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Kathryn A. WhiteheadView profile

Professor

• Drug Delivery
• RNA Therapeutics
• Bionanotechnology
• +4 more

Dr. Kathryn A. Whitehead is a Professor in the Department of Chemical Engineering and holds a courtesy appointment in the Department of Biomedical Engineering at Carnegie Mellon University. She joined the faculty in 2012 after completing postdoctoral training at MIT. Her research focuses on engineering drug delivery systems for RNA therapeutics, maternal-infant health, and overcoming biological barriers to enhance drug efficacy. Key areas include lipid nanoparticle (LNP) design for mRNA delivery, intestinal permeation enhancement, and leveraging maternal milk cells for therapeutic applications. Education: H.B.Ch.E., University of Delaware (2002); Ph.D., University of California, Santa Barbara (2007); Postdoctoral Fellow, MIT (2008–2012). Research Interests: Drug delivery systems, RNA interference, bionanotechnology, personalized medicine, and translational nanomedicine for diseases such as cancer and diabetes. Her lab develops novel LNPs for targeted delivery to tissues like the liver, brain, and pancreas. Awards and Recognition: AIMBE Fellow, DARPA Young Faculty Award (2016), CMBE Young Innovator Award (2016), MIT Technology Review Innovator Under 35 (2014), and NIH Director’s New Innovator Award. Her work has been cited over 9,000 times, with patents in RNA delivery and permeation enhancers. Lab Members: Active researchers include Ph.D. students, postdocs, and undergraduates working on projects such as LNP formulation, maternal milk cell biology, and siRNA therapies. Notable alumni have advanced to roles at Moderna Therapeutics, Verve Therapeutics, and academic institutions. Grants and Funding: Supported by NIH, DARPA, and industry partnerships. Current projects include NIH grants on pregnancy-safe mRNA delivery and DARPA funding for maternal-infant therapeutics.

Daniel HydeView profile

Associate Professor

• Cognitive Development
• Numerical Cognition
• Developmental Psychology
• +7 more

Daniel Hyde is an Associate Professor in the Department of Psychology at the University of Illinois Urbana-Champaign, affiliated with the College of Liberal Arts & Sciences and the Neuroscience Program. His research explores the nature and development of abstract conceptual knowledge through behavioral and neural measures. PhD in Psychology from Harvard University Hyde investigates cognitive development from infancy to adulthood, focusing on quantitative reasoning , spatial reasoning , and psychological reasoning using techniques like event-related brain potentials (ERPs) , functional near-infrared spectroscopy (fNIRS) , and behavioral assessments. His recent work examines how symbolic number knowledge builds on non-symbolic foundations and how neural sensitivity to mental states in infancy predicts later theory of mind abilities. Hyde's publications demonstrate a consistent focus on numerical cognition, multisensory integration, and developmental neuroscience. He leads the Brain and Cognitive Development Lab , participates in global initiatives like ManyNumbers and ManyBabies , and collaborates across disciplines to apply developmental insights to education and public health contexts.

Ashley J ThomasView profile

Assistant Professor

• Developmental Psychology
• Cognitive Science
• Social Psychology
• +7 more

Ashley J Thomas is an Assistant Professor at Harvard University, specializing in infant and child social cognition. Her research explores how young humans develop naive sociology, focusing on social hierarchy, intimacy perception, and moral judgments of parenting decisions. Education: PhD in Psychology (2018), MA in Psychology (2015) from UC Irvine, BA in Architecture (2008) from UC Berkeley. Her work reveals infants use caregiver interactions to evaluate social partners and demonstrates that saliva sharing serves as a key cue for relationship recognition. She examines how implicit theories of intelligence correlate with brain plasticity beliefs, showing that malleable intelligence theories align with environmental influence acceptance. Scientific awards include the NIH National Research Service Award and multiple fellowships. She has organized symposia on social cognition at the Cognitive Development Society and Society for Research on Child Development conferences.

