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Pascal HaegeliView profile

Associate Professor

• Avalanche Safety Research
• Natural and Social Sciences Interface
• Risk Analysis
• +5 more

Dr. Pascal Haegeli is an Associate Professor at the School of Resource & Environmental Management at Simon Fraser University (SFU), where he serves as Undergraduate Program Chair. His interdisciplinary research bridges natural and social sciences to advance avalanche safety through evidence-based tools and frameworks. Affiliation: School of Resource & Environmental Management, SFU Academic Rank: Associate Professor Contact: pascal_haegeli@sfu.ca His work integrates atmospheric science, snow science, risk analysis, decision-making theory, and public health to enhance safety in avalanche-prone environments. Key contributions include developing the Avaluator decision aid, redesigning Canadian avalanche information exchange protocols (InfoEx), and pioneering research on avalanche airbag efficacy. Scientific publications highlight his focus on avalanche hazard modeling, terrain assessment, and recreational risk behavior. While specific grants aren't detailed in the text, his leadership in avalanche safety research suggests extensive funding support. Dr. Haegeli collaborates with international stakeholders and maintains strong ties to Canadian avalanche safety organizations.

• Human Memory
• Cognitive Psychology
• Short-Term Memory
• +4 more

Dr. Marie Poirier is a Lecturer in the Department of Psychology at City, University of London , where she has taught since 2001. She previously served at Sherbrooke University and Laval University in Canada, directing the Cognitive Psychology Research Laboratory before establishing the Memory Research Unit (now Human Memory Research Group) at City. Her work focuses on human memory , particularly short-term memory, retrieval mechanisms, and memory in special populations. Education: PhD in Psychology from Laval University (1989), Quebec, Canada Research interests span cognitive psychology, memory over short and long terms, semantic networks, and determinants of successful retrieval. She collaborates internationally with institutions in the UK, US, Canada, and Australia. Her research has been funded by the Natural Sciences and Engineering Research Council of Canada , British Academy , and Economic and Social Research Council (UK) . Recent publications examine animacy effects in memory , production effect in recall , nonepisodic autobiographical memory , and visuospatial working memory . Her 2024 study in Psychology and Aging challenges assumptions about cognitive decline in older adults, linking narrative differences to communicative preferences rather than memory deficits. Professional activities include serving as an Associate Editor for Memory . She teaches modules like Cognitive Approaches to Mind and Behavior (PS1003) and Memory: Trends and Issues (PS3004) at the undergraduate level, and Contemporary Issues in Psychological Research (PSM511) at the postgraduate level.

• Database Systems
• Natural Language Processing
• Data Mining
• +4 more

Hongrae Lee is a researcher specializing in database systems, natural language processing, and data mining. His work bridges structured data management with language models, focusing on tasks like natural language to SQL translation, similarity joins, and efficient data processing. His research interests include: Database query optimization and similarity search Language model applications for text generation and hallucination correction Web data curation and structured data ecosystems Cloud storage optimization and distributed systems Hongrae Lee's recent publications (2022-2023) highlight trends in large language models (LLMs) for dialogue applications, attributed text generation, and acronym disambiguation with weak supervision. Earlier work (2016-2007) established foundational techniques in database scalability, LSH-based similarity estimation, and geographical data thinning. He has collaborated extensively with researchers at institutions like Google, Seoul National University, and University of British Columbia on projects such as WebTables, LaMDA, and Google Fusion Tables. His contributions span both theoretical advancements (e.g., variance-aware query optimization) and practical systems (e.g., CloudRAMSort, T5-based disambiguation).

Gregory WheelerView profile

Professor

• Probability
• Bayesian Statistics
• Machine Learning
• +7 more

Gregory Wheeler is a Professor of Philosophy and Computer Science at the Frankfurt School of Finance & Management , where he serves as Head of the Computational Science & Philosophy Department and Academic Director of the Master of Applied Data Science program. He earned a joint PhD in Philosophy and Computer Science from the University of Rochester in 2002 and has held faculty positions at institutions including LMU Munich, Carnegie Mellon University, and Nova University of Lisbon. In 2019, he co-founded Exaloan AG , a FinTech company in Frankfurt, where he acts as CTO and Head of AI & Machine Learning. Wheeler's research focuses on probability theory and statistics , with emphasis on imprecise probability , applied Bayesian statistics , and machine learning . His work bridges formal epistemology with computational methods, examining rational acceptance, belief revision, and uncertainty modeling. His publications span topics in statistical mechanics , formal logic , and cognitive psychology , reflecting his interdisciplinary approach. Recent works include analyses of high-dimensional loss landscapes in neural networks and philosophical inquiries into peer disagreement resolution through probabilistic frameworks.

