جستجوی استاد راهنمای دانشگاهی

Thomas Le Barbanchonمشاهده پروفایل

استاد

• Labor Economics
• Public Finance
• Econometrics
• +۵ مورد دیگر

Thomas Le Barbanchon is a Full Professor of Economics at Bocconi University since 2025 and holds the Rodolfo Debenedetti Chair in Labor Economics. He received his PhD from Ecole Polytechnique (CREST-ENSAE) in 2012 and has been affiliated with institutions like CEPR, CREST, J-PAL, LEAP, BIDSA, IGIER, IZA, and IFS. His research focuses on labor economics, particularly job search mechanisms, unemployment insurance effects, gender disparities, and labor market policy evaluation. Educational background: PhD in Economics (Ecole Polytechnique), MSc in Economics (Universitat Pompeu Fabra), Diplôme d'ingénieur statisticien-économiste (ENSAE), and Diplôme d'ingénieur (Ecole Polytechnique) Research highlights include: Quantifying the impact of unemployment insurance reforms in France Analyzing gender differences in job search behavior Studying the effectiveness of hiring credits during economic crises Investigating how traditional AI improves job matching Examining migrant-native job search segregation patterns Scientific contributions appear in top journals like American Economic Journal: Applied Economics , Quarterly Journal of Economics , and Review of Economic Studies . Awards include two ERC grants (2017 & 2024) and the Bocconi Impact Award (2022). He mentors PhD students in economics and labor policy, currently serves as Director of IGIER research center, and maintains active editorial roles at Review of Economic Studies and Journal of the European Economic Association .

• Finance
• Portfolio Management
• Financial Econometrics
• +۳ مورد دیگر

Nathan Lassance is a Lecturer at the Louvain School of Management (LSM), Université catholique de Louvain (UCLouvain), and a member of the Louvain Finance (LFIN) research division. His work bridges financial theory, statistical modeling, and data-driven portfolio optimization, with a focus on addressing parameter uncertainty and improving risk-return tradeoffs in asset allocation. Research Interests: Portfolio management, covariance matrix estimation, financial econometrics, risk analysis, quantitative finance, and non-Gaussian return distributions. Publications: His recent work explores shrinkage methods for high-dimensional portfolio selection, sentiment-aligned covariance matrices, and the economic value of statistical metrics like mean squared error. He has also contributed to understanding the limitations of factor-based mispricing models and the statistical properties of mean-variance portfolios. Labs/Teams: Affiliated with the Louvain Institute of Data Analysis and Modeling (LIDAM) and the Louvain Finance (LFIN) group.

• Cross-cultural psychology
• Psychology
• Political self-enhancement
• +۴ مورد دیگر

Magdalena Żemojtel-Piotrowska is a Professor at the Faculty of Christian Philosophy of Cardinal Stefan Wyszyński University. Her research focuses on cross-cultural psychology, political self-enhancement (particularly narcissism and entitlement), subjective well-being, and beliefs about the social world. She has contributed extensively to understanding the psychological mechanisms underlying cultural differences, pandemic-related behaviors, and the interplay between personality traits and societal attitudes. Her work integrates quantitative methodologies with cross-cultural perspectives, analyzing constructs such as the Dark Triad, collective narcissism, and spiritual transcendence. Key areas include measurement invariance of psychological scales across cultures, the role of entitlement in interpersonal dynamics, and the psychological impacts of global crises like the COVID-19 pandemic. Publications highlight themes such as narcissism’s relationship with war attitudes, psychedelic use, and pandemic stress responses. She collaborates internationally, evidenced by her 59 publications and h-index scores of 17 (Scopus) and 19 (Web of Science). Her research emphasizes validating psychological theories across diverse populations while addressing contemporary societal challenges. Dr. Żemojtel-Piotrowska maintains an active academic presence through her institutional homepage and ORCID profile, emphasizing accessible communication via email. Her contributions bridge theoretical psychology with applied research, offering insights into how cultural, personality, and value systems shape human behavior globally.

