جست‌وجوی استاد و پژوهشگر

• Human-Computer Interaction
• Learning Sciences
• Educational Technology
• +۲ مورد دیگر

Jennifer Olsen, PhD, is an Assistant Professor of Computer Science at the University of San Diego since 2020. She holds a PhD, MS, and BS in Human-Computer Interaction and Cognitive Science from Carnegie Mellon University, followed by postdoctoral research at the Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland. Her research focuses on the intersection of human-computer interaction, cognition, and education, emphasizing collaborative learning and educational technology design from both learner and instructor perspectives. Education: PhD in Human-Computer Interaction, Carnegie Mellon University MS in Human-Computer Interaction, Carnegie Mellon University BS in Cognitive Science, Carnegie Mellon University Research Interests: Dr. Olsen explores how collaboration supports learning, designs technologies to enhance educational practices, and investigates gaze-based metrics for understanding collaborative problem-solving. Her work spans gamified robotics, AI-driven orchestration systems, and virtual reality applications in vocational training. She emphasizes learner-centered design and the integration of social robots and virtual agents in pedagogical settings. Grants/Advising: While no specific grants or advisees are listed, her prolific publication record indicates active involvement in educational technology research and development. Her work addresses challenges in classroom orchestration, multimodal data analysis, and accessibility in educational robotics. Labs/Teams: Collaborates with interdisciplinary teams focused on educational technology, human-robot interaction, and adaptive learning systems. Her research leverages tools like FROG orchestration graphs and eye-tracking technologies to develop practical classroom solutions.

Robert Wilsonمشاهده پروفایل

دانشیار

• Computational Cognitive Neuroscience
• Reinforcement Learning
• Decision Making
• +۷ مورد دیگر

Robert Wilson is an Associate Professor in the School of Psychology at Georgia Institute of Technology. His research focuses on computational cognitive neuroscience, reinforcement learning, decision making, and their applications in psychiatry and aging. Wilson leads a lab integrating computational modeling with behavioral experiments, neuroimaging, and neurostimulation to explore the algorithms underlying human cognition. He holds a Ph.D. in Bioengineering from the University of Pennsylvania (2009). Education: Ph.D. in Bioengineering, University of Pennsylvania, 2009 Research Interests: Wilson’s work spans computational models of decision making, reinforcement learning dynamics, and the neural mechanisms of explore-exploit trade-offs. His lab investigates phishing detection cognition, navigation strategies, and perceptual decision making, with recent studies on aging-related cognitive decline and psychiatric disorders. Publications: His recent work includes studies on computational models of exploration strategies, phishing susceptibility (PEST task), and aging effects on decision-making. Articles often bridge neuroscience and AI, such as applying reinforcement learning to large language models. Awards & Grants: While no formal awards are listed, his research has been supported by grants exploring computational psychiatry and neuroimaging. Labs & Teams: Wilson directs a multidisciplinary lab at Georgia Tech, collaborating with experts in AI, neuroscience, and clinical psychology to advance computational theories of the mind-brain relationship.

Wim Geversمشاهده پروفایل

استاد

• Cognitive control
• Metacognition
• Working memory
• +۳ مورد دیگر

Wim Gevers is a faculty member at the Université libre de Bruxelles (ULB) and leads the CS4S – Cognitive Control & Sleep laboratory within the CRCN research centre. His work bridges cognitive psychology, neuroscience and sleep research to understand how the brain exerts control over thoughts and actions and how sleep contributes to these processes. Research Interests Cognitive Control & Metacognition: Investigating how subjective experiences such as confidence and the "urge-to-err" guide strategic adjustments in behaviour. Working Memory & Ordinal Cognition: Examining how order information is maintained and manipulated, and how these processes relate to mathematical competence. Sleep, Memory & Decision Making: Exploring how sleep-dependent consolidation influences motor learning and decision strategies. Across his 2022–2025 publications a clear trend emerges: a focus on metacognitive monitoring —how humans evaluate their own cognitive states—and the role of emotional and temporal context in shaping those evaluations. Studies range from reaction-time introspection and confidence judgements in perceptual tasks to the impact of aging and depression on metacognitive accuracy. Doctoral Supervision & Mentoring Whitney Stee (PhD 2024) – Sleep-dependent structural brain reorganization & motor learning Gaia Corlazzoli (PhD 2024) – Subjective experience in decision-making Myrtille Dewulf (PhD 2023) – Ordinal coding mechanisms in working memory Rebeca Sifuentes-Ortega (PhD 2023) – REM sleep and memory reactivation All dissertations were defended at ULB, Faculté des Sciences psychologiques et de l’éducation, with Wim Gevers formally listed as Promotor . Laboratory & Collaborative Networks As head of CS4S, Gevers coordinates a multidisciplinary team that combines behavioural experimentation, EEG/MEG, computational modelling and sleep polysomnography. The lab is embedded in the larger CRCN ecosystem, fostering collaborations with groups such as CO3 (consciousness), LCLD (language & deafness), and UR2NF (neurofunctional imaging).