Pixu ShiView profile

Assistant Professor

• Microbiome Research
• Longitudinal/Temporal Omic Data
• Integration of Omic Data
• +2 more

Pixu Shi is an Assistant Professor in the Department of Biostatistics and Bioinformatics at Duke University's School of Medicine. Previously, they served as a Visiting Assistant Professor in the Department of Statistics at the University of Wisconsin-Madison (2018-2020) and as a Postdoctoral Researcher in the Department of Biostatistics at the University of Wisconsin-Madison (2016-2018). Dr. Shi earned their PhD in Biostatistics from the University of Pennsylvania in 2016 under advisor Hongzhe Li. They also hold an MS in Biostatistics from the University of Pennsylvania (2015), an MS in Statistics from Rutgers University (2012), and a BS in Statistics from Peking University (2010). Dr. Shi's research focuses on developing statistical methods for Microbiome Research, Longitudinal/Temporal Omic Data analysis, Integration of Omic Data, Spatial Omics, and High-dimensional Statistical Inference. Their work bridges statistical theory with practical applications in biomedical research, particularly in microbiome studies where they've made significant contributions with the TEMPTED (TEMPoral TEnsor Decomposition) method. The article trends show a strong focus on microbiome analysis, statistical methodology development, and applications in obesity, infectious disease, and cancer research. Their most recent work (2024-2025) demonstrates expertise in tensor decomposition methods, longitudinal data analysis, and integrating microbiome data with clinical outcomes across diverse areas including adolescent obesity, viral infections, and cancer metastases. Dr. Shi has secured multiple substantial research grants from major institutions including the National Institutes of Health (NIMH, NIAID, NCI, NIDDK, NIA), totaling over a decade of continuous funding for projects related to microbiome research, HIV/AIDS, cancer biomarkers, and metabolic studies. They actively contribute to education through teaching courses such as BIOSTAT 905: Linear Models and Inference at Duke University and previously taught statistics courses at the University of Wisconsin-Madison. Dr. Shi has also organized specialized workshop series including Quantitative Methods for HIV/AIDS, Microbiome, Immunology, and Cancer Bioinformatics.

• Epidemiology
• Physical Activity
• Sedentary Behavior
• +3 more

Dr. Kelley Gabriel is a Professor and Associate Dean in the School of Public Health at the University of Alabama at Birmingham (UAB), with a primary appointment in the Department of Epidemiology. She holds additional roles as a Senior Scientist in multiple UAB research centers, including the Nutrition Obesity Research Center (NORC) and the Integrative Center for Aging Research. Her research focuses on optimizing physical activity and sedentary behavior measurement in large epidemiological studies, with a particular emphasis on cardiorespiratory fitness, chronic disease prevention, and life-course health trajectories. Dr. Gabriel earned her PhD in Public Health (Epidemiology) from the University of Pittsburgh, an MS in Exercise Physiology from Northeastern University, and a BS in Athletic Training and Sports Medicine from Ithaca College. Her research interests include developing methodological strategies for precise physical activity measurement, examining the timing of physical fitness and disease risk, and leveraging cohort studies like CARDIA and SWAN. She has secured grants from NIH, NHLBI, and other agencies to support studies on the 24-hour movement paradigm, cognitive health, and cardiovascular outcomes. Key collaborations involve large-scale epidemiological cohorts such as the Coronary Artery Risk Development in Young Adults (CARDIA) and the Multi-Ethnic Study of Atherosclerosis (MESA). Her over 200 peer-reviewed publications and four book chapters reflect expertise in physical activity epidemiology and translational research. Grants include NIH-funded projects on cognitive resilience to Alzheimer’s disease, cardiovascular health trajectories, and the role of activity patterns in aging populations. Her work emphasizes translational strategies to improve public health through evidence-based lifestyle interventions. Dr. Gabriel leads multidisciplinary teams at UAB, contributing to initiatives like the Osteoporosis in Men (MrOS) Study and the Cooper Center Longitudinal Study. Her research integrates wearable technologies, biomarker analysis, and advanced statistical methods to address global health challenges related to physical activity and chronic disease.

