جست‌وجوی استاد و پژوهشگر

Francisco Chiclanaمشاهده پروفایل

استاد

• Fuzzy preference modelling
• Decision making with heterogeneous fuzzy information
• Decision support systems
• +۷ مورد دیگر

Professor Francisco Chiclana is a leading academic in Computational Intelligence and Decision Making at the School of Computer Science and Informatics, De Montfort University (UK). As founder of DIGITS (De Montfort University Interdisciplinary Group in Intelligent Transport Systems), he pioneered research in trust-driven decision frameworks and fuzzy systems. PhD and BSc in Mathematics from University of Granada Coordinated DMU's REF 2014 submission in Computer Science and Informatics Co-developed DMU's Doctoral Training Programme in Intelligent Systems His research focuses on fuzzy preference modelling , consensus reaching processes , and social network analysis for decision support systems. Recent work explores AI applications in trust propagation, power-asymmetric conflict resolution, and large-scale group decision frameworks. Key publications include 15+ peer-reviewed articles in journals like IEEE Transactions on Fuzzy Systems and Information Sciences , covering topics from type-2 fuzzy logic to Nash bargaining compensation mechanisms . His Greenfield-Chiclana Collapsing Defuzzifier won third prize at DMU's Creative Thinking Awards 2010. Outstanding PhD Award (University of Granada, 2000) Finalist in DMU-THE OSCAR AWARDS for Research Excellence (2012) As supervisor of 8+ current and completed PhD students, including Sarah Greenfield and Sergio Alonso Burgos, he has shaped next-generation researchers. His £145K EPSRC-funded project (2006-2009) extended fuzzy logic applications in consensus modelling.

Sherrilyn Roushمشاهده پروفایل

استاد

• Epistemology
• Formal Epistemology
• Knowledge
• +۷ مورد دیگر

Sherrilyn Roush is a Professor in the Department of Philosophy at University of California, Los Angeles (UCLA) , with a PhD in Philosophy from Harvard University (1999). She holds dual B.S. and B.A. degrees with highest distinction from Pennsylvania State University (1988). Her work spans Epistemology , Formal Epistemology , Scientific Method , and Bayesian Reasoning . Harvard University, PhD in Philosophy (1999) University of California, Los Angeles, Department of Philosophy Research interests include the epistemic value of knowledge, probabilistic reasoning in legal contexts, and the distinction between knowledge and understanding. She has extensively analyzed the role of statistical evidence in judicial verdicts, simulation methods in science, and epistemic self-doubt through a Bayesian framework. Her publications cover topics like the epistemic superiority of experiments over simulations, epistemic injustice in testimonial contexts, and evolutionary stable strategies for knowledge. While she has not been explicitly linked to scientific awards or formal student mentoring in the provided texts, her work intersects with medical epistemology through collaborations on self-knowledge in illness .

• Statistical Relational Learning
• Machine Learning
• Probabilistic Graphical Models
• +۵ مورد دیگر

Lise Getoor is a Professor in the Department of Computer Science at the University of California, Santa Cruz, within the Baskin School of Engineering. She previously held positions at the University of Maryland, College Park and has established herself as a leading researcher in statistical relational learning and neuro-symbolic artificial intelligence. Her research focuses on developing principled approaches to reasoning and learning with rich, relational data. She has made significant contributions to probabilistic soft logic, statistical relational learning, knowledge graph construction, and the integration of symbolic and neural approaches to AI. Her work bridges theoretical foundations with practical applications in areas including social network analysis, sustainable recommendations, cyberbullying detection, and fair machine learning systems. Analysis of her recent publications reveals a strong trend toward neuro-symbolic integration, with increasing focus on combining neural networks with logical reasoning frameworks. Her research demonstrates consistent innovation in developing scalable algorithms for structured prediction across diverse application domains while addressing critical issues of fairness and interpretability in AI systems. Professor Getoor has advised numerous PhD students who have become active contributors to the field, including Connor Pryor, Charles Dickens, Eriq Augustine, and Varun Embar. Her research has been supported by multiple grants from major funding agencies, though specific details aren't provided in the current data. She leads research in the Statistical Relational AI (StaRAI) Lab at UC Santa Cruz, where her team develops frameworks that combine logical reasoning with probabilistic modeling to address complex real-world problems requiring both structured knowledge and statistical learning.

