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Lucie CharlesView profile

Lecturer

• Cognitive Neuroscience
• Metacognition
• Decision-making
• +5 more

Dr. Lucie Charles is a Lecturer in Psychology at Queen Mary University of London, affiliated with the Centre for Brain and Behaviour within the School of Biological and Behavioural Sciences. She focuses on cognitive processes related to metacognition, introspection of decisions, and action awareness. Her work integrates psychophysics, computational modelling, and neuroimaging to study how humans evaluate their decisions and actions. Dr. Charles completed her PhD at Neurospin, France, under Stanislas Dehaene, investigating metacognition and consciousness. She held roles at UCL (Senior Research Fellow and Lecturer) and Oxford University (British Academy Fellow), collaborating with Patrick Haggard and Nick Yeung on topics like volition and error detection. She currently leads the Association for the Scientific Study of Consciousness as Executive Director since 2019. Her research explores three core areas: 1) choice awareness and freedom of choice, 2) confidence biases in decisions, and 3) motor awareness. She examines how people introspect decision processes, detect external influences, and perceive motor execution accuracy. Her grants include an ESRC-funded project on freedom of choice and introspection (2019). Key contributions include studies on paradoxical evidence weighting in confidence judgments, Bayesian models of metacognition, and neural correlates of action awareness. She supervises postdoctoral researchers like Keiji Ota and offers PhD opportunities in her research areas. Her work is disseminated through Google Scholar, ResearchGate, and @LucieCharlesCog on Twitter.

• Motion Picture Science
• Imaging Systems
• Radiometric Calibration
• +7 more

Ricardo Figueroa is the School Director of the School of Film and Animation at the College of Art and Design, Rochester Institute of Technology (RIT), where he also holds the distinguished title of John Traver Endowed Professor. He earned his Ph.D. in Computing and Information Sciences from RIT, with prior degrees in Electrical Engineering from the University of Puerto Rico at Mayagüez. His research expertise lies at the intersection of engineering and motion picture science, with a focus on imaging systems, radiometric calibration, electronic image noise, and digital cinema workflows. His work bridges technical precision with creative application, emphasizing the scientific foundations of visual media. The recent publications and his U.S. patent highlight a consistent trajectory in advancing imaging technology for motion pictures, particularly in calibration and encoding. His research integrates statistical methods like Bayesian inference and explores neural networks for motion capture correction, indicating a forward-looking, interdisciplinary approach. SMPTE Fellow, 2020 Ricardo actively mentors students through senior projects and graduate theses, teaching core courses such as Introduction to Imaging and Video Systems, Film Projection and Digital Cinema, and Senior Project sequences. He also oversees independent studies and thesis research. His leadership has fostered industry partnerships, such as with The Dolby Institute, enhancing experiential learning. He supervises student projects in areas like latency perception and rotoscope automation, often leading to publications and real-world applications. He leads the School of Film and Animation, shaping curriculum and research direction, and promoting an interdisciplinary culture where technology and art converge. His lab and team activities are reflected in student capstone projects involving neural networks, deep learning, and digital imaging, supported by industry collaborations and professional society engagement like SMPTE.