• Cognitive Science
• Psychology
• Computational Modeling
• +6 more

Andrew Perfors is a Professor of Psychology at the University of Melbourne, leading the Computational Cognitive Science Lab and directing the Complex Human Data Hub. His research focuses on quantitative approaches to higher-order cognition, including concepts, language, decision-making, and misinformation dynamics. He holds a PhD from MIT and degrees from Stanford University. Education: PhD in Brain & Cognitive Sciences, Massachusetts Institute of Technology (2008) MA in Linguistics, Stanford University (2000) Bachelor of Science in Symbolic Systems, Stanford University (1999) Research Interests: He investigates computational models of cognition, cultural and social evolution, and the spread of misinformation. Recent work emphasizes the cognitive mechanisms underlying inductive reasoning, sampling assumptions, and trust in information. Key Projects: Understanding Information and Trust: From the Individual to the Population (2018–2025) Bridging the Meaning Gap: Computational Approach to Semantic Variation (2023–2027) Awards: Recipient of multiple best paper awards for contributions to cognitive science and computational linguistics. Labs & Groups: Leads the Complex Human Data Hub and co-leads the Computational Cognitive Science Lab, focusing on interdisciplinary research in human behavior and data science.

Lauren EmbersonView profile

Associate Professor

• Developmental Psychology
• Cognitive Psychology
• Infant Perception
• +4 more

Dr. Lauren Emberson (she/her/hers) is an Associate Professor in the Department of Psychology at the University of British Columbia, Faculty of Arts. She directs the Baby Learning Lab, which is part of UBC's Early Development Research Group, a consortium focused on infant and child development. Prior to her position at UBC, Dr. Emberson was an Assistant Professor at Princeton University where she co-founded and co-directed the Princeton Baby and Princeton Kid Labs. Education: Postdoctoral Associate, University of Rochester (PI Aslin) Ph.D, Cornell University (PIs Amso, Goldstein, Spivey) B.Sc, University of British Columbia Dr. Emberson's research focuses on learning, perception (audition, vision, crossmodal or multisensory), language development, face/object perception, and attention in infants. She investigates these capacities using behavioral and neuroimaging techniques, particularly fNIRS (functional near infrared spectroscopy), working primarily with very young infants (birth through 1 year) and preterm/premature infants. Her work examines how infants' learning capacities contribute to rapid development of perception in ecological contexts, with implications for understanding how early life experiences affect later outcomes. Analysis of Dr. Emberson's recent publications reveals a consistent focus on infant perception, learning mechanisms, and neuroimaging methodology. Her work increasingly incorporates advanced fNIRS techniques while maintaining focus on fundamental questions about how infants learn from their environment. There's a growing emphasis on individual differences, cross-cultural comparisons, and applications to infants facing developmental challenges. Dr. Emberson serves on the editorial board of Infancy (journal of the International Congress of Infancy Studies) and is a consulting editor for the Journal of Cognitive Neuroscience . Her research has been published in top journals including PNAS, Current Biology, Psychological Science, Cognition, Developmental Science, and the Journal of Neuroscience. Dr. Emberson has secured significant research funding from prestigious organizations including the Bill and Melinda Gates Foundation, James S. McDonnell Foundation, Natural Sciences and Engineering Research Council (NSERC), Canadian Institutes of Health Research (CIHR), and the National Institutes of Health (NIH). She collaborates with clinicians at BC Women's and Children's Hospitals to understand how different early life experiences impact learning and brain development. Dr. Emberson is currently accepting graduate students into her research program. The Baby Learning Lab, under Dr. Emberson's direction, is part of UBC's Early Developmental Research Group and collaborates with multiple institutions. The lab strives to provide interactive research experiences for infants and families while advancing scientific understanding of early cognitive development. The lab acknowledges that it operates on the traditional, ancestral, and unceded territory of the xʷməθkʷəy̓əm (Musqueam) people.

Julie MarkantView profile

Associate Professor

• Developmental Psychology
• Cognitive Development
• Attention and Learning Mechanisms
• +3 more

Dr. Julie Markant is an Associate Professor in the Department of Psychology at Tulane University and a Faculty Associate in the Tulane Brain Institute. Her research focuses on the interplay between selective attention and learning in infants and young children, emphasizing developmental and neurobehavioral perspectives. She uses behavioral, eye-tracking, genetic, MRI, and fNIRS methods to explore how attention control influences learning efficacy and vice versa. Education: Ph.D., 2010, University of Minnesota Her research interests include developmental attention mechanisms, perceptual learning, and how biological and contextual factors shape cognitive outcomes. Key themes involve understanding how infants and children selectively attend to information and how this attention drives learning processes. Recent work explores caregiver influence on attention, prenatal factors affecting infant attention, and the role of competing information in school-aged learning. Dr. Markant leads the Learning and Brain Development Lab , which investigates cognitive and neural mechanisms underlying attention and learning. She is actively recruiting graduate students from Tulane’s Psychology and Neuroscience Ph.D. programs. Her publications reflect a focus on attention biases, developmental learning dynamics, and methodological innovations like remote infant studies. Awards and honors are not explicitly listed in the provided text.

