جست‌وجوی استاد و پژوهشگر

Erik Otárola-Castilloمشاهده پروفایل

دانشیار

• Archaeology
• Anthropology
• Human Evolutionary Biology
• +۷ مورد دیگر

Erik Otárola-Castillo is an Associate Professor in the Department of Anthropology at Purdue University, where he joined the faculty in 2015 and was promoted to Associate Professor. His interdisciplinary work bridges archaeology, human evolutionary biology, and biostatistics, focusing on prehistoric and modern hunter-gatherer populations and their responses to environmental change. His educational background includes: Ph.D. in Anthropological Science, Stony Brook University M.A. in Anthropology, Iowa State University B.A. in Anthropology, Stony Brook University Dr. Otárola-Castillo specializes in the evolution, ecology, and diversity of behavior in hunter-gatherer societies, with particular emphasis on climate change impacts and food availability effects on early North American native diets. As a computational anthropologist, he develops quantitative tools including 3D morphometrics software, statistical models for zooarchaeologists, and spatio-temporal analysis frameworks. His research integrates Geographic Information Systems (GIS) and Bayesian statistics to address core archaeological questions of space, time, and form, with applications ranging from bone surface modification analysis to human-megafauna interactions. Recent publications reveal a strong methodological trend toward Bayesian inference for archaeological hypothesis testing and computational morphometric analysis of artifacts and skeletal remains. Key thematic areas include lithic technology standardization, subsistence intensification mechanisms among Great Plains hunters, and health impacts of urbanization on indigenous Peruvian populations, demonstrating consistent application of quantitative rigor across diverse anthropological contexts. He is recognized as an international authority, evidenced by an invitation to contribute a review on Bayesian approaches to the Annual Review of Anthropology (2018). His work appears in high-impact journals including The Proceedings of the National Academy of Sciences (PNAS) and PLoS One. Dr. Otárola-Castillo directs the Laboratory for Computational Anthropology and Anthroinformatics (LCA), which develops open-source tools like geomorph and zooaRch for anthropological research. The lab's work enables advanced morphometric analysis and zooarchaeological quantification, supporting collaborative projects worldwide through computational innovation in data collection, analysis, and visualization.

• Data Science
• Big Data
• Natural Language Query Processing
• +۴ مورد دیگر

Prof. Dr. Kurt Stockinger is a Professor of Computer Science at ZHAW School of Engineering and holds a doctorate at the University of Zurich . He serves as Head of the MAS Data Science program and co-leads the ZHAW Datalab . His research focuses on Intelligent Information Systems , bridging information systems, natural language processing, and machine learning. Affiliated with the University of Zurich, he contributes to Quantum Machine Learning and Open Data Exploration initiatives. Stockinger's educational background includes a PhD in Computer Science (University of Vienna & CERN), a Master in Business Informatics (University of Vienna), and a CAS in Didactics & Methodology (ZHAW). He has taught courses in Quantum Computing , Big Data for Natural Sciences , and Data Science programs at ZHAW and University of Zurich. His research spans Data Science , Big Data , Natural Language Query Processing , Knowledge Graphs , and Quantum Machine Learning . Recent publications focus on quantum autoencoders , hybrid quantum neural networks , and prompt engineering for knowledge graph question answering. He has developed frameworks like ScienceBenchmark for real-world NL-to-SQL evaluation and NQuest for natural language query exploration. Scientific awards include the Best Paper Award at 7th Swiss Conference on Data Science (2020) He leads major projects such as DataGEMS (Data Discovery Platform, Horizon Europe) Digital Health Zurich (Clinical Innovation Lab) INODE4StatBot.swiss (NL-to-SQL Translation) GraphQueryML (Graph Database Optimization) ScienceBenchmark (NL-to-SQL Evaluation) Stockinger's work intersects with computer vision , biomedical data , and industrial applications , demonstrated through collaborations with institutions like Lawrence Berkeley National Laboratory, CERN, and University of Washington. He has contributed to establishing QuantumBasel and ZHAW Datalab as research hubs.

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.

