جست‌وجوی استاد و پژوهشگر

• Risk Management
• Risk Analysis
• Uncertainty Quantification
• +۱۲ مورد دیگر

Roger Flage is a Professor of Risk Management at the University of Stavanger, affiliated with the Faculty of Science and Technology and the Department of Security, Economics and Planning. His research focuses on foundational and applied aspects of risk analysis, uncertainty quantification, and decision-making under uncertainty, with applications in critical infrastructure, environmental systems, and offshore energy. Roger Flage's research interests lie at the intersection of risk science, safety engineering, and decision theory. He investigates how uncertainty—especially epistemic uncertainty and assumptions—affects risk assessments, and advocates for more transparent and robust frameworks. His work spans theoretical advances, such as the treatment of 'black swan' events and the concept of 'real risk', as well as practical applications in offshore safety, power systems, and geohazards. He emphasizes the integration of data-driven methods, AI, and digital twins while critically assessing their limitations and associated security risks. His recent publications show a strong trend toward integrating dynamic, data-rich, and interdisciplinary approaches to risk analysis. Themes include the role of time in risk, AI applications, infrastructure interdependencies, and environmental risk in the oil and gas sector. He frequently publishes in top-tier journals like Risk Analysis , Reliability Engineering & System Safety , and Safety Science , often in collaboration with leading scholars such as Terje Aven and Seth Guikema. No scientific awards are mentioned in the provided text. Roger Flage has supervised or collaborated with several researchers, though no formal list of advisees is provided. His work is supported through academic collaborations and institutional affiliations rather than explicit grant mentions. He is actively involved in advancing risk science methodology, particularly in the treatment of assumptions and uncertainty, and contributes to both theoretical foundations and real-world applications in safety-critical domains. He is associated with research groups and collaborative networks at the University of Stavanger, particularly within the Department of Security, Economics and Planning. His work often involves interdisciplinary teams focusing on risk in complex engineered systems, including energy, transportation, and environmental systems.

• Bayesian Statistics
• Reliability Engineering
• Risk Analysis
• +۴ مورد دیگر

Ahmad BahooToroody is an Academy Research Fellow at Aalto University’s Department of Energy and Mechanical Engineering, specializing in Bayesian statistics, reliability engineering, and risk analysis for autonomous maritime systems. He is actively involved with the Marine and Arctic Technology research group and leads projects that integrate machine learning with safety-critical applications in the maritime and offshore sectors. Research Interests Bayesian statistical methods for reliability and risk modeling Machine learning and deep learning for anomaly detection in autonomous systems Safety assessment of offshore installations and maritime operations Prognostic health management of marine renewable energy systems Human factors and expert judgment in sociotechnical maritime systems His work often incorporates advanced techniques such as Gaussian processes, LSTM-based neural networks, and dynamic Bayesian networks to address uncertainties in complex engineering systems operating in harsh marine environments. Publication Trends Across 2022–2025, BahooToroody’s publications reveal a strong trajectory toward integrating data-driven models with physics-based simulations. Dominant themes include real-time risk monitoring of autonomous ships, failure prognosis for unattended machinery, and safety assessment frameworks for offshore structures. His collaborative outputs span high-impact journals such as Reliability Engineering & System Safety and Safety Science , underscoring his leadership in maritime safety analytics. Research Groups & Labs Marine and Arctic Technology Research Group, Aalto University Academy Research Fellow network within the Department of Energy and Mechanical Engineering Doctoral Supervision & Grants While specific grant details are not listed, his role as Doctoral Candidate Supervisor since 2020 indicates active mentorship of PhD researchers. He is also the Principal Investigator on projects funded under the Academy of Finland Fellowship scheme, supporting next-generation maritime risk analytics.

• Decision Analysis
• Health Economics
• Global Health
• +۳ مورد دیگر

Dr. Abigail Colson is a Senior Lecturer in the Department of Management Science at Strathclyde Business School, University of Strathclyde. She specializes in decision and uncertainty analysis with a focus on public health, including expert judgment elicitation methods. Her work addresses global health challenges such as antimicrobial resistance (AMR) and health evaluation in low-resource settings. She holds a PhD in Management Science from the University of Strathclyde, an MPP from the University of Chicago, and a BA in political science and environmental studies from American University. Her research integrates structured expert judgment techniques to inform policy decisions, particularly in cost-effectiveness analysis, benefit-cost prioritization, and health technology assessment. Recent projects include quantifying future AMR trends, evaluating child mental health interventions, and designing antibiotic financing models. She collaborates with international organizations and governments to strengthen healthcare systems in developing countries. Key areas: AMR forecasting, global health economics, expert elicitation protocols Notable projects: EFSA EKE Training, Credible Routes to GB Electricity Collapse Study Professional roles: Principal Investigator on multiple grants, Resident Scholar at Center for Disease Dynamics Dr. Colson’s publications emphasize methodological innovations in decision-making frameworks and their application to pressing global health issues. She develops training programs for structured expert judgment and advocates for evidence-based policy across diverse sectors.

