural network architectures, ensemble learning techniques, and advanced text mining methods. Professor Hájek's research shows strong international collaboration patterns with scholars across Europe, Asia, and North America. His scholarly contributions have focused on developing practical AI solutions for complex financial problems, with particular attention to handling class imbalance issues in financial datasets and creating interpretable models for financial decision-making. Professor Hájek maintains an active research program with consistent publication output across top venues in computational intelligence and financial technology. His work bridges theoretical advances in machine learning with practical applications in finance, demonstrating both academic rigor and real-world relevance.

• Computer Software
• Programming Languages
• Green Computing
• +۳ مورد دیگر

Dr. Lecturer İbrahim ŞANLIALP is a faculty member at the Faculty of Engineering and Architecture, Ahi Evran University, specializing in Computer Hardware and Software Engineering. He holds a Ph.D. (2022) and M.Sc. (2015) in Computer Engineering from Süleyman Demirel University, alongside a B.Sc. in Electronics and Computer Education (2010). Education: Ph.D. in Computer Engineering (Süleyman Demirel University, 2015-2022) M.Sc. in Computer Engineering (Süleyman Demirel University, 2012-2015) B.Sc. in Computer Engineering (Süleyman Demirel University, 2005-2010) Diploma in Electronics and Computer Education (Süleyman Demirel University, 2005-2010) His research focuses on Computer Software and Programming Languages , with recent studies analyzing energy efficiency in code refactoring, landslide prediction using statistical methods, and machine learning applications in public health. His work spans green computing , geospatial analysis , and AI-driven classification systems. Dr. Şanlıalp has contributed to 9 publications, including 2 journal articles (SCI-Exp, TR Dizin) and 7 conference papers. His projects include "3D Environment Path-Finding Algorithms for UAVs" (2025-2026) and "Grid-Based Path Planning Simulation" (2024-2025) as principal investigator. Metrics highlight 26 total citations (Google Scholar), h-index of 1, and active collaborations with researchers from Süleyman Demirel University, Ankara Yıldırım Beyazıt University, and Niğde Ömer Halisdemir University. His teaching portfolio includes courses like "Game Programming", "Computer Concepts", and "Cybercrime" since 2022.

• Database Systems
• Data Warehousing
• OLAP Analysis
• +۳ مورد دیگر

Professor Zbyszko Królikowski is a faculty member at Poznań University of Technology, where he works in the Faculty of Computer Science and Telecommunications, specifically in the Institute of Computer Science. He holds the academic title of Professor (indicated by "prof. dr hab. inż.") and has been actively contributing to the field of computer science, particularly in database systems and data warehousing. His scientific work spans multiple disciplines, with 75% focus on Computer and Information Sciences and 25% on Information and Communication Technology. Professor Królikowski has established himself as an expert in data warehousing, having authored a comprehensive monograph titled "Data warehouses: logical and physical data structures" published in 2007. His research interests primarily revolve around database systems, with specific focus on: Data warehousing and OLAP analysis Logical and physical data structures for databases Sequential data analysis Materialized views and query optimization Database performance evaluation Evolution of data warehouse systems Professor Królikowski has maintained an active research profile with publications spanning nearly two decades, from the early 2000s to 2021. His work shows a consistent focus on database technologies, evolving from traditional relational database systems to more contemporary approaches including in-memory architectures and graph databases. Analysis of his publication trends reveals a progression from theoretical database modeling to practical applications in production planning and modern database technologies. He has contributed to the academic community not only through his publications but also by supervising doctoral research. Notably, he supervised Mikołaj Morzy's dissertation on "Advanced database structures supporting effective association discovery" in 2004 and has served as a reviewer for numerous other doctoral dissertations in related fields. Professor Królikowski has collaborated extensively with other researchers in the database community, particularly with scholars from Poznań University of Technology including Tadeusz Morzy, Bartosz Bębel, and Robert Wrembel. These collaborations have resulted in numerous joint publications that have contributed significantly to the field of data warehousing and database systems.

Marenglen Bibaمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Data Mining
• +۶ مورد دیگر

Marenglen Biba is a Full Professor and Dean of the Faculty of Engineering and Architecture at the University of New York Tirana, where he also chairs the Department of Computer Science. His academic journey includes a Ph.D. in Computer Science from the University of Bari, Italy (2009), and a Laurea degree cum laude from the same institution (2004). His research spans: Core AI/ML : Machine learning algorithms, statistical relational learning, pattern recognition Language technologies : NLP for Albanian, stemming, morphological analysis Applied domains : Computational biology, social network mining, emotion detection Recent publications (2018–2021) focus on NLP for low-resource languages, deep learning surveys, and emotion-aware data mining. Award highlights include: ICT Academic of the Year 2012 (Albania) Best Paper Award at ILP 2008 Multiple University of Bari research grants He has led EU-funded projects like ADRIATinn (€4.6M budget) and maintains collaborations with the University of Washington, University of Bari, and Asian universities. Administrative leadership includes decade-long oversight of UNYT's Computer Science department and current deanship.