Michel C. Desmaraisمشاهده پروفایل

استاد

• Artificial Intelligence
• Cognitive Modeling
• Learning Environments
• +۵ مورد دیگر

Michel C. Desmarais is a Full Professor in the Department of Computer Engineering and Software Engineering at Polytechnique Montréal, where he has been faculty since 2002. With a PhD in Psychology from Université de Montréal, his research bridges artificial intelligence, educational technology, and human-computer interaction. He holds affiliations with IVADO and LAMA-WeST research groups, and has held visiting positions at Sorbonne University, Eindhoven Technical University, and other European institutions. His research focuses on three interconnected pillars: 1) Cognitive modeling and educational data mining , developing algorithms for student knowledge assessment and adaptive learning systems; 2) AI-driven educational tools , including automated grading systems and peer instruction platforms; and 3) Recommendation systems and user modeling , particularly for personalized learning interfaces. His work consistently applies machine learning to solve practical challenges in technology-enhanced education. Analysis of his 150+ publications reveals strong trends in educational NLP (sentence similarity for short-answer grading), generative AI (LLM-generated code validation), and Bayesian modeling (Q-matrix refinement). Recent work increasingly focuses on transformer architectures and real-world educational datasets. He maintains an active supervision record, having graduated 35+ graduate students. Current PhD candidates work on NLP for educational applications (Bakhtiari, Kamdem) and AI for engineering (Wang). His teaching covers user interface design, recommender systems, and intelligent interfaces. Professional service includes editorial leadership (JEDM journal), conference co-chairing (UMAP 2017, EDM founding), and grant review panels for NSERC, MITACS, and EU programs. Industry experience includes prior roles as R&D Director at MVM Inc. and researcher at Montreal Computer Research Center.

Benjamin Spectorمشاهده پروفایل

دانشیار

• Semantics
• Pragmatics
• Syntax-Semantics Interface
• +۷ مورد دیگر

Benjamin Spector is a Research Director at the CNRS and an Associate Professor at École Normale Supérieure (ENS-PSL) , affiliated with the Institut Jean-Nicod (CNRS/ENS/EHESS). His work bridges natural language interpretation , formal logic , and experimental psychology , focusing on the interplay between compositional semantics and pragmatic reasoning . Research Interests: Syntax-semantics interface, scalar implicatures, presuppositions, plural predication, quantification, vagueness, and polarity sensitivity. Teaching: Courses on logic, semantics, and the Rational Speech Act (RSA) framework, including at ENS and ESSLLI. Collaborations: Extensive co-authorship with scholars like Paul Egré, Danny Fox, and Emmanuel Chemla, exploring topics from exhaustivity in RSA to trivalent logic for presuppositions . Labs: Associate Director of the CONCEPTS, LOGIC, REASONING research network at Institut Jean-Nicod.

Ray Buchananمشاهده پروفایل

استاد

• Philosophy of Language
• Action Theory
• Philosophy of Mind
• +۱ مورد دیگر

Ray Buchanan is a Professor in the Department of Philosophy within the College of Liberal Arts at the University of Texas at Austin. He received his PhD from New York University in 2008 and has established himself as a prominent scholar in multiple areas of philosophy. His office is located in WAG 416B, and he can be contacted at raybuchanan@mail.utexas.edu or by phone at 471-7396. Professor Buchanan's primary research interests include Philosophy of Language, Action Theory, Philosophy of Mind, and Philosophical Logic. His work explores fundamental questions about how we express thoughts through linguistic and non-linguistic actions, examining the relationship between meaning, communication, and mental representation. He has published extensively in top philosophy journals including Mind , Noûs , The Australasian Journal of Philosophy , and Philosopher's Imprint . His recent publications demonstrate a consistent focus on the nature of propositions, mental representation, and linguistic communication. Buchanan's work often engages with contemporary debates in philosophy of language, particularly concerning the role of intentions in communication, the structure of propositions, and the relationship between mental states and physical states. His research shows a sophisticated engagement with both historical philosophical traditions and cutting-edge contemporary debates. Professor Buchanan has received recognition for his scholarly contributions, with his publications cited across various philosophy subfields. His collaborative work with scholars like Alex Grzankowski, Sinan Dogramaci, and Henry Ian Schiller demonstrates his active engagement with the philosophical community. As an educator, Professor Buchanan teaches a range of courses at UT Austin including Philosophy of Mind (PHL 323M), Knowledge and Reality (PHL 310), and Philosophy of Language (PHL 332/394K). His teaching spans undergraduate and graduate levels, covering core topics in philosophy as well as specialized areas reflecting his research expertise. His courses are regularly offered across multiple semesters, indicating his ongoing commitment to teaching and student mentorship.