Yehuda Baruchمشاهده پروفایل

استاد

• Career studies
• HRM
• International/global HRM
• +۲ مورد دیگر

Yehuda Baruch is Professor of Management at Southampton Business School, University of Southampton, UK, and Affiliated Professor at Audencia, Nantes France. With over 175 refereed papers, six books, and approximately 50 book chapters, his scholarly impact is substantial with over 30,000 Google Scholar citations and an H-index of 84. Baruch earned his DSc from Technion, Israel, and completed postdoctoral work at City University and London Business School. His academic journey includes significant leadership roles such as Vice-president Research of the European Academy of Management (2016-2019), Associate Editor of Human Resource Management, and Editor of multiple prestigious journals. He is currently Dean of the Peer Review College at the British Academy of Management and Consulting Editor for the Journal of International Business Studies. Professor Baruch's research centers on Human Resource Management and Organizational Studies, with particular emphasis on career development and global HRM practices. His work explores how geographical location impacts career success, career ecosystems in higher education, future workplace scenarios, and the integration of AI in HRM. He has made significant contributions to understanding working from home dynamics following the pandemic and has examined gender-based discrimination across cultural contexts in the UK and Pakistan. His recent publications reveal a strong methodological rigor combined with theoretical innovation, particularly in sampling strategies and career ecosystem frameworks. Baruch's work consistently bridges academic theory with practical organizational applications across global business environments, demonstrating exceptional interdisciplinary reach. Fellow of the Academy of Social Sciences Fellow of the British Academy of Management Cooper Medal for Outstanding Contribution and Leadership (2020) Top 50 globally in business & management studies Top 2% of global highly cited scholars Hughes Lifetime Scholar Award (2024) Professor Baruch has supervised 28 PhD students (7 current, 21 completed), with 14 holding academic positions internationally across multiple continents. His research has attracted substantial funding totaling £1,171,000, including significant grants from UKRI (ESRC) for pandemic-related working from home research and from the UK Art Council for entrepreneurial careers of artists. He has served on editorial boards for 14 major journals and held multiple leadership positions in professional associations. Baruch is actively involved in multiple research centers at Southampton including the Centre for Inclusive and Sustainable Entrepreneurship and Innovation, Centre for Research on Work and Organisations, and Centre for Democratic Futures. His collaborative research spans international boundaries, connecting scholars across continents to address contemporary organizational challenges in an increasingly globalized business environment.

Lori Graham-Bradyمشاهده پروفایل

استاد

• Stochastic finite element methods
• Probabilistic mechanics
• Stochastic simulation of material properties
• +۵ مورد دیگر

Lori Graham-Brady is a Professor in the Department of Civil and Systems Engineering at Johns Hopkins University's Whiting School of Engineering. She serves as Vice Dean for Faculty and directs the Center on AI for Materials in Extreme Environments (CAIMEE), while also holding secondary appointments in Mechanical Engineering and Materials Science and Engineering. Her research focuses on stochastic mechanics, multiscale modeling, and machine learning applications for understanding material variability under extreme conditions. Research areas include probabilistic mechanics, AI-driven materials design, and fragmentation modeling. Leadership roles: Director of CAIMEE, former Director of Center for Materials in Extreme Dynamic Environments, founding Director of HT-MAX, and founding Associate Director of HEMI (2012-2024). Education: PhD in Civil Engineering and Operations Research from Princeton University. Her recent work emphasizes AI for multiscale mechanics, error propagation in material characterization, and digital microstructure generation. Publications highlight stochastic modeling of ceramics, composites, and metals under impact and high-strain-rate loading. Scientific awards include the Presidential Early Career Award, Huber Civil Engineering Research Prize, and Fellowships in ASCE EMI and USACM. She led NSF IGERT programs and serves as Associate Editor for the ASCE Journal of Engineering Mechanics.

