Dr. Christy Wolfe is a faculty member at Bellarmine University's College of Arts and Sciences, teaching in the Psychology and Neuroscience programs. She earned her BS in Psychology from the University of Virginia's College at Wise, MA in Experimental Psychology from East Tennessee State University, and PhD in Psychological Sciences (Developmental Processes) from Virginia Tech. Research Focus: Development of executive functioning in infants and children, cognition-emotion integration, and psychophysiological correlates of temperament. Key Methods: EEG, heart rate monitoring, longitudinal assessments. Her publications span topics including developmental neuropsychology, behavioral development, and neurocognitive mechanisms. She serves as faculty advisor for Psi Chi and Chair of the Institutional Review Board, demonstrating leadership in academic and ethical oversight.
Erika Nyhus is an Associate Professor of Neuroscience and Psychology at Bowdoin College. Her research focuses on the neural substrates of higher-level cognition, particularly executive functioning and episodic memory, using EEG, ERP, and fMRI techniques. She teaches courses in cognitive neuroscience and memory, emphasizing scientific thinking. Post-doctoral Education: Cognitive, Linguistic, and Psychological Sciences, Brown University (2010–2013) PhD: Cognitive Science, Neuroscience, and Psychology, University of Colorado-Boulder (2010) MA: Psychology, University of Colorado-Boulder (2006) BA: Psychology and Anthropology, University of California-Berkeley (2003) Her research examines how neural oscillations (e.g., theta, gamma, alpha) mediate memory retrieval, executive control, and attention. Recent work investigates tACS for memory enhancement and the role of mindfulness meditation in modulating brain activity. She integrates behavioral and neuroimaging methods to explore interactions between brain systems during cognition. The Nyhus Lab leverages EEG to study neural dynamics in memory and attention, with a focus on theta/gamma oscillations during retrieval and spatial navigation. Publications highlight applications of mindfulness, aging-related memory differences, and genetic influences on ERP patterns. Collaborative projects involve undergraduate students in experimental design, data analysis, and co-authorship. Lab members include honors students and research assistants working on EEG paradigms, spatial memory, and neurostimulation. Her outreach includes public science articles (e.g., The Conversation) and media coverage in Bowdoin News and the Cognitive Neuroscience Society. Outside academia, she enjoys yoga, outdoor activities in Maine, and travel, including a year in Spain and the Camino de Santiago pilgrimage.
Ignacio Cifre León is an Associate Professor in the Psychology and Speech Therapy Department at the Blanquerna School of Psychology, Education and Sports Sciences, Universitat Ramon Llull. His research focuses on neuroscience, functional connectivity, chronic pain, fibromyalgia, Alzheimer’s disease, and health communication, using advanced neuroimaging techniques like fMRI and EEG. His research interests center on understanding brain dynamics in neurological and psychological conditions. He investigates functional connectivity patterns in Alzheimer’s, fibromyalgia, and chronic pain, and explores brain complexity related to sleep and aging. His work also extends to mental health in high-risk populations, such as refugee rescue workers, and the psychometric adaptation of clinical tools for aphasia. The recent articles highlight a strong trend in applying nonlinear and multiscale methods to neuroimaging data, integrating fractal analysis, functional connectivity, and brain network dynamics across diverse conditions. His work bridges neuroscience, psychology, and biomedical engineering, with applications in clinical assessment and intervention. He leads and participates in several funded research projects, including FluctCoFuNLin, FASTCONN, and COMSAL, supported by national agencies such as Agencia Estatal de Investigación and MINECO. These projects focus on dynamical functional connectivity, health communication, and objective brain dynamics measurement. He is a core member of the 'Comunicació i Salut' (COMSAL) research group, collaborating with interdisciplinary teams across psychology, speech therapy, and neuroscience. His work involves both primary investigation and collaborative research with experts in trauma, aging, and language disorders.