Chris Cornelisمشاهده پروفایل

استاد

• Machine Learning
• Fuzzy Sets
• Rough Sets
• +۳ مورد دیگر

Chris Cornelis is a full-time Professor in fuzziness and uncertainty modelling at Ghent University's Department of Applied Mathematics, Computer Science and Statistics. His research integrates fuzzy logic and rough set theory to advance machine learning methodologies for complex data analysis. Education: M.Sc. in Computer Science, Ghent University (2000) Ph.D. in Computer Science, Ghent University (2004) Research Focus: Cornelis pioneers fuzzy-rough hybrid systems for uncertainty handling in machine learning. His work spans theoretical foundations (e.g., implication operators, granular approximations) and practical applications including emotion detection, medical diagnosis, and imbalanced data classification. Key innovations include FRNN-OWA classifiers and polar encoding for missing values, demonstrating exceptional versatility in bridging abstract mathematics with real-world AI challenges. Publication Trends: Recent work (2023-2025) reveals intensified exploration of topological data analysis (Mapper-based rough sets), advanced granular computing (disjoint/adjacent fuzzy granules), and ethical AI ("No Imputation Without Representation"). His research shows consistent progression from foundational fuzzy-rough theory toward multi-disciplinary applications while maintaining mathematical rigor, particularly in Choquet integration and quantifier-based frameworks. Scientific Awards: No specific awards were documented in the provided sources. Research Support: Cornelis has secured competitive funding including FWO postdoctoral mandates, a Ramón y Cajal contract at the University of Granada, and an FWO Odysseus Type II project at Ghent University. These grants enabled foundational work in fuzzy-rough set theory and its applications to complex data problems. Research Unit: He leads research within Ghent University's Computational Web Intelligence (CWI) unit, focusing on intelligent data analysis systems that leverage fuzzy-rough methodologies for web-scale information processing.

Corrado Loglisciمشاهده پروفایل

استادیار

• Temporal Data Mining
• Temporal Learning
• Textual Data Mining
• +۱۳ مورد دیگر

Corrado Loglisci is an Assistant Professor at the Department of Computer Science, University of Bari Aldo Moro, Italy. His research focuses on Temporal Data Mining , Machine Learning , and Quantum Computing , with applications in bioinformatics, medical informatics, and cybersecurity. He earned his Ph.D. in Computer Science with a thesis on temporal projection in longitudinal data. Research Highlights : Temporal Learning, Textual Data Mining, Quantum-Classical Hybrid Systems Collaborations : IRSTEA Research Institute (France), Aristotle University of Thessaloniki (Greece) His publications address dynamic network analysis , emotion detection in social media , and quantum-enhanced classification . He contributes to program committees and journal editorial work, including a special issue on Mining Complex Patterns in the Journal of Intelligent Information Systems . Notable contributions include the jKarma framework for change detection and studies on concept drift robustness in intrusion detection systems. His work spans European/National research projects, leveraging machine learning for tasks like mobile crowd sensing trustworthiness prediction (2020) and investor behavior analysis (2023-2025).

Sven Nethمشاهده پروفایل

استادیار

• Decision Theory
• Formal Epistemology
• Philosophy of Science
• +۳ مورد دیگر

Sven Neth is an Assistant Professor of Philosophy at the University of Pittsburgh, specializing in decision theory and formal epistemology. He holds a PhD from the University of California, Berkeley, where he was advised by Lara Buchak, John MacFarlane, and Wesley Holliday, and an undergraduate degree from Freie Universität Berlin. His research focuses on non-ideal decision-making agents, simplicity bias in probability assignments, and natural language reasoning. Notable topics include Goodman's New Riddle of Induction, social choice theory, and the ethics of artificial intelligence. His work bridges philosophy with formal methods, addressing foundational questions in epistemology, decision theory, and the philosophy of science. Education: PhD in Philosophy, UC Berkeley (Advisors: Lara Buchak, John MacFarlane, Wesley Holliday) Bachelor's Degree, Freie Universität Berlin His recent publications explore foundational issues in subjective probability, the limits of Solomonoff prediction, and rational attitudes toward information acquisition. He is also active in interdisciplinary collaborations, including work presented at NeurIPS workshops on decision-making in dynamic environments. Dr. Neth's current research questions include critiques of optimization-centric approaches and the philosophical implications of AI safety frameworks.

