جست‌وجوی استاد و پژوهشگر

Sally Shepleyمشاهده پروفایل

دانشیار

• Special Education
• Autism
• Teacher Education
• +۳ مورد دیگر

Dr. Sally Shepley is an Associate Professor in Special Education at the University of Kentucky (UK) and Director of the Applied Behavior Analysis (ABA) program. She holds a Ph.D. from the University of Georgia and has extensive clinical experience in behavior analysis for individuals with autism spectrum disorder and intellectual disabilities. Her research focuses on leveraging mobile technologies to enhance independence and transition readiness for adolescents and adults with moderate to severe disabilities. She employs single-case experimental designs to evaluate the efficacy of video activity schedules, self-instructional strategies, and technology-mediated interventions. Education: Bachelor of Science in Special Education, University of Georgia Master of Education in Special Education, University of Georgia Doctorate in Special Education, University of Georgia Research Interests: Dr. Shepley investigates how mobile technologies like smartphones and tablets can support skill generalization, problem-solving, and life independence for individuals with disabilities. Her work emphasizes practical applications of behavior analytic strategies in educational and clinical settings, particularly targeting vocational readiness, self-management, and family-centered interventions. Advising & Grants: As ABA program director, she oversees training for future behavior analysts. Her grants and collaborations focus on developing scalable interventions for severe problem behaviors, with a recent emphasis on family-centered service models for children with autism and intellectual disabilities. Labs & Teams: She leads the ABA program at UK, fostering innovation in behavior analytic practices through interdisciplinary collaboration. Her research lab develops technology-based tools for independent living and transition planning.

Lucas Lehnertمشاهده پروفایل

استادیار

• Reinforcement Learning
• Sequential Decision Making
• Generative AI
• +۴ مورد دیگر

Lucas Lehnert is an Assistant Professor in the Department of Computer Science at the University of Saskatchewan, specializing in Artificial Intelligence and Reinforcement Learning (RL). His research focuses on how intelligent systems can learn to solve complex decision-making tasks through representation learning, abstraction mechanisms, and lifelong learning strategies. He also explores applications of AI/RL in scientific and engineering domains. Education: PhD in Computer Science (Brown University, 2021), MSc (McGill University, 2016), BSc (McGill University, 2014). Postdoctoral positions included Meta's FAIR team (2022–2024) and the Mila Quebec AI Institute (2021–2022). Research interests include reinforcement learning fundamentals, generative AI reasoning, exploration strategies, and reward-predictive representations. His work bridges model-based and model-free RL paradigms, emphasizing scalable and generalizable solutions. Awards include the Best Student Workshop Paper Award (2017) and an NIMH training grant in cognitive neuroscience. His research has been published in top conferences like NeurIPS, ICML, and ICLR. He advises graduate students in RL and collaborates on projects involving transformer-based planning, exploration algorithms, and multi-agent systems. Current work includes developing SearchFormer for efficient planning tasks and exploring maximum entropy exploration methods.

Monica Liljeströmمشاهده پروفایل

دانشیار

• Online Learning
• Digitalization in Education
• Special Education
• +۲ مورد دیگر

Monica Liljeström serves as an Associate Professor in the Department of Education at Umeå University, Sweden, where she is affiliated with the Learning and ICT (LIKT) research area. Her primary teaching responsibilities span online-based education programs, including the fully online Education A-C curriculum, special education courses, and HR management instruction. Appointed as assistant professor in 2001, she completed her doctoral degree in 2010 and has since been instrumental in developing the institution's online pedagogical frameworks. Her educational trajectory culminated in a doctorate in 2010 after seven years as assistant professor, reflecting deep institutional commitment and scholarly development. Liljeström's research centers on digital transformation in education, specifically examining online learning methodologies, special education adaptations, and innovative assessment practices. She investigates how collaborative learning and peer assessment function in digital environments, with particular focus on video-based tasks and text-based discussion forums. Her work bridges theoretical frameworks with practical course development, emphasizing student-centered evaluation approaches that foster meaningful engagement in virtual classrooms. Analysis of her publication history reveals a sustained 20-year commitment to advancing online education, evolving from foundational studies on text-based collaboration (2004-2010) to contemporary explorations of video-mediated learning (2017-2023). Her research consistently addresses peer assessment mechanisms, student perception dynamics, and the integration of process evaluation in digital pedagogy, demonstrating methodological rigor across diverse online educational contexts. Scientific Recognition: Distinguished University Teacher award for exceptional pedagogical contributions As an active academic leader, Liljeström has supervised students in special education and pedagogy programs while directing significant research initiatives including the "Collaborative Mixed Reality Aid" project (2019-2020) and foundational work on "Peer assessment in online courses" (2007-2009). These projects secured institutional funding and directly shaped Umeå University's online course development standards. She remains a core contributor to the Learning and ICT (LIKT) research group, driving collaborative investigations into how digital tools transform teaching practices and learning outcomes across educational levels.