Jeffrey S. Katz is a Professor and the Mike and Leann Rowe Endowed Professor in the Department of Psychological Sciences at Auburn University's College of Liberal Arts. He serves as the Director of the Cognitive and Behavioral Sciences (CaBS) Program and leads the Comparative Cognition Lab. His research integrates behavioral experiments and functional neuroimaging across species, including humans, dogs, pigeons, and nonhuman primates. His research interests focus on the mechanisms of learning and cognition, particularly change detection, concept learning, and the neural and behavioral correlates of working dogs. He utilizes traditional operant conditioning methods and fMRI to explore cross-species cognitive processes. Ongoing projects include Canine Neuroimaging, Canine Cognition, Cross-Species Change Detection, Human Concept Learning in fMRI, and Taste Short-Term Memory, conducted at Auburn's MRI Research Center, Canine Performance Sciences, and the Biological Research Facility. The most recent publications highlight a strong emphasis on canine cognition, including word recognition, olfactory memory, and abstract concept learning. There is also a growing integration of human-animal interaction research with applications to human-robot attachment. His work spans cognitive psychology, neuroscience, and comparative behavior, with a consistent focus on translational and applied cognitive science. APA Division 3 Young Investigator Award (2001) Psi Chi Excellence in Undergraduate Teaching (2001-2002, 2012-2013) CLA Early Career Teaching Award (2004-2005) APA Fellow, Division 3 (2007) and Division 6 (2008) Auburn University Alumni Professorship (2006-2011) Gerald and Emily Leischuck Endowed Presidential Award for Excellence in Teaching (2015) Honors College Professor of the Year (2016) Comparative Cognition Society Recognition of Service Award (2014) Katz has secured research funding from the National Science Foundation (NSF) and the National Institute of Mental Health (NIMH). He has mentored numerous graduate and undergraduate students, many of whom have contributed to publications and ongoing projects. He teaches courses such as Cognitive Neuroscience, Animal Cognition, and Advanced Experimental Psychology. He is also actively involved in public outreach, including the Auburn Brain Camp and media appearances on canine cognition and brain research. His lab, the Comparative Cognition Lab, fosters interdisciplinary research and training in cognitive science, with strong ties to Canine Performance Sciences and the MRI Research Center. The lab provides hands-on research opportunities for students interested in animal and human cognition.
Alfredo Benso is a Full Professor in the Department of Control and Computer Science (DAUIN) at the Polytechnic University of Turin, where he is also a member of the Interdepartmental Center PolitoBIOMed Lab - Biomedical Engineering Lab. He has been continuously involved in the Doctoral College for Computer and Systems Engineering since 2008, guiding PhD education across numerous cycles. His academic roles span teaching and research leadership in bioinformatics, systems biology, and computer engineering. Research interests: Bioinformatics and computational biology Systems biology and gene regulatory networks Artificial intelligence and machine learning in biomedicine Molecular modeling and multiscale simulation Biological database systems and data integration Health informatics and public health modeling His recent publications reflect a strong trend in applying AI and machine learning to biological and medical challenges, including protein function prediction, Alzheimer’s and Multiple Sclerosis modeling, food fraud detection, and viral genome analysis. These works span journals and conferences in bioinformatics, computational biology, and biomedical engineering, demonstrating interdisciplinary innovation. Scientific Awards: BIOINFORMATICS 2014 BEST PAPER AWARD (INSTICC, United Kingdom) Advising and Grants: He supervises PhD students, including Sofia Ostellino, and leads major research initiatives such as the BIGMECH (2023–2025) and FISHUB (2016–2018) projects. He has served as Scientific Director for collaborative agreements with public administrations and as Principal Investigator on EU, national (PRIN), and regional research grants focused on bioinformatics, space systems, and reliable digital technologies. Labs and Teams: He is a key member of the SBG - System Biology Group (DAUIN) and contributes to PolitoBIOMed Lab, fostering collaborative research in biomedical engineering and computational biology.