Greg Morrisettمشاهده پروفایل

استاد

• Programming Languages
• Software Security
• Formal Verification
• +۴ مورد دیگر

Greg Morrisett is the Jack and Rilla Neafsey Dean and Vice Provost of Cornell Tech, a graduate campus in New York City focusing on technology, business, law, and design. Previously, he served as Dean of Computing and Information Sciences at Cornell University and held the Allen B. Cutting Chair in Computer Science at Harvard University (2004–2015). He earned a B.S. from the University of Richmond and M.S./Ph.D. from Carnegie Mellon University. His research focuses on programming language technologies for secure, reliable software systems, including typed assembly language, proof-carrying code, and provably correct compilers. Notable projects include CertiCoq, GoNative, and CRASH-SAFE. He is an ACM Fellow and recipient of awards such as the Presidential Early Career Award and NSF Career Award. He has advised over 17 PhD students and mentored numerous postdocs. His work spans formal verification, cryptographic protocols, and secure systems design. Morrisett has served on editorial boards for journals like Communications of the ACM and advisory councils for NSF, DARPA, and Microsoft Research. Current research includes formal verification of cryptographic protocols with the INRIA Prosecco Team and advancing compiler correctness through projects like CertiCoq.

• Machine Learning
• Information Fusion
• Data Clustering
• +۳ مورد دیگر

Julien Ah-Pine is a lecturer at Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS) under Université Clermont Auvergne , with affiliations at Institut national polytechnique Clermont Auvergne and École des Mines de Saint-Étienne . He also holds a Researcher position at CNRS. Research Interests His work spans machine learning , information fusion , aggregation functions , and multi-criteria decision support , with a focus on complex data types like graphs , functional data , and multi-view datasets . Recent publications emphasize anomaly detection in spectral data streams , online learning , and interpretable AI for industrial applications. Selected Publications 2025 work on OnlineBootKNN introduces a novel framework for real-time spectral anomaly detection, while 2024 research explores multiple kernel methods in functional data classification. Earlier studies cover graph-based clustering , relational data mining , and linguistic network models for NLP tasks. Laboratory & Collaborations Works within LIMOS laboratory at Université Clermont Auvergne, collaborating with institutions like Mines Saint-Étienne and CNRS. Key partnerships include Nicolas Rojas Varela and Engelbert Mephu Nguifo on data stream analysis projects.

Salvatore Ramponeمشاهده پروفایل

دانشیار

• Machine Learning
• Cybersecurity
• Internet of Things (IoT)
• +۷ مورد دیگر

Salvatore Rampone is an Associate Professor at the Department of Law, Economics, Management and Quantitative Methods (DEMM) of Università degli Studi del Sannio (Unisannio). His research focuses on Machine Learning , Internet of Things (IoT) , and Cybersecurity , with applications in intrusion detection, bioinformatics, and financial systems. Research Interests : Privacy-preserving Machine Learning Hybrid Cloud-IoT Architectures Genetic Programming Neural Network Applications Data Processing in Distributed Environments Recent Publication Trends : His work spans federated learning for IoT security ( 2025 ), DNA splicing site prediction ( 2020 ), meningitis classification ( 2019 ), RFID-based traceability systems ( 2015 ), and geological data analysis using neural networks ( 1995-1996 ). Key technologies include Apache Spark , MLlib , and Wavelet Transform . Teaching Activities : He teaches courses like Applied Machine Learning and Principles of Computer Sciences across multiple degree programs including Statistical and Actuarial Sciences and Economics and Management .

Đorđević Markoمشاهده پروفایل

دانشیار

• Computational Biology
• Systems Biology
• Infectious Diseases
• +۷ مورد دیگر

Marko Djordjevic is an Associate Professor at the Faculty of Biology, University of Belgrade. His research spans computational biology of infectious diseases, bacterial immune systems (CRISPR/Cas and restriction-modification systems), and quantitative understanding of infection progression with applications to SARS-CoV-2 and computational physics of quark-gluon plasma. Diploma in Physics, Faculty of Physics, University of Belgrade, Serbia. PhD in Biophysics and Bioinformatics, Department of Physics, Columbia University, USA. Postdoctoral training at the Mathematical Biosciences Institute, Ohio State University, USA. Djordjevic's research focuses on nonlinear regulatory dynamics of bacterial immune systems, their role in horizontal gene transfer, and modeling infection progression under social mitigation measures. His secondary interest in computational physics examines quark-gluon plasma dynamics via high-p⊥ observables and tomography. His recent publications address CRISPR/Cas regulation, restriction-modification systems, and SARS-CoV-2 transmissibility drivers. Grants from the Serbian Ministry of Science, Science Fund of Serbia, EU Marie Curie IRG, and Swiss National Science Foundation support his work.