• Marketing
• Marketing Research
• Quantitative Marketing Research
• +7 more

Konstantinos (Kostas) Kaminakis is an Assistant Professor in the Department of Marketing and Communication at the Athens University of Economics and Business (AUEB), School of Business. He maintains an active teaching portfolio across several Greek universities, including the National and Kapodistrian University of Athens and the Greek Open University, at both graduate and postgraduate levels. Education: Ph.D. in Marketing – Athens University of Economics and Business (AUEB) M.Sc. in Marketing and Communication – Athens University of Economics and Business (AUEB) Degree in Accounting and Finance – Athens University of Economics and Business (AUEB) Research Focus: His research centres on the intersection of marketing strategy, service quality, and consumer behaviour. He employs quantitative methodologies to investigate how internal marketing influences customer outcomes, how hospitality servicescapes shape customer–employee interactions, and how demographic factors affect resident support for tourism development. A recurring theme is the application of advanced statistical techniques—such as Bayesian structural equation modelling and multilevel analysis—to marketing problems in tourism, hospitality and service contexts. Publication Trends: Across 2015–2021 his work has appeared in leading journals including Journal of Business Research , Tourism Management , Industrial Marketing Management , Journal of Travel Research , and Marketing Intelligence and Planning . The articles collectively demonstrate a trajectory from foundational studies on service delivery and internal marketing to nuanced explorations of tourist behaviour, crisis-era SME strategies, and brand construal among frontline employees. Professional Service: Reviewer for multiple international conferences and journals Member: Greek Marketing Academy, European Marketing Academy, American Marketing Association, Academy of Marketing Science Teaching & Industry Engagement: In addition to his university roles, Kaminakis has served as a scientific collaborator and employee-lecturer, and he possesses extensive private-sector experience, bridging academic theory with practical marketing challenges.

Dmitry IgnatyevView profile

Senior Lecturer

• Aeronautical Systems
• Autonomous Systems
• Computing, Simulation & Modelling
• +7 more

Dr. Dmitry Ignatyev is a Senior Lecturer in Flight Dynamics and Control at Cranfield University's Centre for Autonomous and Cyberphysical Systems. With a PhD in Physics and Mathematics from Moscow Institute of Physics and Technology (2013), he previously spent eight years at Russia's Central Aerohydrodynamic Institute. His research spans aeronautical systems, autonomous vehicles, and structural dynamics. Education: PhD in Physics and Mathematics (2013) from Moscow Institute of Physics and Technology Affiliation: Cranfield University, School of Aerospace, Transport and Manufacturing Ignatyev's expertise includes Autonomous Systems , Flight Physics , and Computational Modeling . His work focuses on advanced control strategies and aerodynamic modeling to enhance vehicle performance and safety. Notable projects include developing autonomous emergency-responder aircraft with Cranfield's CraneAero team. His recent publications highlight trends in UAV control algorithms , Loewner framework applications for structural health monitoring, and Martian aerobot design . Awards include Fellowships in the Higher Education Academy (FHEA) and Royal Aeronautical Society (FRAeS). Scientific Recognition: Fellow of the Higher Education Academy (FHEA) Fellow of the Royal Aeronautical Society (FRAeS) Leadership: Deputy Course Director for the Autonomous Vehicle Dynamics and Control MSc program

Evan PeckView profile

Associate Professor

• Information Visualization
• Human-Computer Interaction
• Computing Ethics Education
• +5 more

Evan Peck is an Associate Professor in the Information Science Department at the University of Colorado Boulder, where he also serves as Associate Chair of Undergraduate Studies. His research focuses on reimagining data communication for diverse communities and integrating computing ethics into technical education. Collaborations include institutions like MIT, Worcester Polytechnic Institute, and UMass Amherst. Education: Ph.D. in Computer Science from Tufts University (2014). Prior Affiliation: Associate Professor at Bucknell University. Research Interests: Evan examines how implicit design assumptions about technology access and user experiences affect data visualization's societal impact. His work bridges Human-Computer Interaction and Information Visualization , emphasizing public engagement and equity. Recent projects analyze barriers in data literacy, ethical implications of visualization tools, and participatory methods for marginalized communities. Publication Trends: His recent articles highlight interactive visualization frameworks (e.g., SurpriseExplora , Charting EDA ), empirical studies on novice user challenges, and ethical design interventions. Collaborations often involve locational biases in data representation and tools for marginalized groups. Scientific Awards: Best Paper Award (ACM CHI 2023) Best Paper Award (ACM CHI 2019) Advising & Grants: Evan mentors Ph.D. and Master’s students in the Information Visions Lab and secured a Stage 2 grant from Mozilla’s Responsible Computing Initiative (2024). He advocates for undergraduate research integration and socially responsible computing curricula. Labs & Teams: He directs the Information Visions Lab (under construction), focusing on public data tools, and collaborates with the MIT Visualization Group and Visualization for Social Good steering committee.