Erik Schaffernichtمشاهده پروفایل

مدرس ارشد

• Robotics
• Sensor Systems
• Machine Learning
• +۶ مورد دیگر

Erik Schaffernicht serves as a Senior Lecturer in the Department of Natural Sciences and Technology at Örebro University's School of Science and Technology. His research is primarily conducted through the Center for Applied Autonomous Sensor Systems (AASS) where he leads work in the Adaptive and Interpretable Learning Systems and Robot Navigation and Perception research groups. Dr. Schaffernicht's research spans multiple areas in robotics and artificial intelligence, with particular expertise in sensor systems, behavior trees, and gas distribution mapping. His work bridges theoretical computer science with practical applications in autonomous systems, environmental monitoring, and human-robot interaction. His research often involves developing novel algorithms for robot perception, control, and decision-making in complex environments. His recent publications demonstrate a strong focus on behavior trees for robot control, gas distribution mapping techniques, and applications of machine learning in robotics. The research shows increasing sophistication in using deep learning approaches for environmental sensing and robot navigation, with applications ranging from industrial safety to healthcare monitoring. Dr. Schaffernicht maintains an active research agenda with numerous publications in top robotics and AI venues, including IEEE Robotics and Automation Letters, Robotics and Autonomous Systems, and various IEEE conference proceedings. His work shows consistent collaboration with researchers across Europe, particularly with the AASS research center at Örebro University. His research projects include both ongoing work on automatic cognitive screening tests using eye-tracking technology and completed projects such as AIR (Action and Intention Recognition), RAISE (Robotic System for Air Quality Assessment), and SmokeBot (Mobile Robots for Disaster Site Inspection).

Stuart Jonathan Russellمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Probabilistic Reasoning
• +۷ مورد دیگر

Stuart Jonathan Russell is a Distinguished Professor of Computer Science, Cognitive Science, and Computational Precision Health at the University of California, Berkeley. He holds the Smith-Zadeh Chair in Engineering and is also a Professor of Computational Precision Health at the University of California, San Francisco. Russell is the founder and leader of the Center for Human-Compatible Artificial Intelligence (CHAI) at UC Berkeley and serves as an Honorary Fellow of Wadham College, Oxford. His academic journey began with a B.A. in Physics from the University of Oxford, followed by a Ph.D. in Computer Science from Stanford University. Throughout his distinguished career, Russell has received numerous prestigious honors including the IJCAI Computers and Thought Award (1995), IJCAI Award for Research Excellence (2022), Fellow of the Royal Society (2025), and Member of the National Academy of Engineering (2025). Russell's research spans multiple domains within artificial intelligence, with a recent focus on ensuring AI systems remain beneficial to humanity. His work includes significant contributions to machine learning, probabilistic reasoning, knowledge representation, planning, real-time decision making, and inverse reinforcement learning. In recent years, his research has increasingly focused on AI safety, value alignment, and developing frameworks for human-compatible AI systems that maintain human control as AI capabilities advance. His publication record shows a clear trend toward addressing the long-term challenges of AI development, particularly the control problem and value alignment. The research spans theoretical foundations of AI, practical applications in robotics and decision making, and critical examinations of the societal implications of increasingly capable AI systems. Russell's work has evolved from foundational AI research to increasingly focus on the alignment problem and mechanisms for ensuring AI systems remain beneficial. Russell has received numerous scientific awards recognizing his contributions to the field: IJCAI Computers and Thought Award (1995) AAAI Fellow (1997) ACM Fellow (2003) AAAS Fellow (2011) Blaise Pascal Chair (2012) Reith Lectures (2021) Officer of the Order of the British Empire (OBE) (2021) Fellow of the Royal Society (2025) Member of the National Academy of Engineering (2025) Russell has advised numerous doctoral students including Marie desJardins, Eric Xing, and Shlomo Zilberstein, and has mentored many postdoctoral researchers who have become leaders in the field. His research has been supported by various grants from organizations including the National Science Foundation, Defense Advanced Research Projects Agency, and other funding bodies focused on advancing AI research with careful consideration of safety and societal impact. He has been particularly active in securing funding for research on human-compatible AI and value alignment. He founded and leads the Center for Human-Compatible Artificial Intelligence (CHAI), which brings together researchers from multiple disciplines to address the challenge of creating AI systems that reliably do what humans want them to do. The center collaborates with other research groups including the Berkeley Artificial Intelligence Research (BAIR) lab, the Kavli Center for Ethics, Science, and the Public (KCESP), and the Institute for Cognitive and Brain Sciences (ICBS), creating a rich interdisciplinary environment for addressing the challenges of AI safety and human compatibility.