Steve LuckView profile

Professor

• Attention
• Working Memory
• Cognitive Neuroscience
• +3 more

Steve Luck is a Distinguished Professor at the University of California, Davis, holding appointments in the Department of Psychology and the Center for Mind and Brain (CMB). He served as CMB Director from 2009–2019 and is affiliated with the UC Davis MIND Institute and the Center for Neuroscience. His research focuses on attention, working memory, and cognitive dysfunction in psychiatric disorders (e.g., schizophrenia), employing ERP recordings, eye tracking, and behavioral methods. He is a leading developer of ERP methodologies, including the ERPLAB Toolbox and global ERP Boot Camp workshops. Education: Ph.D., Neurosciences, UC San Diego, 1993 M.S., Neurosciences, UC San Diego, 1989 B.A., Psychology, Reed College, 1986 Research Interests: Dr. Luck explores mechanisms of cognitive control, with a focus on working memory's role in guiding attention. His lab investigates ERP correlates of attentional deficits in schizophrenia and develops standardized ERP protocols. Recent work emphasizes multivariate decoding of EEG signals and transdiagnostic neurocognitive biomarkers. Awards: Troland Award (2001) APA Distinguished Scientific Award (1998) McGuigan Young Investigator Prize (2004) Elected Fellow, Society of Experimental Psychologists and AAAS Teaching & Leadership: Professor Luck pioneered hybrid course formats in Cognitive Science and teaches advanced topics in perception and cognitive neuroscience. He co-founded the UC Davis Cognitive Science major and advocates for innovative undergraduate education models. Labs & Collaborations: The Luck Lab integrates clinical and basic research, collaborating globally on ERP method development and schizophrenia biomarker studies. Key projects include ERP Core resources and the CNTRACS consortium for neurocognitive reliability studies.

• Autism Spectrum Disorders
• Child Psychiatry
• Developmental Disabilities
• +8 more

Katarzyna Chawarska is the Emily Fraser Beede Professor of Child Psychiatry at Yale School of Medicine, with primary affiliation in the Child Study Center and secondary appointments in Pediatrics and Statistics. She is a leading expert in autism spectrum disorders (ASD), directing the NIH Autism Center of Excellence, the Social and Affective Neuroscience of Autism Program, and the Yale Toddler Developmental Disabilities Clinic. Education: PhD in Psychology, Yale University (2000) Post-Doctoral Fellowship, Yale University School of Medicine (2000) MS in Psychology, Yale University MPhil in Psychology, Yale University MA, Jagiellonian University (1986) Her research focuses on identifying early diagnostic markers and novel treatment targets in ASD, particularly in infants at risk due to familial, genetic, or perinatal factors. Her work integrates clinical assessment, neuroimaging, eye-tracking, and longitudinal design to understand the neurodevelopmental trajectories of autism. Her recent publications explore disrupted functional connectivity, atypical visual attention, social anhedonia, and familial recurrence in autism. She employs advanced methodologies including fMRI, eye movement dynamics, and machine learning to identify biomarkers. Her research spans developmental neuroscience, clinical psychology, genetics, and pediatric psychiatry, with strong emphasis on early detection and intervention. Scientific Awards: No specific awards mentioned in the provided text. Dr. Chawarska is the Principal Investigator on active clinical trials, including studies on emotional development in infants at risk for ASD and regulation of visual attention and emotion in autism. She mentors research through her lab and collaborates extensively with experts such as Fred Volkmar, James McPartland, and Frederick Shic. She leads the Chawarska Lab, which is part of the Center for Brain & Mind Health and the Wu Tsai Institute at Yale.