• Medical Risk Literacy
• Evidence-Based Decision Making
• Fast-and-Frugal Decision Support Tools
• +7 more

Odette Wegwarth is a Professor at Charité – Universitätsmedizin Berlin and Senior Research Scientist at the Center for Adaptive Rationality, Max Planck Institute for Human Development . Her work focuses on medical risk literacy , evidence-based decision making , and fast-and-frugal decision support tools , addressing critical issues like defensive decision making and conflicts of interest in medicine. PhD in Psychology (2007), Humboldt-Universität zu Berlin Habilitation in Medical Sociology (2015), Charité – Universitätsmedizin Berlin Her research bridges health communication and cognitive psychology , examining how statistical illiteracy affects clinical decisions and patient outcomes. Recent projects include evaluating interactive simulation tools for vaccine-hesitant populations and analyzing privacy-utility trade-offs in health data donation. She has received prestigious awards such as the Heisenberg Professorship (DFG, 2020) and appointments as a WHO expert (2021, 2019). Current grants include European Union Horizon Europe and German Research Foundation (DFG) funding for projects like 'Yellow4Flavi' and 'ERONA', emphasizing transparency in medical communication and preventive health strategies . Her leadership in infodemic management and cancer prevention (e.g., FORECEE project) underscores her commitment to empowering patients and practitioners through evidence-based tools and ethical risk communication frameworks.

• Computer Science
• Artificial Intelligence
• Medical Image Analysis
• +3 more

Xi Wu is a faculty member at Chengdu University of Information Technology , affiliated with the School of Computer Science . He holds a PhD from Sichuan University (2012, College of Electronic and Information Engineering). Current Research Focus: Medical imaging, computer vision, and deep learning applications in healthcare Key Themes: PET image reconstruction, radiotherapy dose prediction, GANs, diffusion models, and facial expression recognition His recent work explores transformer architectures , semi-supervised learning , and uncertainty-aware models for tasks like tumor segmentation and multi-organ analysis. Publications emphasize cross-domain adaptation and multi-modal medical imaging .

Roberto LimongiView profile

Assistant Professor

• Neuroscience
• Cognitive Science
• Psychiatry
• +9 more

Roberto Limongi is an Assistant Professor in the Department of Psychology at Brandon University, located within the Faculty of Arts. His research focuses on neuro-computational mechanisms linking language production to conceptual organization in long-term memory, utilizing fMRI, MRS, computational models, and natural language processing. He leads the Writing-brain Laboratory, investigating effects of writing on academic learning and developmental disorders. Key collaborators include Karl Friston (UCL) and David Galbraith (University of Southampton). Limongi has secured grants including a 2023-2024 New Faculty Grant ($7,052) and a 2024-2026 SSHRC Insight Development Grant ($75,000). He received the 2022 John R. Hayes Award for writing research excellence. Research Themes: Schizophrenia neurobiology, computational linguistics, neurochemical biomarkers, epistemic writing effects Recent Funding: Over $82k in grants Collaborators: Global network including UK & Canadian institutions His lab's current work combines neuroimaging with advanced computational methods to identify neural markers of writing's impact on memory consolidation. Notable findings include glutathione-glutamate interactions in psychosis and syntactic complexity as a schizophrenia biomarker. Training opportunities exist for undergraduates through research participation programs offering $50 payments.

