جست‌وجوی استاد و پژوهشگر

Jens Boosمشاهده پروفایل

پژوهشگر ارشد

• Black Hole Phenomenology
• Modified Gravity
• Quantum Gravity
• +۳ مورد دیگر

Jens Boos is a Young Investigator Group Fellow leading the Black Hole Phenomenology Group at the Institute for Theoretical Physics, Department of Physics, Karlsruhe Institute of Technology (KIT). His research bridges observational black hole data with fundamental physics models, focusing on new particles and gravitational theories beyond general relativity. Previously, he held postdoctoral positions at William & Mary (2020-2023) and completed his PhD at the University of Alberta (2016-2020). His academic journey includes: PhD in Physics, University of Alberta (2016-2020), supervised by Valeri P. Frolov and Don N. Page Perimeter Scholars International program, Perimeter Institute for Theoretical Physics (2015-2016) Master of Science, University of Cologne (2012-2015), thesis on BTZ black hole quasi-normal modes under Friedrich W. Hehl and Claus Kiefer Boos specializes in analytical approaches to three core research pillars: non-singular black hole models (studying light propagation in singularity-free spacetimes), strong first-order phase transitions in the early universe (modeling gravitational wave signatures), and post-Riemannian gravity (exploring theories with torsion and curvature beyond standard geometry). His work connects quantum gravity effects to observable phenomena in gravitational wave astronomy and black hole imaging, with emphasis on mathematical rigor and testable predictions. Publications since 2015 reveal an evolving trajectory from foundational work on exact solutions in general relativity toward contemporary focus on nonlocal gravity phenomenology. Recent output emphasizes ultraviolet regulators in quantum gravity, resonant particle production mechanisms, and mathematical structures in black hole spacetimes—demonstrating consistent integration of differential geometry, quantum field theory, and astrophysical observables. Key recognitions include: Vanier Scholar (premier Canadian doctoral award) University of Alberta Faculty of Science Dissertation Award DTP/WITP P.R. Wallace Thesis Prize from the Canadian Association of Physicists As group leader, Boos currently supervises master's student Hao Hu and bachelor students Felix Wunsch and Marek Hartenfels. While unavailable for PhD/master thesis supervision per his current mandate, he actively recruits bachelor researchers. His KIT-funded Young Investigator Group supports analytical model development for gravitational wave data interpretation, with particular attention to extreme mass-ratio inspirals. The group maintains strong international collaborations with institutions including William & Mary and the University of Alberta. The Black Hole Phenomenology Group operates as a hub for mathematical physics innovation, combining expertise in gauge theories, nonlocal operators, and cosmological phase transitions to probe quantum gravity signatures in astrophysical data. Current projects include kilometer-scale UV regulator phenomenology and topological defect analysis in nonlocal gravity frameworks.

• Cognitive Psychology
• Psychological Research Methodology
• Applications of Mathematics in Psychology
• +۷ مورد دیگر

Dr. Borysław Paulewicz is an Assistant Professor in the Department of Experimental Psychology at Jagiellonian University's Faculty of Philosophy. Previously taught cognitive psychology and psychometrics at SWPS University for a decade. His work bridges cognitive psychology, mathematical methodology, and meta-theoretical foundations of psychology, with a focus on metacognition and causal inference. Current affiliations: Jagiellonian University, Faculty of Philosophy, Department of Experimental Psychology Past affiliations: SWPS University of Social Sciences and Humanities Research Interests: Specializing in causal/Bayesian inference applications, development of hierarchical generalized linear models, and formal definitions of measurement invariance. His projects explore metacognition, consciousness, and placebo mechanisms through National Science Centre grants (MAESTRO, HARMONIA, SONATA BIS/SONATA programs). Academic Contributions: Created R libraries for psychometric models, formulated causal-theoretical measurement frameworks, and authored a GitHub-hosted book on mathematics for psychologists. Published extensively in metacognition, signal detection theory, and causal modeling. Projects: Key investigator in studies on pain unlearning, metacognitive mechanisms, and cognitive control. Collaborated with Agata Blaut on emotional disorder biases, Michał Wierzchoń on consciousness, and Marta Siedlecka on metacognition.