Carsten Schürmannمشاهده پروفایل

استاد

• Information Security
• Cryptographic Voting Protocols
• Security Analysis
• +۵ مورد دیگر

Carsten Schürmann is a Professor of Theoretical Computer Science at IT University of Copenhagen, where he serves as Center Manager for the Center for Information Security and Trust. His research spans information security, cryptographic voting protocols, identity management, and digital democracy, with significant contributions to security ceremonies and formal verification of protocols. Professor, Department of Computer Science Center Manager, Center for Information Security and Trust Principal Investigator for multiple DIREC projects through 2025 Active researcher with 64 publications and 20 projects listed His research focuses on the intersection of theoretical computer science and practical security challenges, particularly in voting systems and security ceremonies. Schürmann has developed formal methods for analyzing security protocols, with emphasis on human factors in security implementations and cryptographic voting systems. His work bridges logical frameworks with real-world security applications, addressing both technical and socio-technical aspects of security. Analysis of his recent publications reveals a strong emphasis on voting security, with multiple papers on risk-limiting audits, receipt-free voting, and election integrity. His work increasingly incorporates formal logical frameworks to verify security properties, while also addressing human factors in security ceremonies. The research spans theoretical foundations in linear logic to practical applications in election systems. As Principal Investigator, Schürmann leads several major projects funded by the Innovation Fund Denmark, including DIREC initiatives focused on Capacity Building, PhD School, Voting, and Entrepreneurship (2020-2025). He has also established working groups in Adversarial AI and Machine Learning. Organized workshops on Code Scanning (2014) and Verifying Security Protocols in Tamarin (2016) Active media commentator on security issues with 311 media appearances through 2025 Principal Investigator for 7 ongoing and 13 completed research projects Schürmann directs the Center for Information Security and Trust, which serves as a hub for interdisciplinary security research connecting theoretical computer science with practical security applications. His center focuses particularly on voting systems security and security ceremonies, bringing together researchers from multiple disciplines to address complex security challenges.

Wolfgang Freitagمشاهده پروفایل

استاد

• Philosophy of Language
• Philosophy of Mind
• Epistemology
• +۳ مورد دیگر

Prof. Dr. Wolfgang Freitag is a Professor of Theoretical Philosophy/Philosophy of Language at the University of Mannheim . He previously held positions at the University of Freiburg, Bern, and Heidelberg. His research spans theoretical philosophy (philosophy of language, epistemology, logic, metaphysics) and practical philosophy (metaphysics of norms). Doctorate: University of Konstanz (2005) Habilitation: University of Konstanz (2010) Education: Philosophy, History, Politics, Mathematics at Konstanz, Liverpool, Austin (Texas), and Oxford. Freitag's work focuses on paradoxes, expressivism, and epistemic norms. He explores the intersection of language, logic, and knowledge, with recent publications addressing causal reasoning, skepticism, and self-defeating statements. His publications include I Know: Modal Epistemology and Scepticism (2013) and Form and Philosophy: A Topology of Possibility and Representation (2009). Recent articles examine topics like lying, expressivist logic, and Kantian epistemology, reflecting his commitment to bridging theoretical and practical philosophy.

Kino Zhaoمشاهده پروفایل

استادیار

• Philosophy of Science
• Philosophy of Social Science
• Philosophy of Statistics
• +۶ مورد دیگر

Kino Zhao is an Assistant Professor in the Department of Philosophy at Simon Fraser University. His research focuses on the philosophy and methodology of the social sciences, emphasizing the interplay between philosophical analysis and scientific practice. He holds a PhD from the University of California, Irvine, an MA from Simon Fraser University, and a BA from the University of British Columbia. Education: PhD in Philosophy (Logic and Philosophy of Science), UC Irvine, 2021 MA in Philosophy, Simon Fraser University, 2015 BA in Psychology and Philosophy, University of British Columbia, 2013 Research interests include methodological challenges in social sciences, statistical assumptions, measurement validity, and the philosophical implications of machine learning and game theory. His work often bridges technical philosophy with empirical scientific practices. Notable contributions include critiques of traditional sampling methods in social sciences and advocacy for validity-first frameworks in measurement. Beyond academia, he co-founded Wonder Philosophy to support underrepresented students in philosophy graduate programs.

