Edward S. Awh is a Professor in the Department of Psychology at the University of Chicago, affiliated with The Institute for Mind and Biology and the Grossman Institute for Neuroscience, Quantitative Biology and Human Behavior. His research focuses on behavioral and neural studies of memory and attention, employing psychophysics, EEG, and functional MRI. His lab investigates neural mechanisms underlying cognitive processes and their interrelationships. Research interests include tracking the contents of online memories and the locus of covert attention using neural decoding techniques. The lab collaborates on projects involving attention and memory studies, as detailed on their website: Awh/Vogel Lab . The lab currently seeks postdoctoral researchers to join ongoing projects using behavioral, EEG, and fMRI methodologies. Contact via awhvogellab@gmail.com .
Tom van Laer is an Associate Professor of Marketing and Deputy Head of Discipline, Research at The University of Sydney Business School. He is globally recognized as the leading expert in storytelling and narrative persuasion, currently occupying the top position on Elsevier's SciVal top 100 list for the most-cited researchers in this domain. His academic journey includes a BA and MA from Nijmegen and a PhD from Maastricht University. Dr. van Laer's research explores storytelling, persuasion, and messaging through an interdisciplinary approach that bridges behavioral experiments, quantitative modeling, and interpretive research. His work spans narrative transportation theory, consumer reviews analysis, digital storytelling, and the psychological mechanisms behind how stories influence consumer behavior. He has developed influential frameworks including the Extended Transportation-Imagery Model and narrative agency theory, with particular expertise in analyzing how stories shape responses to climate change communications and social conflict narratives. His publication record features articles in the most prestigious academic journals including the Journal of Consumer Research (where he serves as Area Editor), Journal of the Academy of Marketing Science, Journal of Business Ethics, Journal of Management Information Systems, and International Journal of Research in Marketing. His recent work shows a strong trend toward meta-analyses of narrative effects, climate change communication, and the psychological mechanisms of 'bleed' between fictional experiences and real-world behavior. Dr. van Laer is an active media commentator whose research has garnered extensive global coverage across Australia, France, Germany, the Netherlands, the UK, and the US, including national television and radio interviews. His media engagement focuses on storytelling in political campaigns, social media marketing, and the psychological impact of narratives in consumer contexts. He teaches MKTG3121 Advertising: Persuasive Principles and MKTG6006 Persuasive Advertising: Illuminating Dark Art, and has received recognition for both research and teaching excellence. His professional affiliations include the Association for Consumer Research, Australian Marketing Institute, Australian & New Zealand Marketing Academy, and International Society for the Study of Narrative. Dr. van Laer is a member of several university research centers including the Sydney Centre for Healthy Societies, Sydney Environment Institute, and Charles Perkins Centre, where he contributes his expertise in narrative persuasion to interdisciplinary research on societal challenges.
Shima Abdullateef is a Postdoctoral Research Fellow at the Centre for Medical Informatics within the Usher Institute, College of Medicine and Veterinary Medicine at the University of Edinburgh. Her work bridges biomedical engineering and clinical medicine through computational modeling and data science applications. Education: PhD in Biomedical Engineering, Brunel University London (2016-2020) MSc in Biomedical Engineering, University of Surrey (2014-2015) BSc in Biomedical Engineering (Bioelectrics), Science and Research IA University (awarded 2013) Research Focus: Dr. Abdullateef specializes in two interconnected domains: computational hemodynamics modeling arterial wave propagation and reflection phenomena, and machine learning-driven seizure detection using minimal-density EEG montages. Her arterial research investigates how vascular geometry impacts blood pressure dynamics, while her neuroscience work develops practical clinical tools for critical care seizure monitoring that reduce electrode requirements by 50-75% compared to standard EEG setups. Publication Trends: Her 15 most recent publications (2018-2025) reveal a strategic shift from pure cardiovascular modeling toward integrated neurological applications, with 60% focusing on seizure detection algorithms. The work consistently applies one-dimensional computational models and phase-synchrony analysis to solve clinical monitoring challenges, particularly in resource-constrained pediatric intensive care settings. Active Projects: A Window in the Brain: Developing a novel seizure detection tool for pediatric critical care (since 2020), funded through University of Edinburgh research channels Collaborative Environment: She operates within the Centre for Medical Informatics' interdisciplinary ecosystem, collaborating with clinicians from Edinburgh BioQuarter and data scientists to translate engineering solutions into clinical practice, with particular emphasis on making neurocritical care monitoring more accessible through reduced-sensor EEG technology.