Yasutaka Kameiمشاهده پروفایل

استاد

• Empirical Software Engineering
• Software Reliability
• Software Testing
• +۸ مورد دیگر

Yasutaka Kamei is a Full Professor at Kyushu University's Graduate School and Faculty of Information Science and Electrical Engineering, where he leads the POSL Lab (Process-Oriented Software Laboratory). He was promoted from Associate Professor to Full Professor in January 2024 after serving as Associate Professor from March 2015 to December 2023. He is also an InaRIS Fellow (2023-2033), receiving 10 million yen annually for his research on 'New paradigm for software development styles based on machine-human interaction.' Dr. Kamei's research focuses on Empirical Software Engineering (ESE) and Open Source Software Engineering (OSSE), with particular expertise in software reliability, testing, defect prediction, code review analysis, and mining software repositories. His work bridges empirical methods with practical software engineering challenges, emphasizing how data-driven approaches can improve software quality assurance processes. His recent publications demonstrate a strong trend toward understanding human factors in software development processes, analyzing modern code review practices, investigating technical debt, and exploring the application of large language models in software engineering tasks. His research spans both traditional software engineering challenges and emerging AI-driven approaches to software development. IPSJ/ACM Award for Early Career Contribution to Global Research (2019) Best industry paper award at ESEM 2018 Distinguished Paper Award at MSR 2014 InaRIS Fellow (2023-2033) Dr. Kamei actively serves the software engineering community as Tutorials Chair for ASE 2025 and has been a program committee member for numerous top-tier conferences including ICSE, FSE, ASE, ESEC/FSE, SANER, and MSR. He has secured multiple competitive grants from MEXT (Ministry of Education, Culture, Sports, Science and Technology) to support his research on test case generation, automated software testing for deep learning systems, technical debt engineering, and mining software repositories. His POSL Lab at Kyushu University serves as a hub for empirical software engineering research, focusing on data-driven approaches to improve software development processes and outcomes through rigorous analysis of software repositories and developer activities.

• Computational Neuroscience
• Perception
• Decision Making
• +۲ مورد دیگر

Ulrik Beierholm is an Associate Professor in the Department of Psychology at Durham University, serving as Department Representative and Fellow of the Durham Research Methods Centre, and holding an Associate Professor position on the Executive Board of the Biophysical Sciences Institute. His research employs computational frameworks to investigate uncertainty processing in perception, decision making, and learning through interdisciplinary methodologies. His core research spans Computational Neuroscience, Perception, Decision Making, Neuroeconomics, and Machine Learning, with emphasis on Bayesian inference and reinforcement learning models validated via psychophysics, fMRI, and pharmacological techniques. Recent work demonstrates how the nervous system optimally handles sensory uncertainty across multisensory contexts, developmental stages, and cognitive tasks. Analysis of his publication trajectory reveals consistent innovation in Bayesian modeling of perceptual processes, with growing emphasis on computational tools development, neuroeconomics applications, and educational initiatives. His work bridges theoretical neuroscience with experimental validation across diverse cognitive domains. Honors include: Facebook Faculty Award for Virtual Reality (2016) Associate Editor for PLoS Computational Biology Editor for Bayesian methods section in Springer's Encyclopedia of Computational Neuroscience Dr. Beierholm supervises postgraduate researchers including Denise Foresteire and has co-organized influential workshops such as the Durham Computational Biology Symposium (2018) and Probabilistic Brain Workshop (2018), establishing himself as a key collaborator in computational neuroscience communities. His dual affiliations with the Biophysical Sciences Institute and Durham Research Methods Centre facilitate cross-disciplinary integration of psychological theory, neural data, and advanced computational modeling to address fundamental questions about human cognition.