Christopher Loniganمشاهده پروفایل

استاد پژوهشی

• Developmental Psychopathology
• Early Literacy Intervention
• Language Acquisition
• +۴ مورد دیگر

Christopher Lonigan is a Distinguished Research Professor and Associate Director at the Florida Center for Reading Research, affiliated with Florida State University's Department of Psychology. He earned his degree from the State University of New York at Stony Brook in 1991. His research bridges developmental psychopathology and early literacy, examining emotional/mototional influences on child development and interventions for at-risk preschoolers. Research interests center on: Developmental psychopathology : Emotional/motivational factors in child psychopathology and PTSD Early literacy : Language acquisition, literacy interventions, and socio-behavioral correlates Temperament studies : Hierarchical models of affect and self-regulation Cross-linguistic research : Bilingual literacy development and transfer effects Publication analysis (2012-2014) reveals three dominant themes: self-regulation/executive function in academic readiness (6 publications), bilingual/language development mechanisms (5 publications), and diagnostic tools for behavioral/cognitive assessment (4 publications). Methodologically, meta-analyses, longitudinal designs, and randomized interventions are prominent. No scientific awards are mentioned in the source material. Advising includes supervision of eight graduate students co-authoring publications. Current recruitment focuses on a graduate student for Fall 2026. Grant activities are not detailed. Lab work spans: Developmental psychopathology: Self-regulatory capacities and emotional influences Early literacy: Typical/at-risk development and intervention efficacy Integrated studies on literacy-behavior connections (e.g., ADHD-literacy links)

Carlos Cardonhaمشاهده پروفایل

استادیار

• Discrete optimization
• Mixed-integer linear programming
• Combinatorial optimization
• +۶ مورد دیگر

Carlos Cardonha is an Assistant Professor in the Department of Operations and Information Management at the University of Connecticut School of Business since 2019. He holds a Ph.D. in Mathematics from Technische Universität Berlin (2011) and degrees in Computer Science from the University of São Paulo (B.Sc. 2004, M.Sc. 2006). Previously, he worked as a Research Staff Member at IBM Research – Brazil (2012–2019). His research focuses on discrete optimization, approximation algorithms, and applications of machine learning and mathematical programming to operations research problems. He teaches courses such as OPIM 5641 (Business Decision Modeling) and OPIM 3511 (Business Data Analytics II), supported by DataCamp. Education: Ph.D. in Mathematics, Technische Universität Berlin, Germany (2011) M.Sc. in Computer Science, University of São Paulo, Brazil (2006) Bachelor in Computer Science, University of São Paulo, Brazil (2004) Research Interests: His work spans analytics, optimization, and theoretical computer science, with a focus on mixed-integer linear programming, combinatorial optimization, and algorithm design. He applies these techniques to real-world problems in scheduling, resource allocation, and machine learning model optimization. Grants & Advising: No specific grants or advisees are listed in the provided materials. Labs/Teams: Not explicitly mentioned in the text.

Maryam Alimardaniمشاهده پروفایل

دانشیار

• Brain-Computer Interfaces
• Virtual Reality
• Neurofeedback
• +۵ مورد دیگر

Dr. Maryam Alimardani is an Associate Professor at the Faculty of Science, Computer Science department, Vrije Universiteit Amsterdam, and a member of the Network Institute. Her research focuses on neurotechnology applications in human-computer interaction, including brain-computer interfaces (BCIs), virtual reality (VR), and robotics. She explores topics such as neurofeedback training for ADHD, workload prediction in flight simulations, and the psychological impact of human-agent interactions. Her work bridges cognitive neuroscience, robotics, and educational technology, with a particular emphasis on improving mental health interventions and learning outcomes through technology. Research interests include EEG analysis for cognitive state monitoring, gamification strategies in BCI training, and the uncanny valley effect in human-robot collaboration. She has contributed to studies on social robotics for stress management, virtual agent design, and the neurophysiological basis of trust in AI systems. Her recent publications address VR flight simulation neural patterns, the role of gender in motor imagery BCIs, and the ethical implications of passive vs. active BCIs. Collaborations span aviation neurophysiology, consumer neuroscience for sustainability, and pediatric language learning through robots. Alimardani teaches Human-Computer Interaction courses and leads projects on adaptive learning systems. Her work emphasizes translational research, applying neuroscientific insights to real-world applications in education, healthcare, and human-technology collaboration.