O. Arda VanliView profile

Professor

• Quality Engineering
• Statistics
• Time Series Analysis
• +5 more

O. Arda Vanli is a Professor in the Industrial and Manufacturing Engineering Department at the FAMU-FSU College of Engineering, jointly operated by Florida A&M University and Florida State University. His research bridges applied statistics, quality engineering, and data analytics to solve critical problems in manufacturing reliability, disaster resilience, and infrastructure safety. Education: Ph.D. in Industrial Engineering and Operations Research, Pennsylvania State University (2007) M.S. in Mechanical Engineering, Pennsylvania State University (2000) B.S. in Mechanical Engineering, Middle East Technical University (1998) Research Focus: Dr. Vanli specializes in variation reduction in manufacturing processes using statistical process control and feedback adjustment strategies. His work on uncertainty quantification addresses errors in computer models for composite manufacturing and wind energy systems, while his condition monitoring research develops sensor-based methods for damage identification using ultrasonic waves and piezoelectric sensors. Recent projects integrate spatiotemporal modeling with disaster response during hurricane-pandemics. Publication Trends: His 2023-2025 publications reveal a strategic pivot toward interdisciplinary applications, combining transportation engineering, epidemiology, and materials science. Key themes include connected vehicle data for evacuation planning, Bayesian risk models for low-probability high-consequence events, and nanomaterial interfacial analysis under extreme conditions—demonstrating consistent methodological rigor in statistical modeling. Scientific Recognition: Air Force Research Laboratory (AFRL) Summer Faculty Fellowship Program (SFFP) award (2019) Air Force Research Laboratory (AFRL) Summer Faculty Fellowship Program (SFFP) award (2020) Air Force Research Laboratory (AFRL) Summer Faculty Fellowship Program (SFFP) award (2021) Research Leadership: Funded by NSF, NOAA, and Florida DOT, Dr. Vanli directs projects on risk assessment for infrastructure resilience and pandemic-disaster response systems. His role as former Director of Graduate Studies (2012-2016) underscores active mentorship in graduate education, with recent work emphasizing data-driven decision frameworks for public safety. Technical Teams: He leads research groups developing statistical frameworks for sensor networks in manufacturing and infrastructure, focusing on real-time reliability prediction and adaptive maintenance protocols through collaborations with transportation and energy sectors.

• Artificial Intelligence
• Machine Learning
• Explainable AI
• +5 more

Amir-Hossein Karimi is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Waterloo and a Faculty Affiliate at the Vector Institute. His research focuses on trustworthy human-AI collaboration, including causal inference, algorithmic recourse, and explainable AI. He holds a PhD from ETH Zurich and prior industry experience at Meta, Google Brain, and DeepMind. Education: PhD (ETH Zurich, 2023), MMath (UWaterloo, 2018), BEng (UofT, 2015) Research interests include advancing AI systems that recover from errors, evaluating AI safety/ethics, and combining human-machine strengths. His work spans causal inference, counterfactual explanations, and program synthesis. Recent articles emphasize causal perspectives in fairness, adversarial robustness, and scalable recourse mechanisms. His publications appear in top venues like NeurIPS, ICML, and AAAI. Awards: Google PhD Fellowship (2021), NSERC Scholarship (2018) Teaching: ECE 457B and ECE 657 since 2024. Advises graduate students in AI ethics, causal ML, and human-AI teaming.

Derek KoehlerView profile

Professor

• Cognitive Psychology
• Judgment and Decision Making
• Social Psychology
• +7 more

Derek J. Koehler is a Professor and Cognitive Research Area Head at the University of Waterloo. His research focuses on cognitive processes underlying judgment, decision-making, and reasoning, with particular attention to biases in political communication, gambling behavior, and metacognition. He holds an email address at derek.koehler@uwaterloo.ca and is located in PAS 4050 on campus. Key research themes include: Partisan language effects on audience perceptions and reputational outcomes Cognitive biases in gambling contexts and interventions to reduce them Illusion of explanatory depth and knowledge calibration Interactions between human judgment and algorithmic systems Role of cognitive reflection in moral and religious beliefs Communication strategies for pandemic-related information His work bridges cognitive psychology with applied domains like public health, political science, and behavioral economics. Notable contributions include developing icon array visualization techniques for gambling risk communication and analyzing framing effects in algorithmic error perception. His research consistently addresses real-world decision-making challenges through rigorous experimental methods. Recent work explores: Reputational impacts of partisan communication choices Metacognitive deficits in distributed knowledge environments Psychological barriers to evidence acceptance during crises Long-term consequences of sunk cost fallacies in moral judgments Dr. Koehler has collaborated extensively on interdisciplinary projects, including international surveys on pandemic responses and experimental studies on belief systems. His work frequently appears in top journals like Cognition and Journal of Experimental Psychology .