Jürgen Dassowمشاهده پروفایل

استاد

• Formal languages
• Regulated rewriting
• Lindenmayer systems
• +۷ مورد دیگر

Jürgen Dassow is a Professor for Theoretical Computer Science at the Faculty of Computer Science, Otto-von-Guericke-University of Magdeburg, Germany. He has held this position since 1992 and previously served as Rector of the university from 1993 to 1996. His academic career spans over five decades, beginning with studies in mathematics at the University of Rostock in the 1960s. Professor Dassow's research focuses on formal languages, regulated rewriting, Lindenmayer systems, grammar systems, syntactical complexity, and biocomputing . His work has significantly contributed to theoretical computer science, particularly in the mathematical foundations of language theory and automata. He has maintained a prolific publication record with over 200 scientific papers and 4 monographs, including the influential 1989 work 'Regulated Rewriting in Formal Language Theory' co-authored with Gheorghe Păun. His recent research (2020-2023) continues to explore operational complexity, closure-involution operations, contextual grammars, and networks of evolutionary processors. These publications demonstrate his sustained engagement with cutting-edge theoretical problems in computer science. Professor Dassow has also been instrumental in organizing the international Descriptional Complexity of Formal Systems (DCFS) workshop series and has edited numerous proceedings volumes. Professor Dassow has been actively involved in the academic community through approximately 100 lectures at conferences and universities across 18 countries. His work bridges theoretical computer science with biological computing models, reflecting the interdisciplinary nature of modern theoretical research. His research group at the Otto-von-Guericke-University continues to advance knowledge in formal language theory, with recent publications addressing contemporary challenges in descriptional complexity and bio-inspired computational models. Professor Dassow's career exemplifies long-term dedication to advancing the theoretical foundations of computer science while maintaining relevance to emerging computational paradigms.

Thierry Bollonمشاهده پروفایل

مدرس ارشد

• Social Psychology
• Neural Networks
• Learning
• +۳ مورد دیگر

Thierry Bollon serves as a Senior Lecturer at the University of Savoie Mont Blanc in Chambéry, France, where he bridges social psychology and computational modeling through innovative connectionist approaches. His research fundamentally challenges traditional social psychology frameworks by simulating how social context shapes cognitive processing. Bollon's work centers on three interconnected domains: Social learning mechanisms in motor task acquisition Computational modeling of social norm internalization (exemplified by the NetNorm framework) Emotion-decision interactions, particularly how uncertainty appraisal modulates risk-taking in tasks like the Iowa Gambling Task His methodology uniquely integrates neural network architectures with social psychological theory to model contextual influences on cognition. Analysis of his 1995-2013 publications reveals consistent emphasis on computational social psychology, with recent work (2008-2013) increasingly focusing on emotion-cognition dynamics. Key themes include appraisal theory applications, social context simulation, and the development of specialized connectionist models for social phenomena. His research demonstrates how computational approaches can generate testable predictions about social behavior. While grant details aren't specified in available materials, Bollon maintains active collaborations with researchers including Virginie Bagneux, Pascal Pansu, and Adeline Paignon across multiple publications. His advising appears to focus on computational social psychology methods, with co-authors suggesting mentorship of junior researchers in neural network modeling applications.

Richard Kempterمشاهده پروفایل

استاد

• Computational Neuroscience
• Memory Systems
• Hippocampal Circuitry
• +۵ مورد دیگر