Fabrizio Riguzziمشاهده پروفایل

استاد

• Logic Programming
• Statistical Relational Artificial Intelligence
• Probabilistic Logic Programming
• +۳ مورد دیگر

Fabrizio Riguzzi is a Full Professor at the Department of Mathematics and Computer Science of the University of Ferrara, Italy. His academic career spans over two decades at the same institution, having served as Associate Professor (2014-2020) and Assistant Professor/Ricercatore (1999-2014). He is an active researcher in the fields of Logic Programming and Statistical Relational Artificial Intelligence with numerous publications and leadership roles in international conferences. His educational background includes: PhD in Electronic and Computer Engineering from the University of Bologna (1999) Laurea in Computer Engineering from the University of Bologna (1995) Riguzzi's research focuses on probabilistic approaches to artificial intelligence, particularly probabilistic logic programming and statistical relational AI. His work bridges symbolic reasoning with probabilistic methods, developing frameworks for uncertain knowledge representation and reasoning. He has made significant contributions to probabilistic answer set programming, neuro-symbolic integration, and applications in areas like network intrusion detection and knowledge graph completion. His research demonstrates how logical formalisms can be enhanced with probabilistic reasoning to tackle real-world problems with uncertainty. An analysis of his recent publications reveals a strong trend toward integrating neural and symbolic approaches in AI, with significant work on probabilistic answer set programming frameworks. His research spans theoretical foundations of probabilistic logic programming, practical implementations, and applications in cybersecurity, knowledge graphs, and decision-making under uncertainty. The interdisciplinary nature of his work connects computer science theory with practical AI applications. His notable awards include: Alain Colmerauer 10-Year Test-of-Time Award at ICLP 2021 Best Paper Award for "BUNDLE: A Reasoner for Probabilistic Ontologies" at RR-2013 Highly Commended Paper Award for "Probabilistic declarative process mining" at KSEM 2010 Riguzzi has supervised several PhD students to completion, including Elena Bellodi, Riccardo Zese, and Giuseppe Cota, who have gone on to win prestigious awards for their theses. He has served in numerous editorial roles, including Associate Editor of the Journal of Artificial Intelligence Research and Editor in Chief of Intelligenza Artificiale. His leadership extends to organizing major conferences like ILP 2018 and serving on program committees for top AI venues including IJCAI, AAAI, and ECAI. He is a member of the ML@unife research group and has developed several online systems including cplint, TRILL, and an Online AUC calculator. His work has fostered collaborations across the AI research community, particularly in the areas of probabilistic logic programming and neuro-symbolic AI.

Li Chenمشاهده پروفایل

استاد

• Conversational AI
• Explainable AI
• Recommender Systems
• +۷ مورد دیگر

Professor Li Chen is a full Professor and Associate Head (Research) in the Department of Computer Science at Hong Kong Baptist University (HKBU), with an affiliate appointment at the Academy of Wellness and Human Development. She leads the Positive Intelligence Lab , focusing on intelligent technologies for human well-being. Her research spans conversational AI, explainable AI, recommender systems, and human-computer interaction. Education: PhD in Computer Science, Swiss Federal Institute of Technology in Lausanne (EPFL), Switzerland (Nominee for Best PhD Thesis Award) Master in Computer Software and Theory, Peking University, China Bachelor in Computer Science, Peking University, China Her research interests revolve around personalized conversational and explainable AI, with applications in entertainment, education, e-commerce, and mental well-being. She has published over 150 papers in top venues including ACM TOIS, IJHCS, CHI, SIGIR, AAAI, RecSys, and UMAP . Her work has been recognized with awards such as the RecSys Best Student Paper Award (2024), CHI Honourable Mention (2022), and multiple best paper awards at UMAP and UMUAI. The most recent publications reflect a strong trend toward fair, explainable, and user-centric recommender systems , with increasing integration of large language models , mental health applications , and conversational agents . Her research emphasizes user feedback, negative sampling techniques, and evaluation frameworks grounded in real user behavior. Scientific Awards & Recognition: President’s Award for Outstanding Performance in Teaching (Individual), HKBU (2024/25) President’s Award for Outstanding Performance in Research Supervision (2022/23) World’s Top 2% Most-Cited Scientists, Stanford University (2021–2024) ACM Senior Member (2015) RecSys’24 Best Student Paper Award CHI’22 Honourable Mention Award UMAP’20 Best Student Paper Award UMUAI 2018 Best Paper Award THE Awards Asia 2021 Excellence and Innovation in the Arts (Co-I) Professor Chen is actively involved in mentoring PhD and Master’s students such as Wanling Cai and Yuhan Zhao, who have co-authored award-winning papers. She has secured research funding through grants like the HKBU IRCMS Project. Her editorial leadership includes serving as Co-Editor-in-Chief of ACM Transactions on Recommender Systems (TORS) , Associate Editor for ACM TiiS , and Editorial Board Member for UMUAI . She has chaired major conferences including ACM RecSys’23 (General Co-Chair), RecSys’20 (Program Co-Chair), and UMAP’18 (Program Co-Chair). She leads the Positive Intelligence Lab , which conducts interdisciplinary research on AI for well-being. The lab has developed datasets like the Intent Annotation of Recommendation Dialogue (IARD) and focuses on user-centric AI design, mental health chatbots, and personalized recommendation interfaces.