Alexa Pichet Binette is an Associate Professor and researcher at the Université de Montréal's Faculty of Medicine, Department of Pharmacology and Physiology, and the Centre de Recherche de l'Institut Universitaire de Gériatrie de Montréal (CRIUGM). She holds a PhD in Neuroscience from McGill University and completed postdoctoral training at Lund University, Sweden. Her research focuses on understanding neurodegenerative processes in aging and Alzheimer's disease, utilizing multimodal biomarker approaches such as neuroimaging (PET/ MRI), blood-based markers, and proteomics across international cohorts. Her work is funded by the Fonds de recherche du Québec and the IUGM Foundation. Affiliations: CRIUGM, Institut de Génie Biomédical (IGB), CIUSSS Centre-Sud-de-l’Île-de-Montréal Recruitment: Actively seeking master’s/PhD students and postdocs Key research interests include Alzheimer's pathophysiology, biomarker development, and early detection strategies. Her lab analyzes longitudinal data to track disease progression and identify therapeutic targets. Recent studies emphasize tau and amyloid pathology interactions, vascular influences, and plasma biomarker validation. Awards and grants are not explicitly listed, but her work is supported by major research funds. Publications highlight advancements in tau PET imaging, plasma biomarkers, and machine learning applications in neurodegenerative disease prediction. Ongoing collaborations aim to translate findings into clinical practice, emphasizing prevention and early intervention strategies.
Dr. Wei-Tang Chang is an Assistant Professor in the Department of Radiology at the University of North Carolina School of Medicine. His research focuses on advancing ultrahigh-resolution functional and diffusion MRI techniques, with emphasis on improving spatial and temporal resolution while reducing scan times. Key projects include submillimeter isotropic-resolution fMRI for hippocampal subfield analysis (funded by NIH R21), novel dMRI approaches to overcome resolution limits, and clinical translation of robust imaging methods resistant to motion/noise artifacts. Dr. Chang holds a PhD in Biomedical Engineering from National Taiwan University and completed postdoctoral training at the Martinos Center for Biomedical Imaging (MGH), Massachusetts General Hospital, and Singapore BioImaging Consortium (SBIC). His research innovations include SORDINO fMRI for awake rodent imaging, pPRISM diffusion MRI for submillimeter resolution, and ZTE pulse sequences for ultra-fast acquisitions. Awards include the 2011 OHBM Trainee Award for work on MEG source localization and fMRI temporal resolution breakthroughs. Current work bridges basic neuroimaging science with clinical applications, particularly in neurodegenerative disease biomarker development and rodent disease model studies. Education: PhD in Biomedical Engineering, National Taiwan University Postdoctoral Fellowships: Martinos Center for Biomedical Imaging (MGH) Singapore BioImaging Consortium (SBIC) Key Technologies Developed: ZTE pulse sequences (25 ms temporal resolution fMRI) pPRISM diffusion MRI (navigator-free submillimeter imaging) Draining-vein suppression layer-dependent fMRI Awards & Funding: NIH R21 Grant (2019) for hippocampal subfield fMRI OHBM Trainee Award (2011) Dr. Chang's translational focus involves adapting laboratory innovations for clinical use, with particular interest in Alzheimer's disease biomarkers through hippocampal network analysis and Huntington's disease models using rodent functional connectivity studies. His lab actively develops open-source MRI reconstruction algorithms and collaborates internationally on multi-center neuroimaging projects.