• Substance Use Recovery
• Adolescent Mental Health
• Behavioral Health Systems
• +3 more

Crystal Reinhart serves as Research Assistant Professor and Senior Research Scientist at the University of Illinois Urbana-Champaign's School of Social Work, with additional affiliation at the Center for Social & Behavioral Science. Her work bridges computational methods and behavioral health interventions, focusing on adolescent substance use recovery systems and community-based solutions. Her research centers on substance use recovery capital among adolescents and emerging adults, examining protective/risk factor patterns through Bayesian networks and machine learning. Key interests include problem resolution frameworks, certified peer specialist integration, and geographic determinants of intergenerational mobility impacting substance use. She investigates how socioeconomic factors and community systems shape recovery pathways, with strong emphasis on methodological innovation in behavioral data collection. Recent publications reveal a clear trajectory toward computational social work, applying advanced statistical techniques to map recovery capital and assess data reliability in adolescent populations. Her work consistently integrates public health, social work practice, and data science to address substance use through recovery-oriented frameworks rather than traditional treatment models. No scientific awards were documented in the provided materials. While specific advising relationships weren't detailed, her research outputs indicate active mentorship through co-authored publications with junior researchers. No grant information was explicitly referenced, though her statewide survey work suggests involvement in large-scale public health initiatives. Her affiliation with the Center for Social & Behavioral Science implies participation in interdisciplinary research teams focused on behavioral health systems, though specific lab structures weren't described.

Tobias RebholzView profile

Research Fellow

• Quantitative Methods for Behavioral Research
• Social Cognition
• Judgment and Decision-Making
• +12 more

Tobias Rebholz is a quantitative psychologist and econometrician currently serving as a Visiting Research Scholar in the Management and Organizations Area at the Fuqua School of Business, Duke University. Previously, he was a postdoctoral research associate in the Social Cognition and Decision Sciences group at the Department of Psychology, University of Tübingen, Germany. His academic journey includes a PhD in Psychology from the DFG-funded Research Training Group 'Statistical Modeling in Psychology' at the University of Tübingen (2023), an M.Sc. in Economics with a focus on Econometrics and Applied Economics from the University of Konstanz (2017-2020), and a B.Sc. in Business Studies and Economics with a major in Psychoeconomics from the same institution (2014-2017). Dr. Rebholz's research centers on quantitative methods in social cognition and judgment and decision-making (JDM). His methodological expertise spans statistics, machine/deep learning, Bayesian inference, and data science, which he applies to investigate phenomena such as judgment aggregation, wisdom of crowds, joint decision-making, advice taking, multidimensional belief updating, anchoring effects, hindsight bias, and science acceptance. A key theme in his current work is quantifying the informational influence of qualitative information—particularly that generated by large language models (LLMs)—on human judgment processes. His recent publications demonstrate a growing focus on human-AI interaction, examining how people integrate advice from generative AI systems, the reliability of various cognitive biases, and the development of quantitative models for understanding information sampling. His work often employs advanced statistical modeling techniques to address ecological constraints in real-world decision contexts, with increasing emphasis on the intersection of traditional psychological phenomena and modern AI technologies. Dr. Rebholz has taught various courses at the University of Tübingen, including 'Heuristics and Biases,' 'Introduction to Machine Learning,' 'R-Programming,' and 'Machine Learning for Data-Driven Decision-Making.' His teaching reflects his interdisciplinary approach, bridging psychology, statistics, and computational methods to equip students with practical skills for behavioral research in the digital age.