Andrew Westمشاهده پروفایل

پژوهشگر

• Robotics
• Nuclear Engineering
• Radiation Detection
• +۳ مورد دیگر

Andrew West is a researcher affiliated with the University of Manchester, contributing to the Dalton Nuclear Institute. His work focuses on advancing robotics and autonomous systems for nuclear environments, particularly in radiation detection, mobile robot navigation, and hazardous environment exploration. Key areas include radiation mapping, sensor integration, and risk assessment in nuclear facilities. He has developed specialized robots like CARMA II and Vega for nuclear surveying and decommissioning tasks. Collaborations span international institutions such as JSI and LUNL, with datasets publicly available via Figshare. His research aligns with UN Sustainable Development Goals related to sustainable energy and industry innovation. Education: Background in robotics and nuclear engineering, though specific degrees are not detailed in the text. Research interests emphasize the practical application of robotics in nuclear decommissioning, including real-time radiation avoidance, sensor fusion, and multi-robot ecosystems. His work bridges theoretical modeling (e.g., Gaussian process regression) with practical field deployments, ensuring robots can safely operate in high-risk environments. Publications highlight advancements in radiation localization, sensor calibration (e.g., angular responses), and safety protocols for autonomous systems. The top-cited works focus on multimodal sensing and digital twin platforms for nuclear robot fleets, showcasing industry-academia partnerships. Grants & Projects: Contributions to projects like TORONE (Total Characterisation of Nuclear Environments) and the development of open-source platforms like Mona robot. West’s lab focuses on creating affordable, robust robotic solutions for nuclear challenges, with datasets publicly accessible to foster collaborative research.

Andrea Crisantiمشاهده پروفایل

استاد

• Molecular Parasitology
• Gene Drive Technology
• Malaria Control
• +۷ مورد دیگر

Professor Andrea Crisanti is a leading academic in Molecular Parasitology at Imperial College London's Department of Life Sciences (Faculty of Natural Sciences). His research focuses on developing gene drive technologies to combat malaria by genetically modifying mosquitoes. His lab demonstrated CRISPR/Cas9-driven population suppression via targeting the doublesex gene, which disrupts female development and could eliminate malaria vectors. Recently, he coordinated the groundbreaking Vo' Euganeo study on early SARS-CoV-2 outbreak management, informing national and international pandemic strategies. Affiliations: Imperial College Network of Excellence in Malaria, Infection and Immunity, Vaccine Research Network Led the development of synthetic biology tools for vector control and agricultural pest management Co-developed Y chromosome-linked gene drives and anti-CRISPR safeguards Contributed to WHO-endorsed guidelines for mosquito containment facilities Research interests span molecular mechanisms of mosquito reproduction, gene drive evolution, and translational applications of synthetic biology in public health. His lab also engages in community outreach through exhibitions and school programs. Notable collaborations include: Target Malaria Consortium Italian Veneto Regional Health Task Force European Infravec2 initiative Laboratory infrastructure includes advanced molecular biology facilities and large-scale mosquito testing environments. Funded by major grants from Wellcome Trust, EU Horizon programs, and philanthropic organizations.

• Decision Making
• Cognitive Neuroscience
• Neuroimaging
• +۶ مورد دیگر

Miriam Klein-Flugge is an Associate Professor at the University of Oxford, holding joint appointments in the Departments of Psychiatry and Experimental Psychology. She is a Wellcome Trust/Royal Society Henry Dale Fellow and UKRI/ERC Starting Grant Fellow, leading the Motivation, Decision and Neurostimulation (Modes) Lab. Her research focuses on decision-making processes, emotion, motivation, and the neural mechanisms underlying flexible behavior, with particular emphasis on subcortical brain regions and mental health applications. Dr. Klein-Flugge uses advanced techniques such as fMRI, MEG, EEG, transcranial ultrasound stimulation (TUS), and computational modeling to study how the brain adapts decisions to internal and external conditions. Her work explores topics like effort-based choices, context-dependent decisions, and the impact of mental illness on decision-making. She also investigates the structural and functional roles of subcortical nuclei in stress and reward processing. Her educational background includes a Mathematics, Computer Science, and Cognitive Science degree from the University of Osnabrück and McGill University, an MSc in Neuroscience from Oxford, and a PhD in Cognitive Neuroscience from UCL. She completed postdoctoral research as a Henry Wellcome Fellow in Matthew Rushworth’s lab at Oxford. Dr. Klein-Flugge has received funding from the Wellcome Trust, ERC/UKRI, and the MRC. Her awards include prestigious fellowships supporting her innovative research. She is actively involved in public outreach, including live MRI school lessons to engage youth in neuroscience.