Aurélie LabbeView profile

Professor

• Data Science
• Statistical Learning
• Machine Learning
• +7 more

Aurélie Labbe is a Full Professor in the Department of Decision Sciences at HEC Montréal, holding the prestigious FRQ-IVADO Chair in Data Science. Appointed as Co-Scientific Director – Academic Partnerships at IVADO in October 2023, she plays a key leadership role in establishing connections between IVADO and partner universities. Her academic journey includes a PhD in Statistics from the University of Waterloo, a Master's degree in Statistics from the University of Montreal, and dual Bachelor's degrees in Applied Mathematics and Social Sciences from Paris-Dauphine University and Pure Mathematics from Versailles-St Quentin University. Her research spans multiple interdisciplinary domains with a focus on developing advanced statistical and machine learning methodologies for big data analysis. Labbe's work bridges theoretical statistics with practical applications across diverse fields including genomics, neuroscience, transportation systems, and health informatics. She has made significant contributions to kernel methods, matrix factorization techniques, random forest applications, and spatiotemporal data analysis, with publications appearing in top journals across multiple disciplines. Analyzing her recent publications reveals a clear trend toward methodological innovation applied to complex real-world problems. Her work demonstrates expertise in handling high-dimensional data from diverse sources including neuroimaging, transportation networks, and genomic studies. The interdisciplinary nature of her research connects statistical theory with applications in healthcare, transportation safety, and biological sciences, reflecting her ability to develop methods that address domain-specific challenges while advancing statistical methodology. Holder of the FRQ-IVADO Chair in Data Science Member of the Center for Mathematical Research Training Professor Labbe actively mentors the next generation of data scientists, supervising numerous doctoral and master's students. Her supervision portfolio includes 1 doctoral thesis (2023), 4 master's theses (2022-2024), and 32 supervised projects spanning 2019-2025. Her students' work covers diverse applications including transportation safety, healthcare analytics, financial modeling, and environmental analysis. Through her leadership of the FRQ-IVADO Chair in Data Science, she coordinates research activities that integrate mathematical, statistical, and computer science expertise with domain knowledge from various data-generating fields. As Co-Scientific Director at IVADO, Professor Labbe leads efforts to establish connections with faculties and departments across five partner universities, integrating them into IVADO's research and knowledge transfer activities. Her leadership role positions her at the forefront of advancing data science research and applications in Quebec's academic ecosystem.

Sarah Dégallier RochatView profile

Professor

• Human-Computer Interaction
• Robotics
• Cobotics
• +6 more

Prof. Dr. Sarah Dégallier Rochat is Head of the strategic thematic field 'Humane Digital Transformation' at Bern University of Applied Sciences (BFH). She holds a joint appointment as Professor at the School of Engineering and Computer Science and serves as co-leader of the Computer Perception and Virtual Reality Lab (cpvrLab) within the Institute for Human-Centered Engineering. Her educational background includes: Ph.D. in Robotics from École Polytechnique Fédérale de Lausanne (EPFL) Master's in Mathematics from EPFL Teaching Diploma in Mathematics from Haute École Pédagogique de Lausanne Psychology studies at University of Lausanne Her research focuses on human-centered technological development with emphasis on: Designing inclusive human-machine interfaces through participatory approaches Developing upskilling strategies for industrial workforce adaptation Examining how techno-narratives shape societal perceptions of technology Creating collaborative robotic systems for agile manufacturing (Cobotics) Exploring mixed reality interfaces for worker augmentation Her publications demonstrate strong interdisciplinary focus on robotics and human-centered AI, with recent works exploring human augmentation in industry, ethical AI implementation, and participatory robot programming. The trajectory shows increasing emphasis on socio-technical systems and workforce empowerment. Significant awards include: Industry 4.0 Shapers Award (2019) CHIRA Best Paper Award (2023) She leads multiple research projects funded by Innosuisse, SNF, and EU programs, including: CODIMAN (Cobotics and workplace humanization) Agile Robotics for High-Mix Low-Volume Production Upskill at Work (digital literacy initiatives) Augmented workers with mixed reality interfaces As founder of Auto-Mate Robotics, she develops flexible robotic cells for industrial applications. She co-leads the Computer Perception and VR Lab and serves on advisory boards including the Swiss Cobotics Competence Center and EUA Task Force on AI.