Marco RagniView profile

Adjunct Professor

• Cognitive Modeling
• Human Reasoning
• Neurocognitive Processes
• +5 more

Marco Ragni is an Adjunct Professor at the Department of Psychology, Albert-Ludwigs-University Freiburg, and reachable at TU Chemnitz. He holds a DFG-Heisenberg Fellowship and is associated with multiple institutions including Justus-Liebig-University Giessen and the BrainLinks-BrainTools Cluster of Excellence. His research focuses on cognitive modeling, spatial reasoning, and neurocognitive processes, with expertise in AI, epistemic possibilities, and human reasoning mechanisms. Research interests include predictive modeling of higher-level cognition, knowledge representation, and the neural correlates of reasoning. He leads DFG-funded projects such as 'Neuro-cognitive Theory of Reasoning' and 'FADE' within the SPP 1921 initiative. His work bridges formal logic and cognitive psychology, with contributions to conditional reasoning, syllogistic tasks, and model-based approaches. As an editor of the KI-Journal and chair of the SIG Cognition in the German AI Society (GI), he promotes interdisciplinary research. His educational background includes PhDs in Cognitive Science and Computer Science from Freiburg, with habilitation in Psychology, Cognitive Science, and Mathematics. Teaching roles include seminars on machine learning and spatial cognition modeling. Scientific awards include the prestigious DFG-Heisenberg Fellowship (2015). Ongoing research explores AI ethics, cognitive systems, and the integration of human-like reasoning into artificial intelligence frameworks.

Olivier RioulView profile

Professor

• Information Theory
• Cryptography
• Side-Channel Security
• +4 more

Olivier Rioul is a Professor at Télécom Paris, part of Institut Polytechnique de Paris, where he leads the Mathematics of Information and Communications (MIC) research team within the Information Processing and Communication Laboratory (LTCI) in the Department of Communications and Electronics (Comelec). His research focuses on fundamental limits in communication networks and developing methods to overcome them. Research Interests: Rioul's work spans information theory, cryptography, side-channel security, signal processing, and human-computer interaction. Key areas include entropy analysis, side-channel attack methodologies, information-theoretic models for human movement (e.g., FITTS' law), and coding theory for secure systems. Publication Trends: His recent articles (2018-2025) demonstrate strong interdisciplinary integration, with theoretical foundations in information inequalities and entropy measures applied to practical domains like cryptographic hardware security and human-performance modeling. Approximately 70% of recent works involve side-channel analysis or information-theoretic security, while 30% focus on human-computer interaction and mathematical foundations. Laboratory Leadership: He directs the MIC team specializing in mathematical frameworks for communication security and information processing. The group collaborates extensively with cybersecurity experts to translate theoretical advances into practical hardware protections.

• Manufacturing Engineering
• Laser Welding
• Digital Twin Technology
• +6 more

Wang Wei is a researcher at the University of Skövde's School of Engineering Science. His work spans multiple domains including manufacturing processes, laser welding, digital twin applications, and sustainable supply chain strategies. Key affiliations: University of Skövde, The Virtual Systems Research Centre, SYMBIO-TIC project, VF-KDO project Collaborations with institutions: Nanjing University of Aeronautics and Astronautics, Innovation Fund Denmark, Vinnova Research interests focus on: Advanced manufacturing techniques (machining deformation prediction, thin-walled part optimization) Laser welding process improvement (porosity reduction, dissimilar material joints) Digital twin security frameworks for cyber-physical systems Green technology adoption and sustainable supply chain coordination Recent publications demonstrate expertise in: Neural operator applications for manufacturing Multi-objective optimization in machining Cybersecurity modeling for industrial systems Environmental economics and consumer behavior analysis Co-funded by: Knowledge Foundation (SIMPLE, VF-KDO projects) Vinnova (QWELD, LaserBATMAN projects) EU H2020 SYMBIO-TIC M-ERA.NET 3 call

Rachel WarnockView profile

Professor

• Phylogenetics
• Paleobiology
• Bayesian Inference
• +3 more

Professor Rachel Warnock leads the Systems Paleobiology research group at the GeoZentrum Nordbayern , part of Friedrich-Alexander University Erlangen-Nuremberg (FAU). Her work bridges paleontological and molecular data through advanced phylogenetic methodologies. Develops Bayesian phylodynamic frameworks Specializes in fossil data integration Focus on speciation/extinction processes Recent publications emphasize Bayesian phylogenetic inference , fossilized birth-death modeling , and macroevolutionary analysis across biological and cultural systems. She co-authored the FossilSim and FossilSimShiny packages for fossil occurrence simulation. Her research team includes collaborators from computational biology, paleontology, and evolutionary ecology domains, operating within FAU's Paleontology Department .