Randall W. Engleمشاهده پروفایل

استاد

• Working Memory
• Attention Control
• Cognitive Neuroscience
• +۳ مورد دیگر

Randall W. Engle is a Professor of Psychology at the Georgia Institute of Technology, specializing in cognitive processes related to working memory and attention control. His research investigates individual differences in executive functions, linking these to fluid intelligence and neurological mechanisms. Engle has contributed significantly to understanding the role of attention control in complex cognitive tasks and its applications in high-stakes testing and military selection processes. Education: Ph.D. (1973) in Experimental Psychology from The Ohio State University. Research Interests: Focus on working memory capacity, attention control mechanisms, and their neural underpinnings, particularly involving dopamine regulation in frontal lobes. He has developed influential theories on how attention control mediates cognitive performance. Recent work emphasizes applied aspects, such as improving predictive accuracy in navy trainee performance and refining measurement tools for attention control. His lab (Attention & Working Memory Lab) collaborates on interdisciplinary projects involving neuroscience and education. Labs/Teams: Director of the Attention & Working Memory Lab at Georgia Tech, fostering graduate student research in cognitive psychology and neuroscience.

Zachary Irvingمشاهده پروفایل

دانشیار

• Philosophy of Cognitive Science
• Philosophy of Mind
• Attention Norms
• +۴ مورد دیگر

Zachary Irving is an Associate Professor in the Corcoran Department of Philosophy at the University of Virginia. His research focuses on the philosophy of cognitive science, particularly mind-wandering, attention norms, and mental action. He holds a B.A., M.A., and Ph.D. from the University of Toronto, specializing in philosophy of cognitive science, epistemology, and philosophy of action. NEH Fellowship (2024): “The Spontaneity Deficit: Good Minds in the Age of Distraction” Templeton Grant (2022): Machine learning classifiers for distinguishing mind-wandering in VR His interdisciplinary work bridges philosophy with cognitive psychology/neuroscience, social psychology, and even household finance (e.g., collaborating with LUSH on a shower routine to harness mind-wandering). Key research programs include: Mind-wandering as unguided attention Foundations of the cognitive science of mind-wandering Normative analysis of attention in the digital era Teaching includes courses on philosophy of mind, consciousness, memory, and neuroscience. Collaborations involve scholars like Sheisha Kulkarni, Caitlin Mills, and Sam Murray, emphasizing empirical and philosophical synergy.

Britton Sauerbreiمشاهده پروفایل

استادیار

• Motor Control
• Neural Circuits
• Neurodegenerative Diseases
• +۳ مورد دیگر

Britton Sauerbrei is an Assistant Professor in the Department of Neurosciences at Case Western Reserve University's School of Medicine. Their research focuses on understanding the neural circuits governing skilled motor control, particularly how distributed neural networks enable adaptive movement and how these dynamics are disrupted in neurodegenerative diseases. They employ high-density electrophysiological recordings, optogenetic manipulation, and computational modeling to study neural ensemble activity during natural behaviors. Education: Bachelor of Arts in Mathematics, University of Chicago (2009) PhD in Computation and Neural Systems, California Institute of Technology (2015) Research Interests: The lab investigates principles underlying neural activity flow in motor control circuits, with emphasis on cerebellar-cortical interactions and disease-related alterations. Techniques include Neuropixels recording probes, optogenetics, and computational methods like adaptive functional PCA. Key Findings: Recent work demonstrates the cerebellum's role in discontinuous movement control and reveals input-driven cortical dynamics during dexterous tasks. Innovations include the development of high-density neural probes ( Neuropixels 2.0 ) and novel motor unit recording devices. Lab & Collaborations: The Sauerbrei Lab actively explores neurodegenerative disease models and sensorimotor integration mechanisms. Collaborative projects focus on translating findings to understand movement disorders and developing computational tools for neural data analysis.