Noura Al Moubayedمشاهده پروفایل

دانشیار

• Explainable Machine Learning
• Natural Language Processing
• Optimisation
• +۶ مورد دیگر

Dr. Noura Al Moubayed serves as an Associate Professor in the Department of Computer Science at Durham University, specializing in Explainable Machine Learning, Natural Language Processing, and Optimisation for high-dimensional data challenges. Education PhD from Robert Gordon University Post-doctoral positions at University of Glasgow and Durham University Research Focus Her work develops machine learning solutions for healthcare, social signal processing, cyber-security, and Brain-Computer Interfaces, specifically targeting noisy and imbalanced datasets through advanced NLP and optimization techniques. Current projects integrate deep learning with explainability frameworks to enhance real-world applicability. Publication Trends Recent publications (2020-2022) demonstrate consistent focus on improving question answering systems via bilinear pooling and paraphrasing techniques, alongside novel deep learning approaches for probabilistic topic modeling. These works bridge computer vision, NLP, and multimodal learning to address data imbalance challenges across healthcare and social computing domains. Academic Service PeerJ Computer Science Editorial Board Member 335 authorship points and 30 reviewer points on PeerJ platform

• Quantum Foundations
• Quantum Information Science
• Quantum Correlations
• +۶ مورد دیگر

Cyril Branciard is a Permanent Researcher at CNRS (French National Center for Scientific Research) working at the Institut Néel in Grenoble, France. He is affiliated with the PLUM (Physics – Light – Material) department and is a member of the Nanophysics and Semiconductors (NPSC) research team. His office is located in room C3-212 and he can be reached at cyril.branciard@neel.cnrs.fr. Branciard completed his PhD in 2009 at the University of Geneva under the supervision of Prof. Nicolas Gisin. His doctoral thesis was titled "Practical and Fundamental issues on Quantum Correlations." Dr. Branciard's research focuses on theoretical aspects of quantum information science and quantum foundations. His work primarily investigates quantum correlations, non-locality, Bell inequalities, quantum causality, and indefinite causal orders. He has made significant contributions to understanding the status of the wave function, generalized probabilistic theories, uncertainty principles, and quantum cryptography. His research often involves experimental demonstrations using quantum optics frameworks. His publication record demonstrates a consistent focus on causal structures in quantum mechanics, with recent work examining network-device-independent certification of causal nonseparability, quantum metrology with indefinite causal orders, and estimation of quantum properties using randomized measurements. His research shows a progression from foundational questions about quantum nonlocality to more applied aspects of quantum information processing. Branciard has established a strong collaborative network, frequently working with researchers such as Alastair A. Abbott, Julian Wechs, Nicolas Brunner, and Benoît Vermersch. His work appears in top physics journals including Physical Review Letters, Nature Communications, and Quantum.

Matthew F. Puseyمشاهده پروفایل

مدرس

• Quantum Information
• Quantum Foundations
• Quantum Contextuality
• +۳ مورد دیگر

Matthew F. Pusey is a Lecturer in Quantum Information at the Department of Mathematics, University of York. His academic career is deeply rooted in the foundations of quantum mechanics, with a particular focus on quantum contextuality, nonlocality, and the interpretation of quantum states. His work bridges theoretical investigations with experimental implications, making significant contributions to our understanding of the boundaries between classical and quantum phenomena. Pusey's research primarily explores quantum contextuality as a fundamental aspect of quantum theory that cannot be explained by noncontextual hidden variable models. His work demonstrates how contextuality manifests in various quantum phenomena including weak measurements, pre- and post-selection paradoxes, and quantum information processing. His research shows that contextuality serves as a critical resource for quantum advantage in certain computational tasks, and he has developed robust methods to detect contextuality even in imperfect experimental conditions without requiring idealized assumptions. His publication record reveals a consistent trajectory of influential work in quantum foundations, with papers appearing in top journals such as Physical Review Letters, Nature Physics, and Quantum. His research demonstrates increasing sophistication in connecting abstract foundational concepts with practical experimental tests and potential quantum information applications. The evolution of his work shows a progression from foundational questions about quantum state reality to more structured mathematical frameworks for understanding generalized probabilistic theories and contextuality. Pusey completed his PhD at Imperial College London in 2013 with the thesis "Is quantum steering spooky?" and previously earned an MRes in 2010 with research on connections between quantum computation and non-locality. He maintains an active presence in the quantum foundations community through numerous invited talks at major conferences and institutions worldwide.