Luca SpalazziView profile

Associate Professor

• Computer Science
• Cybersecurity
• Blockchain Technology
• +5 more

Luca Spalazzi is an Associate Professor at the Department of Information Engineering , Università Politecnica delle Marche , Italy. His research spans multiple domains including cybersecurity , blockchain technology , machine learning , and telerehabilitation systems for Parkinson's disease. He applies formal methods to software verification and security analysis, with a focus on real-time systems and distributed architectures . Key research areas: Cybersecurity, Blockchain, Machine Learning, IoT, Formal Verification Recent work: Blockchain-based sustainable supply chains, Zero-Knowledge Proofs, Smartphone health monitoring His publications (2013-2025) demonstrate expertise in malware detection , smart contract verification , and AI-driven health solutions . Articles include BRAIN 2024 workshop organization and RAPIDO system for Parkinson's telerehabilitation.

James A. FosterView profile

Professor

• Computational Biology
• Evolutionary Algorithms
• Neural Networks
• +2 more

James A. Foster is a University Distinguished Professor of Biology in the Department of Biological Sciences at the University of Idaho. His research spans computational biology, evolutionary algorithms, and stochastic modeling. Key interests include neural ODE optimization, high-order SDE solvers, microbiome influences on health, and viral evolution modeling. Recent computational work focuses on improving efficiency and accuracy in stochastic simulations. Applications extend to pediatric nutrition (INSPIRE study), sepsis diagnostics, and COVID-19 variant analysis. Biological investigations cover gamete preparation and fertilization mechanisms.

• Conservation Biology
• Biodiversity Protection
• Environmental Policy
• +6 more

Ben Earle is a Contract Instructor at the Faculty of Engineering and Design, Carleton University. His research focuses on conservation biology, biodiversity protection, and environmental policy, with an emphasis on systematic conservation planning, ecological connectivity, and freshwater ecosystems. He actively explores the integration of community science data into conservation decision-making and evaluates the effectiveness of conservation actions for imperiled species. Key research interests include the impacts of climate change on species distribution, the role of cities in biodiversity conservation, and the challenges in assessing environmental governance systems. He has contributed to developing the prioritizr R package for conservation prioritization and emphasized the importance of participatory science in bridging knowledge-action gaps. His work consistently highlights emerging threats to Arctic biodiversity, the optimization of ecological surveys, and the need for evidence-based policy frameworks. He advocates for interdisciplinary approaches that combine spatial analysis, policy evaluation, and stakeholder engagement to address biodiversity loss and habitat fragmentation challenges.

Carolina Feher da SilvaView profile

Lecturer

• Cognitive Psychology
• Decision-Making
• Neuroimaging
• +3 more

Dr Carolina Feher da Silva is a Lecturer in Psychology at the University of Surrey's School of Psychology. Her research focuses on decision-making in humans, employing methods such as behavioral experiments, computational modeling, eye-tracking, and neuroimaging. She is affiliated with the Cognitive Psychology research group and the Institute for Sustainability. Dr da Silva's work bridges cognitive psychology with sustainability, emphasizing interdisciplinary approaches to understanding human behavior. Her research interests are centered on model-based and model-free learning strategies, particularly in two-stage decision tasks. She explores how mental effort and neural mechanisms (e.g., striatal prediction errors) influence decision-making processes. Her publications often highlight the dominance of model-based reasoning in complex tasks, challenging traditional reinforcement learning paradigms. Dr da Silva has contributed to open science initiatives, including the Open Library of Bioscience and the development of the neat-python computational tool. Her work has been recognized through her fellowship at the Institute of Sustainability, reflecting her commitment to integrating environmental and social dimensions into cognitive research. Her research has been published in high-impact journals like Nature Human Behaviour , with a focus on experimental psychology, computational modeling, and neuroscientific insights. Collaborations with global researchers underscore her role in advancing interdisciplinary cognitive science.