Isak RoalkvamView profile

Senior Lecturer

• Stone Age
• settlement patterns
• quantitative methods
• +3 more

Isak Roalkvam is a Senior Lecturer in Archaeology at the University of Oslo, specializing in Stone Age studies with a focus on quantitative methods and computational approaches. His research integrates geographical information systems, programming (R and Python), and open research practices to investigate settlement patterns along the Norwegian coast during the Mesolithic period, particularly addressing challenges posed by relative sea-level changes over millennia. Dr. Roalkvam's educational background includes: PhD in Archaeology (2024) from the University of Oslo MSc in Computational Archaeology: GIS, Data Science and Complexity (2019) from University College London Master's degree in Archaeology (2015) from the University of Oslo Roalkvam's research centers on the application of quantitative methods to understand Stone Age settlement patterns, particularly along the Norwegian Skagerrak coast. He specializes in shoreline dating techniques, summed probability distributions of radiocarbon dates, and the relationship between Stone Age sites and sea-level changes. His technical expertise includes developing computational tools (such as the shoredate R package), statistical modeling, and GIS analysis. He is also actively engaged in promoting open research practices within archaeology, as evidenced by his recent publications on open access publishing in the field. Analysis of Roalkvam's publication record reveals a clear methodological trajectory from theoretical development to practical application. His work consistently addresses the complex relationship between archaeological site locations and relative sea-level changes, requiring sophisticated computational approaches. The development of the shoredate R package represents a significant contribution to the field, providing researchers with accessible tools for shoreline dating. More recently, his research has expanded to examine broader issues in archaeological publishing and open science practices, demonstrating his commitment to advancing methodological rigor and transparency in the discipline. Dr. Roalkvam is actively involved in two research groups at the University of Oslo: Materialities – past and present PalaeoTECH – Social approaches to Stone Age technology

Ranxiao Frances WangView profile

Professor

• Attention and Perception
• Spatial Cognition
• Visual Perception
• +7 more

Ranxiao Frances Wang is a Professor of Psychology at the University of Illinois, with additional appointment at the Beckman Institute for Advanced Science and Technology. She holds her office in the Psychology Building and maintains an active research laboratory focused on spatial cognition and perception. Dr. Wang earned her Ph.D. from Massachusetts Institute of Technology before joining the University of Illinois faculty. Her research program spans multiple domains within cognitive psychology, particularly focusing on how humans process spatial information and attention. Her primary research interests include mind wandering and cognitive control, human-robot interaction, biologically-informed artificial intelligence, visual perception, and spatial memory. She has developed innovative methodologies to study spontaneous cognitive processes, particularly in meditation contexts, and has pioneered research on human navigation in non-Euclidean spaces. Her work bridges cognitive psychology with robotics, quantum physics, and virtual reality technologies. Analysis of her recent publications reveals a strong emphasis on the cognitive mechanisms underlying attentional states, spatial navigation in both Euclidean and non-Euclidean environments, and the application of cognitive principles to human-robot interaction. Her research consistently employs rigorous experimental methods combined with computational modeling to uncover fundamental principles of human cognition. Dr. Wang has received consistent research funding that has supported numerous graduate students and collaborative projects across disciplines. Her work has been published in top-tier journals across psychology, neuroscience, and human-computer interaction fields. She actively mentors graduate students in the Psychology Department and collaborates with faculty from multiple departments including Engineering, Computer Science, and Physics. Her laboratory maintains cutting-edge virtual reality equipment for spatial cognition research.

Jakub BijakView profile

Professor

• Statistical Demography
• Migration Modeling
• Demographic Uncertainty
• +4 more

Jakub Bijak is Professor of Statistical Demography at the University of Southampton's Department of Social Statistics and Demography, with nearly 25 years of academic and international civil service experience. He actively contributes to the Statistical Sciences Research Institute (S3RI) and Centre for Population Change, leading research at the intersection of demographic theory, statistical methodology, and policy application. His work bridges demographic science with practical migration governance challenges across European institutions. He earned his PhD in economics with specialisation in demography from the Warsaw School of Economics, establishing his foundation in quantitative demographic analysis. His doctoral research directly informs his ongoing focus on methodological innovation in population studies. Professor Bijak's research centers on statistical demography, migration modeling under uncertainty, and demographic forecasting. He pioneers agent-based simulation approaches for migration decision-making and develops Bayesian frameworks for population projection. His work spans from paleodemographic analysis of ancient populations to contemporary migration governance, with particular emphasis on quantifying uncertainty in demographic processes. Recent projects explore digital trace data for real-time migration monitoring and kinship dynamics across the life course. Analysis of his 2024-2025 publications reveals three dominant trends: (1) Methodological innovation in migration forecasting using mixed-frequency data and agent-based modeling, (2) Integration of digital footprint analysis for timely migration estimates, and (3) Development of policy-relevant frameworks for managing demographic uncertainty. His work increasingly connects demographic modeling with robotics and aging populations, demonstrating cross-disciplinary impact. No scientific awards are documented in the provided source materials. Professor Bijak currently supervises two PhD students: Andrew Peter Hind (MPhil/PhD Social Statistics) and Md Sifat Ar Salan (PhD Social Statistics and Demography). He leads or co-leads multiple major research projects including QuantMig (European Union-funded), Bayesian Agent-based Population Studies (BAPS), and ESRC/EPSRC grants on population change. His projects frequently involve international consortia addressing migration scenarios, demographic uncertainty, and generational connections. He maintains active roles in the Statistical Sciences Research Institute and Centre for Population Change, contributing to interdisciplinary teams developing the QuantMig microsimulation platform and kinship modeling frameworks. His collaborative networks span demography, computer science, and policy institutions across Europe.