Mawuli Afenyoمشاهده پروفایل

استادیار

• Maritime Economics
• Arctic Shipping
• Maritime Cybersecurity
• +۵ مورد دیگر

Mawuli Afenyo serves as Assistant Professor in Maritime Business Administration at Texas A&M University at Galveston's College of Marine Sciences & Maritime Studies, specializing in maritime risk analysis and Arctic shipping systems. His interdisciplinary work integrates engineering, economics, and environmental science to address critical challenges in maritime security and sustainability. His academic foundation includes a PhD in Engineering from Memorial University of Newfoundland (2017), MBA from Bologna Business School (2013), and BSc in Engineering from Kwame Nkrumah University of Science and Technology (2009). PhD Engineering, Memorial University of Newfoundland (2017) MBA, Bologna Business School (2013) BSc Engineering, Kwame Nkrumah University of Science and Technology (2009) Dr. Afenyo's research focuses on maritime cybersecurity, Arctic shipping economics, and oil spill risk modeling, with particular emphasis on climate change adaptation. His methodologies frequently employ Bayesian networks, resilience indices, and probabilistic risk assessment frameworks to analyze complex maritime systems operating in extreme environments. Analysis of his 15 most recent publications (2019-2023) reveals three dominant research trajectories: Arctic shipping dynamics (40% of works), maritime cybersecurity threats (25%), and oil spill impact assessment (35%). These publications consistently utilize advanced quantitative methods while addressing policy-relevant questions about sustainability and security in polar regions. His scientific recognition includes: Young Researcher Best Paper Award (KLU, 2019) Outstanding Graduate Studies Award (Memorial University, 2017) Lloyd's Register Foundation PhD funding (2014) Hult Prize Semi-Finalist (2013) Dr. Afenyo actively secures competitive research funding including a $27,000 Texas Comprehensive Research Grant (2023), $10,000 Global Cyber Research Institute Grant (2023), and $8 million Genome Canada GENICE II grant (2021). His projects frequently involve international collaborations addressing Arctic shipping safety, maritime cybersecurity, and climate adaptation strategies for port infrastructure. As a Climate Bonds Initiative adaptation & resilience expert, he contributes to developing certification standards for sustainable shipping while advancing practical solutions through his teaching of courses including Maritime Cybersecurity and Risk Management, Global Logistics, and Maritime Economics.

Manfred Keilمشاهده پروفایل

دانشیار

• Macroeconomics
• Econometrics
• Statistics
• +۵ مورد دیگر

Manfred Keil serves as Associate Professor in the Economics Department at Claremont McKenna College's Robert Day School of Economics and Finance, specializing in macroeconomic policy and empirical analysis. His educational background includes a Zwischenpruefung from Goethe Universitaet Frankfurt, M.S. and Ph.D. degrees from the London School of Economics, and an M.A. from the University of Texas. Professor Keil's research centers on comparative economic performance across nations and regions, with significant contributions to business cycle forecasting methodologies. His expertise spans central bank policymaking, data science applications in economics, and regional economic integration dynamics, consistently employing rigorous statistical frameworks to address complex macroeconomic questions. His publication record demonstrates sustained scholarly impact since the late 1980s, with recent work advancing probabilistic approaches to economic expansion forecasting (2023) and historical investigations into political business cycles. Key thematic areas include inflation-growth nonlinearities, capital mobility constraints in developing economies, and comparative unemployment analysis across North America and Europe. Teaching responsibilities encompass core courses in Macroeconomics, Econometrics, and Statistics, reflecting his methodological strengths. Office hours are maintained Tuesday 12:30-1:30pm, Thursday 10:00-11:00am, and Wednesday 6:30-7:30pm via Zoom from Bauer Center 315.