Brian Zaboski, PhD, is an Assistant Professor of Psychiatry at the Yale School of Medicine. He holds dual expertise as a licensed Connecticut psychologist and Nationally Certified School Psychologist. His primary academic affiliation is with the Obsessive Compulsive Disorder Research Clinic within the Department of Psychiatry. Dr. Zaboski completed his PhD in School Psychology at the University of Florida, gaining clinical experience across school-based to acute inpatient settings. He specializes in cognitive-behavioral therapy (CBT) and exposure-based interventions for psychological disorders, with particular focus on OCD neurobiology and treatment innovation. His research integrates advanced quantitative methods and translational neuroscience to improve exposure therapy efficacy. Key areas include neurobiological network analysis, machine learning applications for OCD severity prediction, and neurofeedback treatment trials. He leads clinical trials investigating psilocybin therapy, pharmacotherapy combinations, and brain network changes in OCD patients. Dr. Zaboski's work has been funded by prestigious grants including the 2022 Brain & Behavior Research Foundation Young Investigator Award. Collaborations include prominent researchers like Christopher Pittenger, Terence Ching, and Michelle Hampson. His publications span peer-reviewed journals in psychiatry, neuroscience, and school psychology, with a focus on OCD mechanisms, treatment innovation, and school-based mental health interventions. Clinical trials he participates in explore novel treatments like troriluzole and psilocybin while investigating biomarkers for treatment response prediction.
Nicolas Gaspard is an Assistant Professor at Yale School of Medicine, specializing in neurology and critical care neurophysiology. His research focuses on epilepsy, particularly status epilepticus, NORSE/FIRES syndromes, and EEG monitoring in acute neurological conditions. He leads studies on therapeutic interventions (e.g., electrical stimulation, neuroprotective agents) and outcome prediction in cardiac arrest and epilepsy patients. Collaborations include teams at Yale and international institutions, with a focus on translational research and clinical practice improvements. Education: PhD from Université Libre de Bruxelles (2009). Research interests include neurocritical care, cortico-cortical connectivity, and optimizing EEG protocols in intensive care settings. His work bridges clinical practice and advanced neurophysiological techniques, aiming to improve patient outcomes in severe neurological emergencies. Key contributions include studies on single-pulse electrical stimulation reducing seizures and the role of sodium DL-3-ß-hydroxybutyrate in neuroprotection post-cardiac arrest. Publications (2023–2025) emphasize epilepsy syndromes, critical care EEG applications, and multicenter studies on treatment adherence and long-term outcomes. His team actively engages in NORSE/FIRES registry analyses to characterize disease progression and communication trends. Grants and funding details are not explicitly listed, but his research aligns with Yale’s focus on translational neurology.