Affiliations & Roles Rachel Romeo is an Assistant Professor in the Department of Human Development and Quantitative Methodology at the University of Maryland College Park , affiliated with the College of Education . She directs the LEAD Lab and holds faculty roles in the Neuroscience and Cognitive Science interdisciplinary program. Additional affiliations include a courtesy appointment in Hearing and Speech Sciences and memberships in the Language Science Center , Field Committee in Developmental Science , and Brain Behavior Institute . She is licensed in Maryland as a Speech Language Pathologist with clinical certification from ASHA. Education B.A. in Psychology and Linguistics, University of Pennsylvania (2011) M.Sc. in Language Sciences, University College London (via Fulbright Fellowship) Ph.D. in Speech and Hearing Bioscience and Technology, Harvard/MIT Program (2018) Clinical training: MGH Institute of Health Professions Postdoctoral training: Boston Children’s Hospital, Harvard, MIT Research Focus Romeo’s work examines how early experiences shape brain and cognitive development , with emphasis on socioeconomic influences, neurodevelopmental disorders, and translational applications to education/social policy. Key areas include language acquisition mechanisms, neural plasticity in conversational environments, and equity in developmental neuroscience research. Recent studies investigate caregiver-child neural synchrony, speech input variability’s impact on vocabulary, and fNIRS methodology improvements for diverse populations. Awards & Recognition Fulbright Fellowship (UCL) American Speech-Language-Hearing Association Clinical Competence Certification Lab & Interventions LEAD Lab research focuses on Preschool Language and Neural Engagement Study , exploring how socioeconomic factors and conversational environments affect early learning. Projects emphasize precision interventions for disadvantaged populations, including neuroimaging-based approaches and family-centered communication strategies. Current work addresses digital media’s neurodevelopmental impacts and equity in scientific participation.
Dr. Amélie Gourdon-Kanhukamwe is a Lecturer in Neuroscience and Psychology Education at King's College London's Department of Neuroimaging, part of the Institute of Psychiatry, Psychology & Neuroscience. She specializes in experimental social psychology, focusing on decision-making under uncertainty, health communication, and neurodivergence in academia. She contributes to the Psychological Science Accelerator for large-scale replication studies and actively promotes open scholarship practices. As deputy programme leader for the BSc Neuroscience and Psychology, she teaches statistics using R and open science principles. Research Interests : Judgment/decision-making, verbal uncertainty interpretation, autonomy-focused health communication, neurodivergence in academia, and open science methodologies. Current projects include workplace accommodations for neurodivergent individuals and biases in medical communication involving neurodivergent patients. Publications Trends : Recent work emphasizes replicability in psychological science, neurodiversity advocacy, and pedagogical strategies for open scholarship. Key contributions include multi-lab cognitive dissonance studies and frameworks for participatory research in neurodiversity. Awards : None explicitly listed in provided texts. Grants/Advising : Collaborates with students on neurodivergence research projects. Leads initiatives integrating open science into curricula and promoting accessible academic practices. Active member of the Society for Improvement of Psychological Science and Psychological Science Accelerator. Labs/Teams : Manages a lab focused on replicability and neurodiversity research, collaborating internationally through multi-institutional projects.
Bjørn-Eivind Kirsebom serves as an Associate Professor II at UiT The Arctic University of Norway, specializing in clinical neuropsychology and neurology with a particular focus on dementia diseases. He holds the position of Head of the Dementia Disease Initiation (DDI) department in Tromsø, demonstrating his leadership in this critical research area. His research interests center on Alzheimer's disease, biomarker development, and regression-based norms for neuropsychological assessment. Dr. Kirsebom's work spans both clinical practice and research, contributing significantly to early diagnosis methods and monitoring of cognitive decline. His expertise in developing standardized cognitive testing protocols for Norwegian populations has been instrumental in establishing culturally appropriate diagnostic criteria. Analysis of Dr. Kirsebom's recent publications (2023-2025) reveals a strong emphasis on plasma biomarkers, particularly tau proteins, and their relationship to Alzheimer's disease progression. His research has explored the relationship between phosphorylated tau levels and cognitive impairment severity, blood-based biomarkers for early detection, and regression-based norms for cognitive testing that account for demographic variables. ResearchGate profile available ORCID: https://orcid.org/0000-0002-1413-9578 Dr. Kirsebom actively collaborates with researchers across Norway and internationally, as evidenced by his numerous co-authored publications. His work bridges clinical practice and research, with practical implications for improving diagnostic accuracy and understanding disease progression in dementia. He contributes to multiple research projects focused on early detection of Alzheimer's disease and related dementias, with particular attention to biomarker development and validation.