Virginia E. Vitielloمشاهده پروفایل

عضو هیئت علمی

• Early Childhood Education
• Teaching and Learning
• School Readiness
• +۳ مورد دیگر

Virginia E. Vitiello serves as a Research Associate Professor at the University of Virginia's School of Education and Human Development, where she is affiliated with the Center for Advanced Study of Teaching and Learning and the Research in Education and Learning Lab. Her scholarly work centers on early childhood education with particular emphasis on classroom processes that influence children's development. Her primary research interests include: Early childhood education and development School readiness and transitions from pre-K to kindergarten Teacher-student interactions and classroom quality Curriculum implementation in preschool settings Mathematics and science education in early childhood Curiosity development in classroom contexts Dr. Vitiello's research portfolio reveals consistent focus on how specific teaching practices and classroom environments shape children's academic and social-emotional outcomes. Her recent publications demonstrate growing interest in curiosity as a critical learning mechanism in early education, particularly in math and science contexts. She employs longitudinal methodologies to track developmental trajectories across educational transitions. She actively contributes to several major research initiatives: Curiosity in Classrooms MyTeachingPartner - Mathematics/Science Curricula and Implementation Support System Fairfax PreK to Third Grade Project Learning to Objectively Observe Kids (LOOK) Assessment, Instruction and Mathematics in Kindergarten Classrooms (AIM) STREAMin³ Curriculum Model STREAMin3 Impact Project Through these projects, Dr. Vitiello develops and evaluates evidence-based practices for improving early childhood education quality and effectiveness.

Clayton E Curtisمشاهده پروفایل

استاد

• Neuroscience
• Cognitive Science
• Neural Mechanisms
• +۶ مورد دیگر

Clayton E Curtis is a Professor of Psychology and Neural Science at New York University, affiliated with the College of Arts & Science. His research focuses on understanding neural mechanisms underlying higher-order cognition, particularly in the prefrontal cortex (PFC) and parietal cortex, emphasizing working memory, attention, and motor control. He investigates how these brain regions support adaptive behavior and contribute to cognitive disorders like schizophrenia and Alzheimer’s disease. Education: Ph.D. in Psychology, University of Minnesota, 1999 M.A. in Psychology, University of Minnesota, 1997 B.A. in Psychology, University of Texas at Austin, 1992 Research Interests: Dr. Curtis studies the neural basis of working memory, spatial cognition, and executive control. Key areas include persistent neural activity in PFC, spatial attention, inhibitory control of actions, and translational research linking human and non-human primate models. His work employs fMRI, electrophysiology, and behavioral experiments to unravel how the brain prioritizes information and coordinates motor responses. Publications & Trends: His recent articles explore mechanisms of working memory prioritization, neural correlates of cognitive effort, and spatial tuning in visual cortex. Themes include interplay between attention, memory, and motor planning, with a focus on neural network dynamics and disease-related deficits. Labs & Teams: His lab at NYU integrates neuroimaging and behavioral methods to study cognitive functions, collaborating with researchers in electrophysiology and computational neuroscience. Ongoing projects include mapping retinotopic organization in frontal cortex and investigating drug effects on memory precision.

Vikram S. Chibمشاهده پروفایل

دانشیار

• Decision-making
• Motor Control
• Neuroeconomics
• +۴ مورد دیگر

Vikram S. Chib is an Associate Professor of Biomedical Engineering at the Johns Hopkins University School of Medicine. He is also a Research Scientist at Kennedy Krieger Institute and affiliated with the Kavli Neuroscience Discovery Institute. His research integrates robotics, neuroscience, and economics to study how the brain controls movement and motivational processes, focusing on decision-making, reward valuation, and effort-based choices. Chib holds a PhD and MS in Biomedical Engineering from Northwestern University (2007, 2003) and a BS in Bioengineering from the University of Pittsburgh (2001). His postdoctoral training was at the California Institute of Technology. His work explores how motivational cues drive motor actions, with applications to neurological disorders and incentive design. Key areas include cognitive fatigue mechanisms, dopamine’s role in effort perception, and neural substrates of decision-making. His lab uses functional brain imaging, noninvasive brain stimulation, and behavioral experiments to investigate these topics. Chib’s research has been featured in high-impact studies on fatigue regulation, schizophrenia-related effort deficits, and the neurobiological basis of social and prosocial behavior. He collaborates across disciplines to translate findings into treatments for neurological impairments and performance optimization strategies.