Dr. Gary Glover is a Professor of Radiology (Radiological Sciences Lab) at Stanford University , with courtesy appointments in Psychology and Electrical Engineering. His work focuses on the physics and mathematics of MRI, particularly rapid scanning methods using spiral k-space trajectories for functional brain imaging and multimodal neuroimaging (fMRI/EEG/fPET/fNIRS) combined with neuromodulation techniques like TMS and transcranial ultrasound. Academic Appointments: Radiology, Psychology, Electrical Engineering Professional Affiliations: Bio-X, Stanford Cancer Institute, Wu Tsai Neurosciences Institute Research Interests include: Development of blood oxygen level-dependent (BOLD) and viscoelastic contrast in MRI Functional MR Elastography for brain activation mapping Optimization of MR-ARFI for transcranial ultrasound guidance Automated spinal cord segmentation (EPISeg) using machine learning Scientific Awards : National Academy of Engineering (2013) Gold Medal, ISMRM (2000) Steinmetz Award, General Electric (1985) Lauterbur Lecture, ISMRM (2018) Recent Publications analyze: Fast fMRI sampling and spurious signal correction Dissociated patterns in default mode network anti-correlations Neural correlates of collaborative behavior in triadic fMRI Salience network contributions to depression pathophysiology
University of Massachusetts Chan Medical SchoolUnited States
Christine Eckhardt is an Assistant Professor in the Department of Neurology at the T.H. Chan School of Medicine (UMass Chan Medical School), specializing in Neurocritical Care. She earned her MD from Harvard Medical School and holds an MS degree. Education: MD, Harvard Medical School, Boston, MA MS (unspecified field) Dr. Eckhardt's research focuses on neurocritical care, neurotoxicity syndromes, and EEG-based diagnostics. She develops quantitative EEG methods for assessing immune effector cell-associated neurotoxicity (ICANS) and delirium severity, with applications in CAR T-cell therapy and critical care neurology. Her recent publications (2022–2023) emphasize automated neurotoxicity detection , EEG signal processing , and health equity disparities in heart failure care. Key subfields include neurocritical care, computational neuroscience, and clinical outcome modeling.
Jorge Peña is a Professor at the University of California, Davis, specializing in computer-mediated communication and virtual environments. His research explores cognition, affect, and behavior in video games and VR/AR contexts, with a focus on avatar customization, social comparison, and health outcomes. He serves on the editorial board of the Journal of Computer-Mediated Communication and previously chaired the National Communication Association's Game Studies Division. Education: Ph.D. in Communication, Cornell University (2007) M.S. in Communication, Cornell University (2004) B.A. in Social & Organizational Psychology, Universidad de Santiago de Chile (2002) Research Interests: Peña investigates how digital environments shape social interactions, including priming effects in virtual contexts, avatar embodiment, and the impact of video games on empathy and prosocial behavior. His work combines quantitative methods like experiments and linguistic analysis. Publications Trends: Recent studies focus on VR/AR health applications (e.g., pain reduction, social connection), avatar appearance influencing physical activity, and the Proteus Effect. His work bridges communication studies with emerging technologies like AR and EEG hyperscanning. Awards & Grants: $25,000 UC Davis CAPR seed grant (2021) $63,000 UC systemwide Innovative Learning Technology Initiative grant (2018) His lab ( Victr Lab ) develops interventions using immersive technologies to address mental health and social issues. Current projects explore VR-based pain management and avatar-driven behavioral interventions.
Beth Smith, PT, DPT, PhD is an Associate Professor of Pediatrics and Biokinesiology & Physical Therapy at the University of Southern California. She directs the Infant Neuromotor Control Laboratory, where she leads research on neural control of movement during infancy and develops interventions for infants with or at risk for developmental delay. Dr. Smith's research focuses on several critical areas in pediatric development: Neural mechanisms underlying infant motor development Application of wearable sensor technology for objective movement measurement Early identification of developmental delays through quantitative analysis Evaluation of intervention effectiveness for at-risk infants Cross-cultural studies of infant development in diverse settings including rural Guatemala Her work demonstrates a strong integration of technology and clinical practice, with recent publications highlighting innovative approaches to measuring infant movement in natural environments. Dr. Smith's research on algorithmic detection of developmental disabilities using wearable sensors represents a significant advancement in early identification methods. Her studies on telehealth administration of developmental assessments have gained particular relevance following the COVID-19 pandemic, potentially expanding access to early intervention services globally. As director of the Infant Neuromotor Control Laboratory, Dr. Smith oversees a research program that bridges neuroscience, engineering, and clinical practice to improve outcomes for infants with developmental challenges. Her work has important implications for developing evidence-based interventions that can be implemented across diverse healthcare settings.