Hegang Chen, PhD, serves as Professor in the Department of Epidemiology and Public Health at the University of Maryland School of Medicine. He is a lead statistician for the General Clinical Research Center (GCRC) and member of the Hormone Responsive Cancers Program within the Marlene and Stewart Greenebaum Cancer Center, with extensive collaborative experience in clinical trials and epidemiological research since joining in 2002. His academic credentials include: Ph.D. in Statistics from the University of Illinois M.S. in Mathematics from the University of Mississippi Dr. Chen's research centers on statistical methodology development—including optimal experimental design, generalized mixed linear models, and machine learning applications for molecular biology and real-time clinical decision support (e.g., predicting blood transfusion needs)—and biomedical collaborations spanning cancer, infectious diseases, trauma, public health, and pharmacogenomics. His work has been published in premier journals like Nature, JAMA, and Annals of Statistics. Analysis of his recent publications (2020-2025) reveals a dominant focus on predictive analytics for traumatic brain injury outcomes, blood transfusion prediction, and lung cancer diagnosis using real-time physiological monitoring and machine learning. This trend demonstrates a translational shift toward operationalizing statistical methods in critical care decision support systems. No scientific awards were mentioned in the provided text. While no specific advisees are listed, Dr. Chen's leadership in the GCRC and extensive collaborative network across trauma, oncology, and global health indicate active mentorship within multidisciplinary teams. His grant involvement is evidenced by NIH-funded GCRC work and high-impact publications in clinical domains. Dr. Chen maintains key affiliations with the General Clinical Research Center as lead statistician and the Hormone Responsive Cancers Program, where he integrates advanced statistical methodologies into translational cancer research and clinical trial design.
Leonard Edward White is an Associate Professor in Neurology at Duke University, with additional appointments in Psychology and Neuroscience, Orthopaedic Surgery, and Neurobiology. He serves as Associate Director of the Duke Institute for Brain Sciences and Director of Undergraduate Studies of Neuroscience. His academic career spans over three decades since earning his Ph.D. from Washington University in St. Louis in 1992. Dr. White's research focuses on the structure and function of the mammalian brain, particularly through the development of advanced magnetic resonance methods for interrogating brain structure. His work combines light sheet microscopy with MRI techniques to provide new insights into microscopic brain structure, whole-brain connectivity, and how neural tissue constrains connectivity in animal models. He maintains a sustained interest in how early sensorimotor experience influences neural circuit formation and maturation in the cerebral cortex, as well as the intersection of brain sciences with humanities. His recent publications (2020-2025) reveal a strong emphasis on high-resolution brain imaging techniques, particularly MRI and light sheet microscopy for creating detailed brain atlases. His work spans multiple species (mouse, rat, human) and addresses fundamental questions in neuroanatomy, connectomics, and developmental neuroscience. Notably, he has been developing the Duke Mouse Brain Atlas and exploring the impact of prenatal drug exposure on brain development. Dr. White has secured significant research funding, including the current 'Ultra-high Resolution Structural Connectome Atlases of the Animal Brain' grant (2022-2026) from the University of Pittsburgh, and previously led NIH-funded projects on visual cortex development spanning nearly two decades. He is deeply involved in medical education, serving as Director of Undergraduate Studies of Neuroscience and developing innovative approaches to teaching neuroanatomy. His educational scholarship includes work on integrating art into medical education and revitalizing neuroanatomy teaching methods. He also maintains an active presence in neurohumanities, exploring the intersection of neuroscience with arts and humanities.