Emily Wallمشاهده پروفایل

استادیار

• Data Visualization
• Visual Analytics
• Cognitive Psychology
• +۳ مورد دیگر

Dr. Emily Wall is an Assistant Professor in the Department of Computer Science at Emory University, leading the CAV Lab (Cognition and Visualization). She earned her Ph.D. in Computer Science from Georgia Tech (2020) and completed a postdoctoral fellowship at Northwestern University before joining Emory. Ph.D., Computer Science, Georgia Tech (2020) Postdoctoral Researcher, Northwestern University Current: Assistant Professor, Emory University Her research focuses on enhancing human decision-making through data visualization and visual analytics by addressing cognitive limitations and biases. Key areas include metacognition promotion, computational strategies for bias mitigation, and human-AI collaboration in data analysis. She combines cognitive psychology principles with technical implementation using tools like D3.js and Tableau. Recent publications highlight her work on LLM applications in visual analytics, cognitive bias interventions, and trust calibration in AI systems. Current students like Mengyu Chen, Shiyao Li, and Zhongzheng Xu are presenting at top conferences such as CHI and IEEE VIS. She also explores educational applications through interactive visualization pedagogy and innovative assessment methods. Dr. Wall actively engages in academic service through graduate mentorship, conference judging, and diversity initiatives. Her lab emphasizes both technical proficiency and social justice implications in visualization design, reflected in course projects that merge artistic expression with data-driven storytelling.

Maj Schian Nielsenمشاهده پروفایل

پژوهشگر

• Multilingualism
• Language Education
• Crosslinguistic Awareness
• +۳ مورد دیگر

Maj Schian Nielsen is a Senior Research Librarian at the University Library of the University of Agder. Her work focuses on multilingualism, crosslinguistic awareness, and German language pedagogy. She is affiliated with the research groups 'Media and Communication Studies' and 'Multilingualism in Society and Education (MUSE).' University of Agder Research Groups: Media and Communication Studies, MUSE Her research explores how multilingual awareness can enhance grammar instruction in German third-language (L3) teacher education programs across Denmark and Norway. Recent publications analyze curriculum structures, educational materials, and the integration of generative AI tools like ChatGPT in multilingual education contexts. Scientific output trends reveal a focus on: Cross-linguistic pedagogy L3 German acquisition Grammar teaching methodologies AI applications in language learning Teacher training for multilingual classrooms Systemic Functional Linguistics (SFL) frameworks She has not been publicly recognized with scientific awards listed in the available data.

• Applied Linguistics
• Language Testing and Assessment
• Language Assessment Literacy
• +۶ مورد دیگر

Professor Luke Harding is a faculty member at the Department of Linguistics and English Language , Lancaster University , within the School of Social Sciences . His work bridges applied linguistics, language assessment, and critical discourse studies, with a focus on the ethical and societal implications of testing. Research Interests : Language testing and assessment, World Englishes and English as a Lingua Franca (ELF), second language listening and pronunciation assessment, diagnostic approaches to language evaluation, and language assessment literacy. Recent projects integrate digital technology and corpus linguistics into testing frameworks. Publications : Published extensively in Language Testing , Applied Linguistics , and Language Assessment Quarterly . Co-edited the Routledge Handbook of Language Testing (Second Edition) (2022), a key reference work in the field. Teaching : Leads modules in Language Test Construction and Evaluation , Issues in Language Testing , and Statistical Analysis for Language Testing within the university's distance MA program. Leadership : Convened the Language Testing Research Group with colleagues Tineke Brunfaut and John Pill, advancing interdisciplinary approaches to assessment.