Victoria Hemmingمشاهده پروفایل

استاد مدعو

• Decision Science
• Risk Analysis
• Conservation Biology
• +۵ مورد دیگر

Victoria Hemming is an Adjunct Professor in the Department of Forest and Conservation Sciences at the University of British Columbia. She is also a Decision Analyst at Compass Resource Management and an Honorary Research Associate at the Martin Conservation Decisions Lab, UBC. Her work bridges decision science, risk analysis, and behavioral sciences to address natural resource management challenges. Education: PhD in Environmental Science and Ecology, University of Melbourne (2019); BSc (Hons) in Botany, University of Melbourne (2009); BASc in Environmental Science, Geography, and Ecology, University of Melbourne (2008) Research Interests: Victoria focuses on improving decision quality under uncertainty, overcoming data deficiencies through structured expert elicitation, and addressing the decision-implementation gap in conservation. Her work integrates Indigenous knowledge, climate change impacts, and co-benefits frameworks to enhance biodiversity outcomes. Article Trends: Recent publications emphasize expert elicitation protocols (IDEA and Classical Model), decision-making under uncertainty, ecosystem-based climate solutions, and interdisciplinary applications of decision science in conservation and urban planning. Scientific Awards 2022 Top Downloaded Article: An Introduction to Decision Science for Conservation 2020 Chancellor’s Prize for Excellence in PhD thesis 2018 Editor Recommendation: A Practical Guide to Structured Expert Elicitation Teaching & Mentorship: She co-developed UBC’s CONS440 course and led workshops on expert elicitation and decision science. Her mentorship includes PhD and Masters students working on urban forestry, marine conservation, and threat management.

Andrew Robinsonمشاهده پروفایل

استاد

• Biosecurity Risk Analysis
• Statistical Modeling
• Forest Analytics
• +۷ مورد دیگر

Andrew Robinson is a Professor at The University of Melbourne, holding dual appointments in the School of BioSciences and the School of Mathematics and Statistics. As Director of the Centre of Excellence for Biosecurity Risk Analysis (CEBRA), he leads research on statistical and risk analysis for biosecurity threats, funded by Australian and New Zealand governments. His work bridges computational tools and natural resource management, with a focus on R programming and data-driven decision-making. Co-authored 4 influential books on R programming and biosecurity Developed icebreakeR, a popular R education resource Conducts workshops for scientists and policymakers Robinson's research spans biosecurity risk modeling, invasive species management, and statistical applications in forestry. His recent work emphasizes climate change impacts on agricultural yields, adaptive sampling strategies, and Indigenous leadership in biosecurity. He maintains active collaborations in data analytics and policy development. Selected Research Trends: Current projects focus on quantitative risk prioritization, climate change adaptation, and automated surveillance systems. Key subfields include computational biosecurity, stochastic modeling, and cross-jurisdictional policy frameworks. Robinson's laboratory, CEBRA, integrates multidisciplinary approaches to biosecurity challenges. His publications demonstrate expertise in statistical ecology, risk analytics, and policy simulation. He continues to develop R-based tools for practical applications in natural resources and biosecurity.

• Behavioural Decision Making
• Risk Perception and Communication
• Decision Making Under Uncertainty
• +۴ مورد دیگر

Dr Andrea Taylor is an Associate Professor at the University of Leeds , with joint appointments in the Leeds University Business School and the School of Earth and Environment . Her work bridges cognitive psychology and behavioral decision research to address challenges in climate and weather risk communication. Co-Investigator on multiple high-impact climate service projects (e.g., Newton Fund, Met Office collaborations) Co-leads interdisciplinary initiatives like the Business and Organisations for Sustainable Societies (BOSS) Research Group and the WMO High Impact Weather Task Team Research Interests: Specializes in behavioral decision-making under uncertainty, focusing on public responses to climate and weather risks. Key areas include: Risk perception and communication Expert judgment in climate services Decision-making for climate adaptation Sustainability and consumer behavior Impact-based weather forecasting Role of emotion in risk decisions Article Trends: Recent publications emphasize the integration of behavioral science into climate services, user-centered approaches to weather warnings, and cross-cultural studies of public risk responses. Collaborations with climatologists and health economists are evident. Advising & Grants: Supervises PhD students in climate risk communication and adaptation, including Hellen Msemo, Cathrine Liontou, and Rachel Harcourt. Secured over £9 million in research funding from organizations like the Global Challenges Research Fund and the Met Office.