Stephen E. Sallan, MD , is a Professor of Pediatrics at Harvard Medical School and a Physician at Dana-Farber Cancer Institute and Children's Hospital . His career spans over five decades in pediatric hematology/oncology , with a focus on acute lymphoblastic leukemia (ALL) and pediatric brain tumors . Education : MD, Wayne State University School of Medicine (1967) Residencies : Boston Floating Hospital (1968), Children's Hospital of Philadelphia (1969), Hospital for Sick Children, London (1970) Fellowship : Pediatric Oncology, Children's Hospital/DFCI (1972) Leadership Roles : Chief of Staff (1995), Chairman of Medical Staff Executive Committee (1995), Chief of Staff Emeritus (2012) Dr. Sallan's research integrates genetic heterogeneity , disease recurrence , and drug resistance in ALL, with efforts to develop targeted therapies like tumor vaccines and antiangiogenesis agents. His work addresses long-term treatment toxicities (cardiac, skeletal, neurocognitive), particularly in survivors of childhood cancers. His 15 most recent publications (2024–2018) demonstrate ongoing engagement with pharmacogenomics, thrombosis risk models, dietary interventions, and molecular markers in brain tumors. Key subfields include TRK-C in medulloblastoma , asparaginase complications , and DFCI ALL Consortium Protocols . Scientific Awards : Distinguished Alumni Award, Wayne State University School of Medicine (1997) James Carreras Prize for International Pediatrician of the Year (1987) As a leader in pediatric leukemia research , Dr. Sallan has shaped treatment protocols that minimize late effects while improving survival. He collaborates with multidisciplinary teams in neuro-oncology and pharmacogenomics, maintaining active roles in clinical trials and laboratory investigations.
Dr. Sonja de Zwarte is an Assistant Professor in the Department of Psychology within the Faculty of Social and Behavioral Sciences at Utrecht University. Her office is located in the Martinus J. Langeveld building at Heidelberglaan 1 in Utrecht. She maintains an active research program focusing on developmental psychology and neuroscience, with particular emphasis on early childhood development and brain imaging. Her research interests span multiple interconnected domains including the critical first 1001 days of child development, prenatal brain development, schizophrenia and bipolar disorder research, genetic risk factors, and the application of artificial intelligence in behavioral analysis. Her work often involves large-scale collaborative efforts through international consortia such as ENIGMA (Enhancing Neuro Imaging Genetics Through Meta Analysis), which enables powerful analyses of brain structure and function across thousands of participants worldwide. Dr. de Zwarte's publication record demonstrates consistent productivity with numerous high-impact publications in top neuroscience and psychiatry journals. Her recent work shows a clear trajectory integrating advanced neuroimaging techniques with genetic analysis to understand developmental pathways in both typical and at-risk populations. She has made significant contributions to understanding how genetic risk factors manifest in brain structure and cognitive function, particularly in relation to schizophrenia and bipolar disorder. Her methodological expertise spans both traditional neuroimaging analysis and cutting-edge applications of artificial intelligence to behavioral data, as evidenced by her recent work on automated segmentation of fetal brain structures using deep learning and automated analysis of parent-child interactions. This interdisciplinary approach positions her work at the intersection of developmental psychology, clinical neuroscience, and computational methods.
Yajuan Si is a Researcher at the University of Michigan , affiliated with the School of Public Health and the Department of Biostatistics . Her work focuses on advancing statistical methodologies in survey inference and data analysis. Education: PhD from Duke University (2012) Email: yajuan@umich.edu Address: ISR 4014, 426 Thompson St, Ann Arbor, MI 48104 Research Interests Dr. Si specializes in Bayesian statistics , survey inference , missing data analysis , and confidentiality protection techniques . Her projects address critical challenges such as: Statistical adjustments for nonresponse bias in complex surveys Enhancing synthetic data methods for privacy-preserving analysis Population heterogeneity correction in neuroimaging studies Unifying multilevel regression and poststratification frameworks Selected Publications Her recent work spans Bayesian modeling applications in education surveys, massive data imputation , and healthcare data analysis . Key themes include survey weighting, computational scalability, and bias correction. Collaborative Efforts Dr. Si collaborates with multidisciplinary teams across public health, economics, and social sciences, applying her statistical expertise to real-world problems in COVID-19 transmission modeling and demographic research .
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