Chen-Yu Weiمشاهده پروفایل

استادیار

• Interactive Machine Learning
• Reinforcement Learning
• Robust Learning Algorithms
• +۵ مورد دیگر

Chen-Yu Wei is an Assistant Professor in the Department of Computer Science at the University of Virginia. He holds a Ph.D. from the University of Southern California (2022), and M.S. and B.S. degrees from National Taiwan University (2015, 2012). His research focuses on interactive machine learning, emphasizing robust and adaptive algorithms for non-stationary/adversarial environments, sample-efficient reinforcement learning, and decentralized multi-agent systems. Education: Ph.D., Computer Science, University of Southern California, 2022 M.S., Electrical Engineering, National Taiwan University, 2015 B.S., Electrical Engineering, National Taiwan University, 2012 Research interests include reinforcement learning, game theory, and algorithmic economics. He has received prestigious awards such as the COLT and ALT Best Paper Awards (2021-2022) and the Simons-Berkeley Research Fellowship (2022). His work bridges theory and practice, addressing challenges in adversarial environments and multi-agent coordination. Current research group members include Haolin Liu (PhD), Braham Snyder (PhD), Kingsley Kim (Undergraduate), and Rishik Balerao (Undergraduate). Teaching includes courses on Reinforcement Learning, Artificial Intelligence, and Algorithmic Economics. He co-organizes the RL Meetup and Theory Seminar at UVA.

Hans-Joachim Grafeمشاهده پروفایل

پژوهشگر

• Nuclear Magnetic Resonance
• High Temperature Superconductivity
• Quantum Magnetism
• +۳ مورد دیگر

Dr. Hans-Joachim Grafe is a group leader at the Institute for Solid State Research within the Leibniz Institute for Solid State- and Materials Research (IFW Dresden) in Germany. His research focuses on Nuclear Magnetic Resonance (NMR) studies of quantum materials, particularly investigating high temperature superconductors and quantum magnets. Dr. Grafe completed his diploma thesis at TU Braunschweig on NMR measurements of Sr 14 Cu 24 O 41 under the guidance of Hans-Henning Klauß. He then pursued his PhD at IFW Dresden and TU Dresden, working with Bernd Büchner and Nicholas Curro at Los Alamos National Laboratory on NMR studies of rare earth co-doped lanthanum cuprates. His research interests span Nuclear Magnetic Resonance spectroscopy, high temperature superconductivity, quantum magnetism, and the development of novel NMR instrumentation. Dr. Grafe has made significant contributions to understanding the electronic and magnetic properties of unconventional superconductors using NMR techniques. Recently, he has been involved in developing self-assembled rolled-up microcoils for NMR on nanoliter-sized samples, expanding the capabilities of NMR spectroscopy for studying minute quantities of materials. Analysis of Dr. Grafe's recent publications (2021-2025) reveals a strong focus on applying NMR techniques to investigate quantum magnetic systems, high-temperature superconductors, and novel instrumentation development. His work spans condensed matter physics, materials science, and NMR methodology, with particular emphasis on frustrated magnets, iron-based superconductors, and innovative approaches to enhance NMR sensitivity for nanoscale applications. Dr. Grafe has presented his research at numerous international conferences and seminars, including the Mitteldeutsches Resonanztreffen, Analytica, and various university seminars across Europe. His invited talks often focus on NMR applications in quantum materials and recent advances in NMR instrumentation.