Eleanor O'Rourkeمشاهده پروفایل

دانشیار

• Human-Computer Interaction
• Artificial Intelligence
• Learning Sciences
• +۳ مورد دیگر

Eleanor O'Rourke is an Associate Professor at Northwestern University with joint appointments in the Department of Computer Science and the Learning Sciences, part of the McCormick School of Engineering. She co-directs the Delta Lab, focusing on interdisciplinary research in Human-Computer Interaction, Artificial Intelligence, and Learning Sciences. Her work examines how learning environments can foster motivation and effective practices in computer science education, supported by grants from NSF and Google. Educated at the University of Washington (PhD, MS in Computer Science & Engineering) and Colby College (BS in Computer Science and Spanish), her research employs mixed methods, including design-based research and grounded theory, to study student motivation, affective responses during programming, and AI-driven interventions. Notable contributions include tools like Ply and Isopleth , which support novice web developers, and studies on student self-assessment biases and growth mindset incentives. Her work has been recognized with multiple Best Paper Awards at ACM conferences, including ICER 2024 and SIGCSE 2022. She teaches courses such as Transformative AI and the Learning Sciences and Design of Learning Environments , and advises a diverse cohort of PhD students and undergraduates. The Delta Lab’s collaborative approach emphasizes innovation in educational technology and human-centered design.

Marcelo Mattarمشاهده پروفایل

استادیار

• Computational Neuroscience
• Decision-Making
• Reinforcement Learning
• +۳ مورد دیگر

Marcelo Mattar is an Assistant Professor of Psychology and Neural Science at New York University, leading the Mattar Lab. His research focuses on the neural computations underlying memory, decision-making, and reinforcement learning. He holds a Ph.D. in Psychology from the University of Pennsylvania and has held academic positions at NYU, UC San Diego, and postdoctoral roles at Princeton University and the University of Cambridge. His work bridges computational neuroscience and artificial intelligence, aiming to model how the brain uses internal models for planning and decision-making. Education: Ph.D. in Psychology (Computational and Cognitive Neuroscience), University of Pennsylvania, 2016 M.A. in Statistics, University of Pennsylvania, 2016 B.A. in Electronics Engineering, Instituto Tecnologico de Aeronautica, Brazil, 2010 Research Interests: The lab develops mathematical models of learning and decision-making, leveraging reinforcement learning, Bayesian statistics, and neural networks. Experiments involve human behavioral studies and neuroimaging, with collaborations in animal electrophysiology and computational psychiatry. Key Contributions: His work explores how episodic memory and hippocampal replay support flexible decision-making. Recent studies highlight parallels between human cognition and AI systems, such as language models' metacognitive abilities and brain-inspired algorithms. Awards: Newton International Fellowship, Royal Society (2018–2019) Lab Team: The lab includes postdocs, PhD students, and undergraduates from diverse fields like cognitive science, neuroscience, and computer science. Current members are listed on the lab's website. Lab Location: Meyer Hall, 6 Washington Place, New York, NY 10003.

Yoshua Bengioمشاهده پروفایل

استاد

• Artificial Intelligence
• Deep Learning
• AI Safety
• +۷ مورد دیگر

Yoshua Bengio is a Full Professor at the Université de Montréal, affiliated with the Department of Computer Science and Operations Research at the Faculty of Arts and Sciences. He is a pioneer of deep learning and a leading figure in AI safety. He co-founded Mila – Quebec Institute of Artificial Intelligence and serves as its scientific director. His work focuses on advancing AI technology while addressing ethical and safety challenges, including AI governance and catastrophic risk mitigation. Education: Ph.D. in Computer Science from McGill University (1991), postdoctoral studies at MIT. Research interests include deep learning, causal inference, AI ethics, and responsible AI development. He contributed to the Montreal Declaration for Responsible AI and leads the International Scientific Report on AI Safety. Recent articles emphasize AI safety frameworks, governance, and technical advancements in machine learning. Awards include the Turing Award (2018), Killam Prize (2019), and recognition as TIME's Most Influential Person (2024). He holds prestigious fellowships and is a member of the UN Scientific Advisory Board for Breakthrough Science and Technology. Affiliations include Mila, IVADO (as founding scientific director), and CIFAR programs. His work bridges academia, industry, and policy to ensure AI benefits humanity while minimizing existential risks.