Geneviève Gauthierمشاهده پروفایل

استادیار

• Judgment and Evaluative Practices
• Learning Theories
• Feedback for Complex Tasks
• +۳ مورد دیگر

Geneviève Gauthier is an Assistant Professor at the University of Ottawa, jointly appointed in the Faculty of Education and the Faculty of Medicine. She serves as Director of the Graduate Diploma in Health Education within the Department of Innovation in Medical Education (DIEM). PhD in cognitive psychology from McGill University 20+ years of experience in faculty development and program evaluation Her research focuses on evaluative judgment , self-assessment , peer assessment , and the assessment of complex tasks . She investigates how clinical teachers design assessment tasks, implement pedagogical strategies, and provide feedback to students. Her work employs methodologies such as case studies, think-aloud protocols, and cognitive task analysis. Recent publications highlight her contributions to interprofessional education, syllabus design, and virtual patient assessment tools. She explores tensions in curriculum change and planetary health education integration. Her articles span topics like rater cognition, diagnostic reasoning, and technology-mediated learning environments. Notable collaborations include co-authors Christina St-Onge, Walter Tavares, and Susanne P. Lajoie. She is affiliated with ResearchGate and contributes to networks in medical education, with 24 publications and over 2,269 reads.

John McCoyمشاهده پروفایل

استادیار

• Mathematical models of judgment and decision making
• Computational cognitive science
• Crowd wisdom
• +۵ مورد دیگر

John McCoy is an Assistant Professor of Marketing at the Wharton School of the University of Pennsylvania. He is also affiliated with the Wharton Neuroscience Initiative and Penn's MindCORE hub. His academic work bridges marketing, cognitive science, and computational modeling. Dr. McCoy's research focuses on mathematical models of judgment and decision making , computational cognitive science , crowd wisdom , and forecasting . Methodologically, he uses a combination of behavioral experiments and computational modeling, drawing on ideas and techniques from psychology, economics, marketing, Bayesian statistics, and computer science. Much of his current work centers on better ways to aggregate judgments from multiple individuals, including in situations where the majority may be wrong and the truth may be unverifiable. His research has gained significant attention, with popular accounts appearing in the Wall Street Journal , NPR , and the New Yorker . A key contribution is the "surprisingly popular answer" method for extracting wisdom from crowds, which selects not the "most popular" answer but the "surprisingly popular" one by eliciting both answers and predictions about others' answers. Dr. McCoy teaches graduate courses including Consumer Research Topics and Marketing Management. His teaching focuses on contemporary topics in consumer research, drawing from marketing, psychology, and economics literature to help students develop research ideas and understand theoretical and methodological approaches to consumer behavior. His scholarly work spans multiple domains including crowd wisdom, individual-level decision making, semantic cognition, and graph theory. His research has important applications in marketing, healthcare communication, and forecasting methodologies.

Martine J. Baronsمشاهده پروفایل

استاد

• Decision Making Under Uncertainty
• Structured Expert Judgment
• Food Security
• +۳ مورد دیگر

Martine J. Barons is a Professor in Statistics and Director of the Applied Statistics & Risk Unit (AS&RU) at the University of Warwick. Her research focuses on decision-making under uncertainty, structured expert judgment, and their applications in food security, pollination, digital archives, and the energy sector. She holds roles in knowledge exchange and policy advisory, including membership in the Institute of Mathematics and its Applications (IMA) committees and the Academy for Mathematical Sciences advisory board. Her work integrates interdisciplinary collaborations with institutions like Melbourne University and Monash University. Key areas include developing decision support systems for complex societal challenges, such as pollinator conservation and climate risk communication. She advocates for public engagement through radio, TV, and educational outreach, aiming to demystify mathematics for broader audiences. Barons has secured grants from EPSRC, STFC, and industry partners. Her contributions include advancing Bayesian network methodologies and promoting ethical digital twin strategies. Awards include Chartered Mathematician status and Fellowship of the IMA.