Jennifer SomersView profile

Assistant Professor

• Developmental Psychology
• Clinical Psychology
• Psychophysiology
• +7 more

Jennifer Somers is an Assistant Professor in the Department of Psychological Sciences at Auburn University , directing the FLOWER Laboratory (Families: Leveraging Opportunities for Wellbeing and Resilience). Her research examines biobehavioral processes in parent-child interactions that influence depression and anxiety risks. Education: PhD in Clinical Psychology (Arizona State University, 2021) MA in Clinical Psychology (Arizona State University) BA in Psychology & English (Pomona College) Her work focuses on dyadic resilience , emotion regulation , and physiological synchrony in families. She has secured funding from NIMH, NSF, and private foundations. Recent publications analyze parent-child interactions , RSA synchrony , and transdiagnostic biomarkers spanning developmental psychology, clinical research, and behavioral science. Labs & Teams: FLOWER Lab investigates mechanisms to promote family resilience across the lifespan, integrating biological and environmental factors in mental health outcomes.

• Nursing & Midwifery Education
• Healthcare Ethics
• Nurse Prescribing
• +3 more

Dr. Chanel Watson is a Senior Lecturer and Programme Director in the School of Nursing and Midwifery at the Royal College of Surgeons in Ireland (RCSI), where she also serves as Deputy Director of Academic Affairs and coordinates Erasmus activities. She holds a Doctorate in Higher and Adult Education from Maynooth University (2020) and has additional postgraduate qualifications in Healthcare Ethics and Health Professions Education. Her research focuses on nursing education and prescribing practices, employing qualitative methodologies. She currently co-supervises 3 PhD students and is the primary supervisor for an additional 3. Dr. Watson has held roles in research ethics committees, including appointment to the National Research Ethics Committee for clinical trials in 2024, and has led national initiatives in nurse prescribing education frameworks. She has secured grants totaling over €1.6M for projects including nurse prescribing programs, gerontology education, and clinical trial coordination. Dr. Watson is an external examiner at multiple universities and actively reviews submissions for journals like Nursing Ethics and Journal of Nursing Education and Practice . Her professional engagements include leadership in national healthcare education reforms and international conference speaking engagements. Education: MSc in Healthcare Ethics and Law, RCSI (2004–2006) Post Graduate Diploma in Health Professions Education, RCSI (2014–2015) Doctorate in Higher and Adult Education, Maynooth University (2016–2020) Research Interests: Dr. Watson’s work emphasizes advancing nurse and midwife prescribing education, healthcare ethics, and clinical trial coordination. She has pioneered programs such as Ireland’s first Professional Certificate in Musculoskeletal Casting and Splinting. Her qualitative research explores nurse-patient interactions in acute care settings and the impact of burnout on pediatric nursing outcomes. She advocates for evidence-based practices in pain management and patient safety. Grants & Awards: €968,830 National Tender for PGDip Gerontology (2024) €450,000 Sexual Assault Forensic Nurse Examiner Education (2025) €225,180 Residential Care Education (2024) Fellowship of the Faculty of Nursing and Midwifery Committees & Leadership: National Lead for Nurse/Midwife Prescribing Competency Framework (HSE/NMBI) Member of National Research Ethics Committee CT-D External Examiner for University of South Wales and University College Cork

Louis CollinsView profile

Professor

• Neuroimaging
• Medical Image Processing
• Magnetic Resonance Imaging (MRI)
• +7 more

Louis Collins is a Professor in the Department of Biomedical Engineering and Department of Neurology and Neurosurgery at McGill University, with associate membership at the Center for Intelligent Machines. His work focuses on advanced medical imaging techniques for neurological applications. Key Expertise: Non-linear image registration, model-based segmentation, neuroimaging, MRI analysis Applications: Alzheimer's disease, Parkinson's disease, multiple sclerosis, epilepsy, schizophrenia Methodology: Development of computer vision algorithms for image-guided neurosurgery (IGNS), automated atlasing, and biomarker quantification Collins' research combines computational neuroanatomy with clinical translation, particularly in: Quantifying brain atrophy and anatomical variability across populations Optimizing MRI templates for improved diagnostic accuracy Developing tools like SEEGAtlas for surgical electrode classification Exploring neurophysiological fingerprints of neurodegenerative diseases His lab (NIST-Lab) actively pursues CIHR-funded projects on ultrasound-based image-guided neurosurgery and machine learning applications in clinical trials.