Cezary Z. Janikowمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Evolutionary Computation
• Genetic Algorithms
• +۹ مورد دیگر

Cezary Z. Janikow is an Associate Professor and former Chair of the Department of Mathematics and Computer Science at the University of Missouri–St. Louis (UMSL), where he conducts research in artificial intelligence, evolutionary computation, and machine learning. He is the developer of FID (Fuzzy Inference Decision tree), a system for generating fuzzy decision trees that handle missing, noisy, and continuous data. His research is supported by NIH, NSF, and NASA/JSC, and he has contributed significantly to the field of genetic programming, particularly in constrained and adaptable representations (ACGP). Ph.D. in Computer Science, University of North Carolina at Chapel Hill, 1991 His research interests center on evolutionary algorithms , fuzzy decision trees , and symbolic machine learning . He explores how genetic programming can adapt representations and incorporate constraints to improve search efficiency and solution quality. His work on FID has advanced fuzzy logic applications in classification and data analysis. The recent publications reflect a sustained focus on genetic programming , particularly Adaptable Constrained Genetic Programming (ACGP) , heuristics in evolutionary search , and fuzzy decision systems . His work spans theoretical development, algorithm design, and practical implementation, with applications in optimization and machine learning. Dr. Janikow has delivered corporate training in software development and served as an expert witness in software-related legal cases. He has also organized academic workshops and presented tutorials on evolutionary algorithms. Co-PI, NIH: Statistical Methods for Recursively Partitioned Trees NSF Support: Fuzzy Decision Trees NASA/JSC Collaboration: Constrained Genetic Programming He leads the FID project, a software system for fuzzy decision tree generation, which includes a GUI and supports cross-validation and noise simulation. This tool reflects his integration of research and software development.

• Statistics
• Spatial Statistics
• Spatio-Temporal Modeling
• +۷ مورد دیگر

Donato Posa is a Full Professor in Statistics at the Department of Economic Sciences, University of Salento. He holds the academic position of Professor Ordinario (Full Professor) in the field of Statistics (SECS-S/01) and is actively engaged in research and academic leadership. His work bridges economics, environmental science, and advanced statistical modeling. University: University of Salento Department: Department of Economic Sciences Academic Rank: Professor Email: donato.posa@unisalento.it Office: Centro Ecotekne Pal. C, S.P. 6, Lecce - Monteroni, LECCE (LE) Phone: +39 0832 29 8737 Donato Posa earned his degree in Physics, cum laude, from the University of Bari with a thesis conducted at CERN, Geneva, and completed a specialization in Physics. His international academic experience includes extended research stays at Stanford University (USA), the University of Arizona, and the University of North Carolina. His research focuses on spatial and spatio-temporal statistics, with major contributions in geostatistics, multivariate geostatistics, stochastic simulation, and time series analysis. He has developed theoretical and applied models for environmental monitoring, pollution assessment, and socioeconomic data analysis. His work has been applied in risk mapping, environmental policy, and urban planning. The 15 most recent articles reflect a consistent trend in spatio-temporal modeling and geostatistical innovation. They span theoretical developments in covariance modeling and variogram analysis to practical applications in environmental monitoring, pollution dispersion, and ecosystem well-being. The research demonstrates a strong interdisciplinary focus, integrating statistical theory with environmental, economic, and computational sciences. His scientific recognition includes multiple CNR and NATO research grants, CERN awards, and an International Diploma of Honour from the American Biographical Institute for contributions to geostatistics. He has served on editorial boards, chaired international conferences (e.g., GeoEnv 2012), and participated in national scientific qualification committees. Posa has supervised numerous research projects funded by CNR, MIUR, Fondazione Caripuglia, and EU programs. He has acted as a scientific referee for leading journals such as Stochastic Environmental Research and Risk Assessment and Computational Statistics and Data Analysis . He has also led educational initiatives in statistical methods and GIS for environmental and cultural heritage applications. He has been actively involved in academic governance, serving as President of the Research Observatory at the University of Salento (2013–2017) and as a member of national evaluation committees. He has chaired international conferences and contributed to major scientific associations including the Bernoulli Society, the International Association for Statistical Computing, and the American Statistical Association.