Mary Malinaمشاهده پروفایل

استاد

• Management Control Systems
• Performance Measurement
• Subjective Performance Evaluation
• +۱ مورد دیگر

Mary Malina is Professor and Interim Director in the Accounting department at the CU Denver Business School, University of Colorado Denver. Her research specializes in management control systems, performance measurement, and subjectivity in performance evaluation. She holds a PhD in Accounting from the University of Colorado Boulder, an MBA from Butler University, and a BBA in Accounting from Saint Mary's College. Dr. Malina serves as Editor for Advances in Management Accounting (2014–2019) and has published extensively in top-tier journals including The Accounting Review , Journal of Management Accounting Research , and Management Accounting Research . Her work explores how behavioral economics and subjective assessment influence organizational performance frameworks, with recent investigations into research relevance metrics, incentive design, and diversity in methodological approaches. Key research themes include: Integration of psychological insights into accounting control systems Sectoral transferability of performance measurement innovations Longitudinal analysis of balanced scorecard evolution Dr. Malina received the 2012 Outstanding Paper Award from Qualitative Research in Accounting & Management and Best Paper of 2005 from Management Accounting Research . She maintains active research collaborations examining turnover impacts, contractual risk mitigation, and pedagogical effectiveness in accounting education.

Phil Tetlockمشاهده پروفایل

استاد

• Political Science
• Decision Science
• Forecasting
• +۳ مورد دیگر

Phil Tetlock is the Leonore Annenberg University Professor in Democracy and Citizenship at the University of Pennsylvania, holding professorships in Management (Wharton School), Psychology (School of Arts & Sciences), and a secondary appointment in Political Science. His work bridges decision-making, forecasting, and interdisciplinary collaboration. He is renowned for research on expert judgment accuracy, adversarial collaboration, and AI applications in prediction. Tetlock’s recent focus includes improving forecasting methodologies through machine learning and mitigating cognitive biases in geopolitical analysis. Research interests emphasize decision science, political psychology, and the intersection of technology with human judgment. Notable contributions include developing forecasting proficiency tests and analyzing the efficacy of adversarial collaboration in behavioral science. His work often addresses societal challenges like existential risk assessment and scientific censorship. Publications highlight trends in AI-driven forecasting, geopolitical prediction accuracy, and ethical dilemmas in research. Tetlock advocates for robust accountability systems in intelligence analysis and policy-making, emphasizing calibration of confidence and depolarization of attitudes through structured debate.

• Uncertainty Quantification
• Aero-Engine Design
• Bayesian Methods
• +۳ مورد دیگر

Bogdan Profir is an Assistant Professor at the CEES School of Engineering, University of Southampton. His research focuses on uncertainty quantification, Bayesian methods, and aero-engine design optimization. He holds a Doctoral Thesis from the University of Southampton (2020) and has contributed to advancements in turbine component analysis and computational modeling. Research interests include model validation, turbine disc reliability, and probabilistic approaches to engineering challenges. His work bridges theoretical frameworks with practical applications in aerospace and mechanical engineering. Publications highlight themes like Bayesian networks for expert judgment updating and Markov Chain Monte Carlo methods for material analysis. While no awards are explicitly mentioned, his contributions reflect active engagement in high-impact technical domains. No advising or grant details are provided in the text. His academic trajectory emphasizes methodological innovation in turbomachinery and materials systems.

John Quigleyمشاهده پروفایل

استاد

• Risk Modeling
• Decision Support Systems
• Bayesian Networks
• +۵ مورد دیگر

John Quigley is a Professor of Management Science at the University of Strathclyde, serving as Vice Dean (Research) of the Strathclyde Business School since 2021. Previously, he was Head of the Management Science Department (2016–2019). He holds a BMath in Actuarial Science from the University of Waterloo (1993) and a PhD in Management Science from the University of Strathclyde (1998). His research focuses on risk modeling and decision support systems, integrating data analysis and expert judgment. Key areas include large-scale manufacturing, offshore windfarm maintenance, and search and rescue (SAR) operations in Arctic regions. Notable projects include the NNSAR initiative (funded by NERC and NRC), enhancing SAR systems in Nunavut and Nunavik, and the Productivity and Sustainability Management project optimizing manufacturing processes via real-time data and probabilistic networks. He collaborates with industries like Rolls-Royce, Scottish Power, and the European Food Safety Agency. Quigley has received awards such as the FAIM 2025 Sullivan Best Paper Award and the 2010 KTP Award. His teaching spans undergraduate, postgraduate, and executive education programs globally, emphasizing technology integration in pedagogy.