Charles Louis Feffermanمشاهده پروفایل

استاد

• Mathematical Analysis
• Harmonic Analysis
• Partial Differential Equations
• +۷ مورد دیگر

Charles Louis Fefferman is the Herbert E. Jones, Jr. '43 University Professor of Mathematics at Princeton University, where he has held a faculty position since 1977. Previously, he served as a full professor at the University of Chicago from 1971 to 1977, becoming the youngest full professor in U.S. history at age 22. His academic journey began at the University of Maryland, College Park, where he earned his undergraduate degree at 17 before completing his PhD at Princeton under Elias Stein at age 20. Fefferman's research spans mathematical analysis with particular emphasis on harmonic analysis, partial differential equations, and complex analysis. His groundbreaking work on singular integrals, Hardy spaces, and the Bergman kernel revolutionized these fields, leading to his Fields Medal in 1978. More recently, he has made significant contributions to Whitney extension problems, fluid dynamics singularity formation, and mathematical aspects of topological materials. His publication record shows remarkable consistency over five decades, with recent work (2019-2023) focusing on manifold learning, smooth function interpolation, and quantum systems. These publications demonstrate both theoretical depth and increasing connections to data science applications, maintaining his position at the forefront of mathematical research. Fefferman's scientific honors form an exceptional constellation of recognition: Fields Medal (1978) Alan T. Waterman Award (1976, inaugural recipient) Salem Prize (1971) Bergman Prize (1992) Bôcher Memorial Prize (2008) Wolf Prize in Mathematics (2017) BBVA Foundation Frontiers of Knowledge Award (2021) As an advisor, Fefferman has mentored numerous doctoral students who have become leaders in their fields, including Matei Machedon, Luis Seco, and Michael Christ. His research group continues to explore fundamental questions in analysis while developing mathematical frameworks for emerging applications in data science and quantum physics. Fefferman remains actively engaged in research, with publications through 2023 demonstrating his continued intellectual vitality and mathematical creativity.

Rüdiger Glaserمشاهده پروفایل

استاد

• Historical Climatology
• Climate Reconstruction
• Global Change
• +۵ مورد دیگر

Prof. Dr. Rüdiger Glaser holds the Chair of Physical Geography at the University of Freiburg within the Faculty of Environment and Natural Resources. His extensive academic career spans over three decades with significant contributions to climatic geography, particularly in historical climatology and climate change research. He maintains active roles in multiple research projects, editorial boards, and academic committees at both national and international levels. Glaser completed his geography studies at Julius-Maximilians-University in Würzburg (1981-1986) with minors in Botany and Administrative Law, plus additional credits in Geology, Sociology, Spanish, Statistics and IT. His academic progression includes: Diploma thesis on remote sensing with Landsat-5 Thematic Mapper (1986) Doctoral research on climate reconstruction for Mainfranken, Bauland, and Odenwald (1989) Habilitation with thesis on historical climatology in Central Europe since 1000 AD (1997) C3 Professorship at Heidelberg University (2001-2004) C4 Professorship at Freiburg (since 2004) His research focuses on historical climatology, including weather and climate reconstruction, climate extremes analysis, and social conceptualization of climate phenomena. Glaser has developed the Historical Climate Database Germany and conducts scale-related analyses of global change across different landscape zones. His environmental planning work addresses sustainability processes, Agenda 21 implementation, and assessment procedures like ecological footprint analysis. In e-Geography, he applies remote sensing techniques and develops e-learning modules for physical geography education. His regional expertise centers on Central Europe and North America, with particular attention to global change manifestations in these regions. His publication record shows a clear trend toward applied climate research with increasing focus on municipal climate adaptation, risk archetypes, and cross-border cooperation in the Upper Rhine region. Recent work integrates climate science with social dimensions, particularly examining how climate change impacts different demographic groups and economic sectors, with special attention to vulnerable populations like the elderly. Glaser's scientific recognition includes: Instructional Development Award from University of Freiburg (2014) Media Prize of the University of Freiburg (2004) Virtual Teaching Award from Baden-Württemberg (2003) Canadian Government Scholarship (2002) Election as full member of the German Academy of Regional Studies (2004) As an academic advisor, Glaser has supervised numerous doctoral and master's students whose research spans climate vulnerability assessment, energy efficiency, renewable energy potential, and urban climate adaptation. He serves on multiple examination boards and selection committees, including for the M.Sc. Geography of Global Change program. His current research is supported by diverse funding sources including EU INTERREG, DFG, and the German Federal Ministry for the Environment. Glaser leads research teams working on transnational climate adaptation projects like Clim'Ability Care and RiverDiv, which involve collaboration between German, French, and Swiss institutions. His work emphasizes practical applications of climate science for municipal decision-making and cross-border environmental management in the Upper Rhine region.