Mark Nigriniمشاهده پروفایل

دانشیار

• Forensic Accounting
• Benford's Law
• Fraud Detection
• +۷ مورد دیگر

Mark Nigrini is an Associate Professor at the College of Business and Economics, Department of Accounting , West Virginia University. He is renowned for his expertise in forensic accounting, Benford's Law, and fraud detection, with a focus on applying mathematical and statistical techniques to financial data. Ph.D., University of Cincinnati M.B.A., University of Stellenbosch B.Com (Hons), University of Cape Town His research spans Forensic Accounting , Benford's Law , Cybersecurity , biases in government statistics, and Sports Betting analysis. He has pioneered methods to detect fraud using digital analysis and has consulted for major corporations like Procter & Gamble and American Airlines. The 15 most recent articles highlight his interdisciplinary work, including applications of Benford's Law in auditing, cybersecurity risk assessment, public health statistics, and medical research. Notable trends include integrating mathematical rigor into fraud detection and analyzing publication length and pandemic impacts. Scientific Awards : 2014 Lawler Award for best article in the Journal of Accountancy Nigrini's career combines academic research with practical forensic consulting and expert witness work. He has appeared in global media outlets like the BBC, NPR, and the New York Times, and his books Benford's Law (2012) and Forensic Analytics (2020) are seminal texts in the field.

Anna Schnauber-Stockmannمشاهده پروفایل

دانشیار

• Media Use and Effects
• Mobile Media and Communication
• Situational Media Research
• +۴ مورد دیگر

PD Dr. habil. Anna Schnauber-Stockmann is a prominent researcher in media and communication science at Johannes Gutenberg University Mainz, where she has been a member of the Media Structure and Media Effects research group since 2010. She completed her habilitation in October 2024 with the thesis 'The Importance of the Situation in Media Use and Media Effects Research' and was awarded Venia Legendi in Communication Science. Previously, she served as an interim professor at IJK (HMTM Hannover) from April to September 2021. Her academic journey includes earning a Dr. phil. in Communication Research in May 2016 with a dissertation on 'Day-to-day Media Selection. The Role of Habits in the Selection Process' and completing her Master's degree at the University of Mainz in 2007. Dr. Schnauber-Stockmann's research focuses on media use and effects, particularly examining how situational factors influence media selection and consumption patterns. Her work explores media habits, mobile communication behaviors, self- and feedback-effects in media contexts, and the application of quantitative research methods, especially in situ methodologies. She investigates how daily routines shape media platform usage and how these patterns affect individual behavior and social interactions. Her research bridges theoretical frameworks with practical applications in digital media environments, with particular attention to how time, context, and personal characteristics interact in media consumption. Her recent publications reveal a strong emphasis on situational media research, with significant contributions to understanding phubbing behavior, mobile media habit formation, and the distinction between person-specific and situation-specific variations in media use. Through meta-analyses and longitudinal studies, she has advanced methodological approaches for measuring media habits and examining real-time media effects. Her work consistently applies sophisticated quantitative methods to capture the dynamic nature of contemporary media consumption. Top Faculty Paper 2023 of ICA's Mobile Communication Division Top Student-led Paper 2023 of ICA's Mobile Communication Division Best Proposal Award 2017 of the DGPuK division Methods Research grant from the 'Friends of the University of Mainz' for outstanding dissertation (2017) Award for best dissertation on media convergence, University of Mainz (2016) As an active member of the academic community, Dr. Schnauber-Stockmann serves as treasurer of the German Communication Association (DGPuK) since May 2020 and previously served as spokesperson for the Media Reception and Effects division (2019-2021). She is an editorial board member for 'Media Psychology' and 'Mobile Media & Communication' and regularly reviews for leading communication journals. Her work demonstrates significant influence through numerous invited presentations and collaborations with international researchers across multiple institutions.