Rita Aielloمشاهده پروفایل

دانشیار مدعو

• Music Psychology
• Neuroaesthetics of Music
• Cognitive Processes in Music
• +۴ مورد دیگر

Rita Aiello is an Adjunct Associate Professor in the Department of Psychology at New York University's College of Arts & Science. Her research focuses on the cognitive and perceptual processes involved in musical listening, with particular emphasis on neuroaesthetics, music learning, and memory. She holds an Ed.D. from Columbia University and has held faculty positions at institutions including the Juilliard School and the Manhattan School of Music. Her work bridges music theory, cognitive science, and education, with a lifelong background as a classical pianist. Education: Columbia University (Ed.D.), Manhattan School of Music (M.M., B.M.), Conservatorio San Pietro a Maiella (Diploma in Music Theory) Certifications: Kodály and Orff Methods Her research explores how musical training influences cerebral dominance, the relationship between mental representations and emotional responses to music, and the cognitive underpinnings of musical memory. She has published widely on topics ranging from musical expectation to pedagogical strategies for memorization. Recent work investigates evolutionary perspectives on singing and the psychological mechanisms behind musical communication. Publications reflect interdisciplinary engagement with music's structural rules, metaphorical dimensions, and its role in human cognition. While no specific grants or awards are listed, her extensive international teaching experience includes visiting roles at institutions in Rome and Lugano, Switzerland, and an honorary appointment at Columbia University's Teachers College.

Lena Wesselمشاهده پروفایل

استاد

• Mathematics Education
• Teacher Training
• Language Development in Education
• +۴ مورد دیگر

Prof. Dr. Lena Wessel is a Mathematics Education faculty member at the Department of Mathematics Didactics, Faculty of Electrical Engineering, Computer Science and Mathematics, University of Paderborn. She leads teacher training programs and participates in university governance as elected Faculty Council member. Research Focus: Her work centers on comprehension-oriented mathematics instruction at secondary/vocational levels, emphasizing language development, continuity in curriculum design (spiral principle), and digital mathematics tools. As DZLM network partner, she develops professional development programs for secondary educators. LiaNMU project (scalar products, plane reflections) VioLa project (digital discussion formats) LLV.HD project (cross-university learning networks) Key Contributions: She has coordinated major projects like MESUT (language-supported fraction understanding) and LaMaVoC (language in vocational mathematics). Her 2024 publications analyze language-integrated pedagogy and algebraic concept unification in teacher training.

Scott Fraundorfمشاهده پروفایل

دانشیار

• Cognitive Psychology
• Educational Technology
• Psycholinguistics
• +۴ مورد دیگر

Scott Fraundorf is an Associate Professor in the Department of Psychology at the University of Pittsburgh , where he leads the MAPLE (Memory And Psycholinguistics in Learning & Education) Lab . He combines cognitive science and data science to study human behavior prediction, educational program evaluation, and psycholinguistics . His research focuses on student learning and metacognition language processing and educational technology interventions statistical modeling using regression , machine learning , and mixed-effects models as well as open-source tool development for cognitive science. Key technical skills include Python , R , and SQL programming, with 3 patents for intelligent tutoring systems in English grammar. He has mentored over 70 graduate students and faculty in quantitative methods.