Tiziana Cianoمشاهده پروفایل

استادیار

• Artificial Intelligence
• Applied Mathematics
• Machine Learning
• +۷ مورد دیگر

Tiziana Ciano (born April 21, 1991) serves as a tenured Researcher and Assistant Professor at the Department of Economic and Political Sciences, University of Aosta Valley. She holds a PhD in Law and Economics & Doctoral Europaeus from Mediterranean University of Reggio Calabria & University of Portsmouth, and a Master's Degree in Economics obtained with highest honors. Her academic appointments include Contract Professor at DICEAM Department, Mediterranean University of Reggio Calabria, and membership in Decisions_Lab scientific laboratory. Dr. Ciano's research spans mathematical economics with strong AI applications: Artificial Intelligence and Applied Mathematics Machine Learning and Deep Learning for socio-economic systems Stochastic Programming and Multi-objective Optimization Dynamic Systems and Epidemic Modeling Decision Support Systems for tourism and finance Her recent publications reveal a consistent focus on applying advanced mathematical methods to portfolio optimization, pandemic dynamics, climate change sustainability, and tourist flow forecasting. She has developed tri-objective optimization models for financial decision-making and fuzzy fractional-order models for pandemic dynamics, demonstrating methodological innovation across multiple domains. Dr. Ciano has received multiple prestigious recognitions including the Best Poster Award at DySES2022 conference for her work on fake news sentiment analysis during pandemics, a Research Award for her paper on duopoly game analysis published in Symmetry, and the Anassilaos Giovani Ricerca Award under the patronage of the President of the Republic of Italy. She serves on editorial boards of high-impact journals including Mathematics (MDPI) Financial Mathematics section (Q1, IF 2.592), Applied Mathematical Sciences, and International Journal of Contemporary Mathematical Sciences. As Guest Editor, she has curated special issues on mathematical economics, differential games, and symmetry in machine learning algorithms. She regularly referees for Mathematical Problems in Engineering, Information Processing & Management, and Scientific Reports (NATURE). Dr. Ciano actively participates in Decisions_Lab research laboratory and leads multiple collaborative projects including MONTUR (Real-time Monitoring of Tourist Flows in Aosta Valley), MEC – Marketplace Ecosostenibile Calabria, and IUSTIT-IA. She has organized numerous international conferences including AMASES 2023, NUMTA2023, and special sessions on predictive analytics and machine learning applications in socio-economic systems.

Marius Călinمشاهده پروفایل

مدرس

• Soft Computing in Agricultural Sciences
• Decision Making under Uncertainty
• Decision Support Systems
• +۲ مورد دیگر

Marius Călin serves as a Lecturer in the Department of Exact Sciences at the Faculty of Horticulture, University of Agricultural Sciences and Veterinary Medicine of Iasi, Romania. His academic profile bridges computational science with agricultural applications through expertise in Information Technology, Applied Mathematics, and E-learning systems development. His research portfolio centers on five core domains: Soft Computing in Agricultural Sciences: Pioneering fuzzy logic applications for plant breeding and greenhouse management Decision Making under Uncertainty: Developing models for agricultural scenarios with incomplete data Decision Support Systems: Creating tools for land suitability assessment and resource optimization E-learning Applications: Designing specialized platforms for agricultural education Graph Databases: Implementing knowledge representation systems for agricultural data Analysis of his publication trajectory reveals an evolution from foundational fuzzy decision models (2000-2007) toward increasingly interdisciplinary work. Recent publications (2015-2022) demonstrate strong convergence between e-learning infrastructure development and agricultural informatics, particularly through Moodle-based systems for remote education during the pandemic and computational models for soil management. His work consistently emphasizes practical implementation of grid computing and soft computing techniques in agricultural contexts. Dr. Călin has secured significant research funding through seven major contracts, including leadership as USAMV Iasi responsible for the CEEX 1801 grid computing project (2006-2008) and contributions to sustainable soil management initiatives (ECOSEUMET, CNCSIS 738). His grant portfolio demonstrates sustained focus on translating computational research into agricultural solutions. Within the university ecosystem, he serves as Moodle platform administrator and coordinates Informatics discipline activities, fostering cross-departmental collaboration. His professional affiliations include ESNA (European Society for New Methods in Agricultural Research) and ROMAI (Romanian Society of Applied and Industrial Mathematics), reflecting his commitment to interdisciplinary scientific exchange.