Ulrich Schroedersمشاهده پروفایل

استاد

• Psychological Diagnostics
• Technology-based Competency Diagnostics
• Measurement of Cognitive Abilities
• +۵ مورد دیگر

Ulrich Schroeders is a Professor of Psychological Diagnostics at the University of Kassel, where he has been employed since October 2017. His work focuses on developing and validating psychological assessment tools, with particular expertise in cognitive diagnostics and educational measurement. He teaches various programs for approximately 500 students annually and serves as a supervisor for teacher training students preparing for their oral state examinations in Pedagogy/Psychology. Dr. Schroeders earned his PhD from Humboldt University of Berlin in 2010 with a dissertation titled "Measurement of Cognitive Abilities Using Modern Technologies: Artifacts, Equivalence, and New Constructs." Prior to that, he completed his Diploma in Psychology at Julius-Maximilians-University Würzburg in 2004 with a thesis on diagnosing dyscalculia in first-grade students. His research spans several key areas in psychological assessment. He specializes in technology-based competency diagnostics, developing innovative methods for measuring cognitive abilities and school competencies. A significant portion of his work involves applying Machine Learning and metaheuristics to psychometric problems, particularly in structural equation modeling. His methodological expertise includes advancing techniques in Local Structural Equation Modeling (LSEM) and Meta-Analytic Structural Equation Modeling (MASEM), with applications across educational and clinical psychology contexts. Analysis of Dr. Schroeders' recent publications reveals a strong focus on computational approaches to psychological assessment. His work frequently employs optimization algorithms like Ant Colony Optimization and Bee Swarm Optimization to address challenges in test construction and validation. There's a clear trajectory toward game-based and technology-enhanced assessment methods, as seen in studies using Mastermind and Wordle as assessment tools. His research also demonstrates growing interest in applying machine learning to predict behavioral outcomes, including juvenile delinquency, suicide risk, and psychotherapy outcomes. Dr. Schroeders has secured significant research funding, including projects funded by the German Research Foundation (DFG) and the Hector Foundation. His current projects include "Facing the Replication Crisis in Machine Learning Modeling" (2025-2027) and "PINGUIN: Potenzialidentifikation IN der GrUndschule" (2024-2027), which focuses on identifying elementary students' initial competencies. He leads the development of the BEFKI assessment system (Berliner Test zur Erfassung fluider und kristalliner Intelligenz), which includes versions for different age groups (5-7, 8-10, and 11+). His methodological toolbox includes specialized approaches for test construction and validation, particularly focusing on optimization algorithms applied to psychological measurement problems.

• Multimedia Modeling
• Machine Learning
• Computer Vision
• +۷ مورد دیگر

Dr. Stevan Rudinac is a Researcher at the University of Amsterdam's Faculty of Economics and Business , Section Business Analytics . His work focuses on interactive learning systems and multimodal data analysis, particularly in urban contexts and multimedia modeling. Education: PhD in Multimedia and Information Retrieval from Delft University of Technology (2013). Research Interests: Stevan specializes in multimedia modeling , hypergraph learning , and interactive video search . He develops frameworks for scalable analysis of social networks, urban imagery, and large multimodal datasets, bridging machine learning with practical applications in city planning and financial social media. Recent Trends: His 2024-2025 publications highlight large language model optimization , diffusion model evaluation , and dynamic graph embedding for meme stocks. Collaborative projects include the CASTLE 2024 dataset and Exquisitor , a system for 100 million image exploration. Labs & Teams: He contributes to the Business Analytics group at UvA, collaborating with Prof. Marcel Worring and Dr. Björn Þór Jónsson. He co-organized the UrbanMM'21 workshop and participates in ACM Multimedia and MMM conferences.