Jack Peltz, PhD, serves as an Assistant Professor in the Department of Psychology, Philosophy, and Neuroscience Programs at the State University of New York at Brockport. His academic career focuses on the intersection of developmental psychopathology, sleep science, and family systems dynamics, with particular emphasis on adolescent and college-age populations. His educational background includes: PhD in Clinical Psychology (Concentration: Developmental Psychopathology; Certificate: Quantitative Methods), University of Rochester, 2013 MA in Clinical Psychology, University of Rochester, 2010 MA in Child Development (Concentration: Clinical and Developmental Psychology), Tufts University, 2007 BA in Japanese, Middlebury College, 1996 Dr. Peltz's research program centers on developmental psychopathology and sleep regulation , investigating bidirectional relationships between sleep disturbances and family functioning. As a clinical psychologist specializing in behavioral sleep health for children and families, he develops community-based interventions to promote sleep hygiene. His work uniquely bridges quantitative methodology with clinical applications, examining how economic stressors, social media influences, and developmental transitions impact sleep-wake patterns. Analysis of his recent publications (2023-2025) reveals three dominant research trajectories: (1) sleep as a mediator between adverse childhood experiences and psychological outcomes, (2) technology-mediated sleep disruptions (including wearable devices and social media), and (3) developmental transitions (puberty, college entry) affecting sleep-family dynamics. His methodological approach combines longitudinal designs, ambulatory EEG, and mixed-methods analysis to capture real-time sleep-family interactions across diverse populations including youth with visual impairments.
New Jersey Institute of Technology (NJIT)United States
Xiaobo Li is a Professor in the Department of Bio-Medical Engineering at New Jersey Institute of Technology. Holding a Ph.D. in Computer Aided Geometric Design from the University of Birmingham and a B.S. in Automation from Nanjing University of Aeronautics, their research bridges computational methods with neuroimaging and psychiatric disorder analysis. Ph.D., University of Birmingham (Computer Aided Geometric Design, 2004) B.S., Nanjing University of Aeronautics (Automation, 1999) Dr. Li’s work focuses on applying machine learning and graph theory to understand brain network abnormalities in conditions like ADHD , schizophrenia , and traumatic brain injury . Their studies analyze structural-functional connectivity , reward processing , and gut-brain axis interactions using fMRI , fNIRS , and diffusion tensor imaging . Recent publications highlight their development of tools like the GAT-FD MATLAB toolbox for brain network analysis and their exploration of multimodal MRI in schizophrenia diagnosis. They also investigate the neurobiological effects of photobiomodulation and vision therapy interventions.
Swiss Federal Institute of Technology in LausanneSwitzerland
Kathryn Hess Bellwald is a Full Professor at École Polytechnique Fédérale de Lausanne (EPFL) in both the School of Life Sciences and School of Basic Sciences . She leads the Laboratory for Topology and Neuroscience and serves as Academic Director for the Euler Programme . Her work bridges pure mathematics and interdisciplinary applications in neuroscience, materials science, and data analysis. Education : PhD in Mathematics (MIT, 1989), preceded by positions at Stockholm, Nice, and Toronto universities. Her research spans algebraic topology , homotopy theory , operad theory , and algebraic K-theory , with applications in neuroscience and materials science . She has pioneered topological data analysis methods for classifying neuronal morphologies , microglia phenotypes , and nanoporous materials , creating a parameter-free framework linking neural network structure to activity. The 15 most recent publications highlight her work on topological inverse problems , neuroinflammation , and equivariant homotopy . These studies often involve collaborations with the Blue Brain Project and EPFL teams in neuroscience , machine learning , and materials science . Scientific Awards : Fellow, American Mathematical Society (2017); Distinguished Speaker, European Mathematical Society (2017); Crédit Suisse Teaching Prize (2012); Polysphère d'Or (2013); Full Member, Swiss Academy of Engineering Sciences (2016); Chaire de la Vallée Poussin (2023); Fellow, Association for Women in Mathematics (2024). She has mentored numerous PhD students in mathematics and neuroscience, including Adélie Eliane Garin , Varvara Karpova , and Dimitri Zaganidis . Her EPFL Mathematics affiliations include the DIVISION MATH , while her Neuroscience lab operates under the Brain Mind Institute (BMI) in the School of Life Sciences (SV). Grants and collaborations are evident in her work on neurodegenerative diseases , synthetic materials , and machine learning frameworks .
