Stanford University
Showing 3,451-3,500 of 14,417 Results
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Cassondra Eng
Adjunct Lecturer, Psychiatry and Behavioral Sciences - Interdisciplinary Brain Sciences
BioDr. Cassondra (Cassie) Eng is an NIH-funded T32 Postdoctoral Scholar in Sports Neuroscience at Stanford University’s Center for Interdisciplinary Brain Sciences Research (CIBSR). Her research focuses on optimizing immersive interventions that promote neurological, cognitive, and physical health outcomes. Dr. Eng investigates attentional processes in technologically enhanced contexts, with an emphasis on the brain-behavior mechanisms that drive differential outcomes. She specializes in using mobile functional near-infrared spectroscopy (fNIRS), a modern neuroimaging technique that is noninvasive, wearable, and allows for full mobility in naturalistic settings—making it ideal for studying human behavior in ecologically relevant settings.
Dr. Eng programs exercise-based interventions using game engines to enhance participant engagement and data automation, supplementing neurocognitive assessments with physiological measures across populations from childhood to adulthood. Her work incorporates task-based and clinical norm-referenced assessments of cognition, quantitative and qualitative assessments of learning in VR/XR contexts, eye tracking, EEG, cardiovascular measures related to performance and stress, and data analysis techniques using mixed-effects modeling, multivariate analysis, and longitudinal data analysis.
Dr. Eng earned her Ph.D. in Cognitive Neuroscience and Developmental Psychology from Carnegie Mellon University, where she also received a Program for Interdisciplinary Education Research (PIER) Certification through the Institute of Education Sciences. Her work specializes in educational neuroscience, an interdisciplinary field bridging cognitive science, psychology, educational technology, human-computer interaction, computer science, and related disciplines to identify optimal learning contexts that support brain development and cognitive skills essential for overall well-being and health. -
Claudia Engel
Academic Technology Specialist, Center for Interdisciplinary Digital Research
BioClaudia Engel collaborates with students and faculty on digital research projects in the Anthropology Department, where she also has a lecturer appointment and teaches courses in GIS, Digital Methods, and Critical Data Practices. She is a member of the Research Data Services (RDS) Division at the Stanford Libraries. In that role she teaches workshops and supports researchers in the use of digital data repositories.
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Robert Joel England
Lead Scientist, SLAC National Accelerator Laboratory
Current Role at StanfordHead of Accelerator Operations for MeV-UED/ASTA
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Koray Ertan
Research Engineer, Rad/Radiological Sciences Laboratory
BioKoray Ertan received his B.Sc. degree in Electrical and Electronics Engineering from Bilkent University, Turkey, where he also completed his Ph.D. under the supervision of Prof. Ergin Atalar. During his doctoral studies, he conducted research at the National Magnetic Resonance Research Center (UMRAM) in Turkey. His dissertation focused on the development of novel magnetic resonance imaging (MRI) technologies, including gradient array systems aimed at improving diagnostic image quality, reducing specific absorption rate (SAR), and shortening scan times.
In April 2019, he joined Prof. Brian Rutt’s group at Stanford University as a postdoctoral researcher. Shortly after, in June 2019, he was also appointed as a MINDED postdoctoral fellow. As part of the MINDED program, his research involved developing a system to modulate the permeability of the blood-brain barrier using focused radiofrequency heating from ultra-high field MRI transmit coils, with the goal of enhancing nanomedicine-based treatments for neurodevelopmental disorders.
He is currently a Research Scientist in the Radiological Sciences Laboratory at Stanford. His present work focuses on the design of next-generation head gradient coils and the analysis of peripheral nerve stimulation (PNS) thresholds. He is developing a predictive framework to estimate subject-specific PNS limits using basic demographic data and localizer MRI scans, with the aim of enabling safer and more efficient MRI.