Richard Kempter is a Professor at Charité - Universitätsmedizin Berlin's Institute of Neuroscience, where he leads research in computational neuroscience with a focus on hippocampal circuitry and memory systems. His work bridges experimental neuroscience with theoretical modeling, examining how neural networks support spatial navigation, memory formation, and consolidation processes. His research interests center on the computational principles underlying hippocampal function, particularly in memory consolidation, spatial navigation, and neural coding. Kempter investigates how hippocampal circuits generate sharp wave-ripple events, how grid cells form spatial representations, and how memory traces transform during systems consolidation. His work combines computational modeling with experimental data analysis to develop testable theories about neural mechanisms. Analyzing Kempter's recent publications reveals a strong focus on hippocampal CA3 circuitry, with particular attention to sharp wave-ripple complexes and their role in memory consolidation. His work demonstrates how specific connectivity patterns between pyramidal neuron subtypes enable memory replay, while his computational models explain how grid-like representations emerge in entorhinal cortex. The research spans multiple scales from single-cell properties to network dynamics, with applications to both rodent and human memory systems. Kempter's scientific contributions have appeared in top-tier journals including Nature , Neuron , and PNAS , reflecting the significance of his work in understanding fundamental neural mechanisms. His publications demonstrate consistent innovation in developing computational frameworks that explain experimental observations while generating new testable predictions about memory systems. His research team collaborates extensively across institutions, working with experimental neuroscientists to bridge theoretical models with empirical data. Current projects examine how neural synchrony creates functional filters during rest states, how population sparseness affects memory capacity, and how subtype-specific connectivity enables sequential activation during memory replay events.

Alan Yilan Xuمشاهده پروفایل

استادیار

• Behavioral Nudges
• Sustainability and Food Choice
• Food Marketing
• +۳ مورد دیگر

Alan Yilan Xu is an Assistant Professor of Agricultural Economics at Fort Hays State University, specializing in applied economics with a focus on behavioral interventions and sustainability in food systems. His work bridges economic theory with real-world consumer behavior analysis. His academic credentials include: Ph.D. in Agricultural, Environmental, and Development Economics from The Ohio State University (2022) Master's in Economics from the University of Delaware Master's in Statistics from the University of North Carolina at Chapel Hill Dr. Xu's research integrates behavioral nudges and discrete choice modeling to explore sustainability-driven food choices, environmental valuation, and marketing impacts. He prioritizes empirical rigor through original survey and experimental data collection, addressing critical gaps in non-market valuation and consumer decision-making processes. His methodological approach emphasizes translating theoretical concepts into testable economic frameworks for food policy applications. As an active scholar, he maintains professional visibility via Google Scholar, ORCID, LinkedIn, and Twitter (@alanyilan), though specific collaborative projects or institutional initiatives remain undocumented in available sources.

Nichalin Summerfieldمشاهده پروفایل

دانشیار

• Explainable AI
• Predictive Analytics
• Simulations
• +۳ مورد دیگر

Nichalin Summerfield serves as Associate Professor and M.S. in Business Analytics Program Coordinator in the Operations and Information Systems Department at UMass Lowell's Manning School of Business, leveraging interdisciplinary expertise in quantitative methods and healthcare systems. Education: Ph.D. in Operations Management (2010), Department of Management Information Systems, The University of Arizona M.S. in Management Information Systems (2005), Department of Management Information Systems, The University of Arizona BEE in Electrical Engineering (Honors) (1998), Sirindhorn International Institute of Technology, Thammasat University Research Focus: Her work integrates explainable AI , simulation modeling , and game theory to solve healthcare logistics challenges including patient no-show prediction, substance use disorder treatment optimization, and mobile banking security. Recent methodologies emphasize interpretable machine learning for generating testable hypotheses from complex clinical datasets. Publication Trends: Spanning 2011-2025, her research evolved from foundational operations research (Chinese Postman Problem applications, stochastic programming) toward cutting-edge healthcare analytics, with 2021-2025 publications demonstrating strong emphasis on explainable AI frameworks for medical decision support and financial systems security. Scientific Recognition: Department's Research Excellence Award (2025) Department's Teaching Excellence Award (2022) Runner-up - DSI Regional Best Paper Award (2021) Best Application of Theory Paper Award (2021) Research Leadership: As Co-Principal Investigator for the 2024 Internal Seed Grant on electoral precinct resource allocation and 2017 urban transportation analytics project, she secures funding for real-world problem solving. Current work explores deep reinforcement learning in supply chain optimization , building on prior industry experience at Accenture and NASA's Phoenix Mars Lander software development. Collaborative Networks: Partnerships with University of Massachusetts Medical School and UMass Memorial Healthcare enable translational research, while active participation in Decision Sciences Institute and INFORMS conferences drives methodological innovation in business analytics.