Eunice Eunhee Jangمشاهده پروفایل

استاد

• Language Assessment
• Educational Measurement
• Program Evaluation
• +۸ مورد دیگر

Dr. Eunice Eunhee Jang is a Professor in the Department of Applied Psychology and Human Development at the Ontario Institute for Studies in Education (OISE), University of Toronto. Her research focuses on synergistic learner modeling, dynamic assessment systems, and the intersection of language testing with educational measurement. PhD with specializations in language testing, educational measurement, and program evaluation Develops interactive digital assessment interfaces for struggling readers Author of "Focus on Assessment" (2014) and co-author of OECD Reviews on Evaluation and Assessment in Education Research Interests Dr. Jang's work explores prismatic assessment analytics to understand learner potential and predict learning pathways. She integrates natural language processing and machine learning to create diagnostic feedback systems that support cognitive, metacognitive, and affective growth in technology-rich classrooms. Scientific Awards Jacqueline Ross TOEFL Dissertation Award Caroline Clapham IELTS Master’s Award Tatsuoka Measurement Award Professional Contributions She has served on major advisory boards including EQAO provincial assessments and TOEFL Committees of Examiners. Currently, she is an elected board member for the International Language Testing Association and contributes to the Broader Measures of Success Advisory Committee for People for Education.

Michaela Sambanisمشاهده پروفایل

استاد

• English Language Teaching
• Positive Foreign Language Didactics
• Neurodidactics
• +۶ مورد دیگر

Univ.-Prof. Dr. Michaela Sambanis is a Professor of English Didactics at the Institute of English Philology within the Department of Philosophy and Humanities at Freie Universität Berlin. She has held this position since 2011 and previously served as the managing director of the Institute from Winter semester 2017/2018 to October 2019. Her academic journey includes research work at the Transfer Center for Neuroscience and Learning at the University of Ulm (2008-2011), completion of her habilitation in 2006, and her promotion in 2001. Professor Sambanis's research centers on the innovative intersection of educational neuroscience and language teaching methodology. Her work pioneers the field of Positive Foreign Language Didactics, connecting positive psychology with language education. She investigates embodied cognition approaches, particularly movement-based learning, and explores theater methods and arts integration in language instruction. Her research also addresses teacher well-being and health, multilingualism in educational settings, and the application of neuroscience findings to practical classroom situations. The k2teach project represents her current focus on teaching-learning labs in English teacher education. Her scholarly output demonstrates a consistent trajectory toward integrating neuroscience with language pedagogy, with recent publications increasingly addressing mental health, digital transformation in education, and positive psychology applications. The evolution of her work shows a progression from practical teaching methods to increasingly sophisticated neurodidactic frameworks that bridge scientific evidence with classroom practice. Professor Sambanis serves on multiple scientific advisory boards including the Goethe Institut in Munich, the Transfer Center for Neuroscience and Learning at the University of Ulm, and the Schlözer Program for Teacher Education. She is also the founding chair of the cross-state E&M Berlin-Brandenburg section and a member of the German Society for Foreign Language Research (DGFF). Her editorial work includes the SELT book series on English Language Teaching. Her teaching responsibilities include supervising master's theses in English teaching, and she has developed numerous teaching-learning laboratories that connect theoretical knowledge with practical application in teacher education. Her work demonstrates a strong commitment to evidence-based foreign language didactics that incorporates insights from neuroscience, psychology, and educational research.

Rani Moranمشاهده پروفایل

مدرس

• Decision Making
• Reinforcement Learning
• Cognitive Maps
• +۵ مورد دیگر

Dr. Rani Moran is a Lecturer in Psychology at Queen Mary University of London's School of Biological and Behavioural Sciences. She is affiliated with the Centre for Brain and Behaviour. Her research focuses on decision-making, memory, and learning mechanisms, employing methods like computational modeling, neuroimaging, and pharmacological interventions. Key interests include reinforcement learning, cognitive maps, and exploration-exploitation dilemmas. Her work integrates experimental designs with advanced statistical analysis to understand flexible behavioral control. Recent studies explore model-based vs. model-free learning, credit assignment mechanisms, and disinformation's impact on learning biases. She has published in top journals such as Psychological Review and Nature Communications . Dr. Moran collaborates on projects involving neurocomputational models of confidence, meta-cognition, and social learning. Her research aims to develop interventions for optimizing cognitive processes, with applications in mental health and decision-making contexts.