Jason HiltonView profile

Associate Professor

• Demographic Forecasting
• Bayesian Statistics
• Human Mortality
• +4 more

Jason Hilton is an Associate Professor in Social Statistics at the University of Southampton's Faculty of Social Sciences, specializing in demographic methods and data science. His work bridges academic research and practical applications through collaborations with government bodies and international organizations. His research focuses on probabilistic forecasting of demographic components (mortality, fertility, migration) and kinship modeling , employing Bayesian statistics and agent-based simulation techniques. Key interest areas include demographic forecasting, human mortality analysis, and modeling intergenerational relationships. Hilton's publications reveal strong thematic continuity in demographic methodology, with recent work emphasizing kinship dynamics (2024-2025), migration flow prediction (2021), and Bayesian mortality modeling (2021). His research consistently integrates computational approaches with real-world demographic challenges. As a supervisor, he currently guides four PhD students in Social Statistics and Demography: Andrew Peter Hind (MPhil/PhD), Md Sifat Ar Salan, Shu Li, and Clara Renee Girault. His research is supported by major grants including ESRC's 'Connecting Generations' project and the Bill & Melinda Gates Foundation's WorldPop initiative. Hilton contributes to the Centre for Population Change and Demographic and Migration Modelling research groups, focusing on projects like 'Modelling kinship and quantifying connections between generations' and 'FuturePop' for high-resolution population projections.

Kenneth MalmbergView profile

Associate Professor

• Cognitive Psychology
• Human Memory
• Episodic Memory
• +7 more

Kenneth Malmberg is an Associate Professor in the Department of Psychology at the University of South Florida, within the College of Arts and Sciences. His research lies at the intersection of cognitive psychology, mathematical modeling, and human memory systems. He leads a lab focused on episodic memory, decision-making, and computational theories of cognition. PhD in Cognitive Psychology, University of Maryland (2000) NIH NRSA Postdoctoral Fellow, Indiana University (2000–2003) Dr. Malmberg's research investigates the cognitive and computational mechanisms underlying human memory. His work emphasizes mathematical and computational models to explain phenomena such as context-dependent memory, encoding and retrieval dynamics, aging effects on memory, and episodic decision-making. He integrates empirical data with formal modeling to develop unified theories of memory and cognition. His recent publications span foundational reviews, theoretical models, and empirical studies in top journals like Psychological Review , Cognitive Psychology , and Journal of Mathematical Psychology . Themes include recognition memory, frequency judgment, sequential dependencies, and the role of attention and perception in memory formation. His 2024 book, Human Memory: The General Theory and Its Various Models , represents a major synthesis of the field. Scientific recognition includes: American Psychological Association's Division 3 New Investigator Award (2004) Dr. Malmberg has been consistently supported by research funding, though specific grants are not listed. He advises graduate students in the Cognitive & Neural Sciences program and contributes to the training of future cognitive scientists. His lab continues to explore how memory representations are formed, maintained, and retrieved under varying cognitive conditions.