Dr. Jennifer Ahjin Kim is an Assistant Professor in the Department of Neurology at Yale School of Medicine. She specializes in neurocritical care, focusing on quantitative analysis of electroencephalography (EEG) and neuroimaging for early diagnosis and treatment optimization in patients with severe neurologic injuries. Her clinical interests include traumatic brain injury, subarachnoid hemorrhage, stroke, and post-traumatic epilepsy. PhD in Neuroscience, Brown University (2012) MD from Brown University (2012) Neurology Residency, Massachusetts General Hospital/Brigham & Women's Hospital (2016) Neurocritical Care Fellowship, Massachusetts General Hospital/Brigham & Women's Hospital (2019) Dr. Kim’s research integrates multimodal data (EEG, MRI, CT) with machine learning to predict secondary complications after brain injuries. She actively contributes to clinical trials like BOOST3 and ASPIRE, aiming to improve outcomes for patients with traumatic brain injury, stroke, and hemorrhage. Her recent work emphasizes automated detection of epileptiform discharges, predictive modeling for delayed cerebral ischemia, and application of NLP to CT reports. Collaborations include frequent partnerships with Guido Falcone, Lawrence Hirsch, and Emily Gilmore. Dr. Kim leads the Kim Laboratory, which focuses on bedside monitoring technologies and secondary prevention strategies.
Srinivas Sridhar is a University Distinguished Professor of Physics, Biomedical Engineering, and Chemical Engineering at Northeastern University, with a secondary appointment as Lecturer on Radiation Oncology at Harvard Medical School. He previously served as Vice Provost for Research at Northeastern University (2004–2008), overseeing its research portfolio. As an elected Fellow of the American Physical Society and the American Institute of Medical and Biological Engineering, his research spans nanomedicine, neurotechnology, drug delivery, and quantitative MRI, with over 450 publications and patents. He founded the Nanomedicine Innovation Center and directs major NIH/NSF programs like CaNCURE and IGERT, focusing on undergraduate and graduate training in nanomedicine, particularly for underrepresented communities. His research interests include Nanomedicine Neurotechnology Quantitative MRI Drug Delivery Systems Metamaterials and Nanophotonics Quantum Chaos Superconductivity . Recent work involves machine learning-enhanced diagnostics for glaucoma, engineered nanoparticles for BRCA-deficient cancers, and portable neuro-ophthalmic devices. His publications from 2025–2017 reflect interdisciplinary applications in oncology, neurology, and materials science, with a focus on therapeutic and diagnostic innovation. Scientific accolades include the 2016 Biomedical Engineering Society Diversity Award University Distinguished Professorship . As an educator and entrepreneur, he has trained over 120 researchers, developed first-of-their-kind nanomedicine courses, and founded companies commercializing technologies like QUTE-CE MRI. His lab leads projects on cancer nanomedicine, quantitative imaging, and nanoscale magnetism, supported by grants from NIH, NSF, DoD, and private foundations.
Mark Kramer is a Professor in the Department of Mathematics & Statistics at Boston University. He belongs to the Applied Mathematics research group, focusing on mathematical, statistical, and machine learning approaches to characterize brain activity. His work bridges data-driven neuroscience with computational methods, exploring topics like biophysical models of neurons, field models of neural populations in epilepsy, and theoretical questions about brain rhythms. His research interests include: Biophysical modeling of single-neuron dynamics Neural population activity in pathological states Machine learning for detecting abnormal brain rhythms Analysis of cross-frequency coupling and coherence Kramer has developed educational resources like Case Studies in Neural Data Analysis using both MATLAB and Python. These materials teach practical data analysis techniques for spike trains and field data, emphasizing hands-on implementation over theoretical mathematics. He has received funding from NIH and NSF for computational neuroscience projects. His recent publications focus on epilepsy research, sleep spindle analysis, and neural signal processing. The work spans from developing statistical frameworks to understanding network dynamics in seizure termination and exploring phase consistency in neural data. Notably, his coherence studies revealed non-intuitive coupling patterns between brain regions, demonstrating that low-amplitude rhythms can be more informative than dominant ones.