Pierre Duchesneمشاهده پروفایل

استاد

• Time Series Analysis
• Sampling Theory
• Multivariate Analysis
• +۲ مورد دیگر

Pierre Duchesne is a Full Professor in the Department of Mathematics and Statistics at the University of Montreal . He serves as Professor-responsibility for the M.Sc. and Ph.D. in Statistics programs (2000-2004). His research focuses on applied statistics with emphasis on: Time Series Analysis (univariate and multivariate models, serial correlation testing, portmanteau statistics) Sampling Theory (robust estimation methods, calibration estimators) Multivariate Analysis (ARCH effects, vector autoregressive models, causality testing) Applications in Econometrics and Financial Econometrics His work combines theoretical development with practical implementation through: Wavelet-based diagnostic methods Simulation studies for model validation Software development (S-PLUS/SAS) for statistical analysis Collaboration with organizations like Statistics Canada and Canadian Journal of Statistics He has served as Associate Editor for journals including Computational Statistics & Data Analysis (CSDA) and Canadian Journal of Statistics (CJS/RCS) .

• Decision Neuroscience
• Neuroeconomics
• Cognitive Neuroscience
• +۶ مورد دیگر

Scott A. Huettel is a Professor in the Department of Psychology and Neuroscience at Duke University, where he also serves as Senior Associate Dean for Research in Trinity College of Arts & Sciences. He holds additional appointments as Professor of Neurobiology and Professor in Psychiatry and Behavioral Sciences. As a Bass Fellow, Huettel leads research in decision neuroscience and neuroeconomics, with affiliations spanning multiple Duke research centers including the Center for Brain Imaging and Analysis, Duke Institute for Brain Sciences, and Center for Cognitive Neuroscience. Huettel's research focuses on the brain mechanisms underlying economic and social decision making. His laboratory uses fMRI to probe brain function, behavioral assays to characterize individual differences, and various physiological methods including eye tracking, pharmacological manipulation, and genetics to link brain and behavior. His work has advanced new analysis methods for fMRI data, including functional connectivity analyses, pattern classification, and combinatoric multivariate approaches. His research spans applications in behavioral economics, consumer decision making, and neuroethics. Huettel's recent publications demonstrate a strong focus on social decision making, risk assessment, and the neural mechanisms of economic choices. His work increasingly integrates computational approaches with traditional neuroimaging to better understand how people process information during decision making. His research has significant implications for understanding financial behavior, health decisions, and social interactions across the lifespan. Education in Neuroimaging Award from the Organization for Human Brain Mapping (2021) 2014 Innovation Award from the Social and Affective Neuroscience Society (2013) Bass Fellow for Excellence in Research and Teaching (2012) Jerry G. and Patricia Crawford Hubbard Professorship at Duke University (2012) Top 5% undergraduate instructor in Arts & Sciences at Duke (2010) Dean's Award for Excellence in Mentoring from Duke University Graduate School (2010) Huettel actively mentors students and has trained numerous postdoctoral and graduate researchers who now lead their own laboratories. He is lead author of the textbook Functional Magnetic Resonance Imaging (3rd edition, 2014) and teaches courses including Fundamentals of Decision Science, Decision Neuroscience, and Neuroethics. His research is supported by multiple grants from NIH and other funding agencies, focusing on mechanisms of social behavior, aging, and neuroimaging technology development. Huettel directs a productive research laboratory that integrates multiple methodologies to investigate decision processes. His team combines fMRI, eye tracking, behavioral testing, and computational modeling to examine how people make economic and social choices. The lab has made significant contributions to understanding how attention, risk, and social context influence decision making across different populations including adolescents, older adults, and clinical populations.