Wen Shi, PhD Postdoctoral Researcher
Wen received her Ph.D. degree in Electrical Engineering from Nanyang Technological University, Singapore in 2015 and Bachelor of Engineering degree in Computer Science from Jinan University, P. R. China in 2011. Wen has worked on various types of analysis of biomedical signals including ECG, EEG, PSG, MRI, and acoustic signals. She is interested in building automated analytic models by developing predictive, actionable algorithms for better performance and efficiency. In the Chu Lab, Wen is developing tools to detect and analyze spike ripples as an improved biomarker for the epileptogenic cortex compared to either spikes or ripples alone.
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Hunki Kwon, PhD Postdoctoral Researcher
Hunki received his Ph.D. degree in Biomedical Engineering in 2017 and Bachelor of Engineering degree in Biomedical Engineering in 2010 from Hanyang University, Korea. His recent research has focused on what happens in the early stages of visual perception using intracranial EEG. He is also interested in multimodal imaging analysis using fMRI, EEG, DTI, MRI, etc. In the Chu Lab, Hunki is leading multiple projects evaluating developmental epilepsy using MEG/EEG electrical source imaging, resting-state fMRI functional connectivity, and probabilistic tractography algorithms with statistical approaches.
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Anirudh Wodeyar, PhD Postdoctoral Researcher
Anirudh earned his Ph.D. in Cognitive Science, as well as an M.S. in Statistics, from the University of California, Irvine, and a B.E. in Computer Science from BITS Pilani. Anirudh’s academic focus has been on understanding the neural mechanisms behind cognitive processes, with a particular interest in the dynamics and constraints of neural population activity. His research has focused on the investigation of brain rhythms, cross-frequency coupling, real-time analysis, and functional networks. In the Chu lab, Anirudh focuses on analyzing the influence of sleep brain rhythms on memory and the dysfunction of sleep brain rhythms in epilepsy.
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Dhinakaran Chinappen, MEng, MBA Graduate Student Research Assistant
Dhinakaran is currently working towards his Ph.D. in Computational Neuroscience at Boston University. He graduated from the University of Pennsylvania in 2009 with a B.S. in Bioengineering and a B.A. in Economics with a minor in Mathematics, obtained his Master of Engineering in Biomedical Engineering from Cornell University in 2013 and obtained his Master of Business Administration at the University of Illinois at Urbana-Champaign in 2019. In the Chu lab, he analyzes multimodal brain imaging data for seizure localization, develops software and tools for data collection and analysis, collects multimodal imaging data in patients with epilepsy, and analyzes thalamic recordings in patients with epilepsy. He hopes to be able to contribute to the body of literature on neurological diseases with practical applications for patients.
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Erin Berja, BS Clinical Research Coordinator
Erin graduated from Tufts University in 2020 with a B.S. in Cognitive and Brain Science and a minor in Asian American Studies. She previously worked in cognitive neuroscience labs analyzing research areas such as social cognition, emotion regulation, and sleep-based memory consolidation, and she is interested in advancing translational neuroscience research towards clinical applications and health equity. In the Chu Lab, Erin coordinates the multi-center neonatal seizure registry, collects neuroimaging and experimental data in human subjects, and investigates biomarkers, thalamocortical circuit dysfunction, and cognitive comorbidities in Rolandic epilepsy.
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Katherine Walsh, BS Clinical Research Coordinator
Katie graduated from Tufts University in 2021 with a B.S. in Biology and a B.A. in Spanish. She has previously worked in tissue engineering and developmental neuroscience labs and is interested in translational neuroscience research to improve health outcomes, with a focus on neurodevelopmental disorders. In the Chu Lab, Katie has collated a large normative database of EEGs in infants and children for biomarker development, performs multimodal data collection and cognitive tasks in children, and coordinates and supports the spike ripple projects.
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Skyler Goodman, BS Clinical Research Coordinator
Skyler will be graduating from Simmons University in 2023 with a B.S. in Neuroscience and Cognitive Behavior. She has previously worked in clinical research studying Transcranial Magnetic Stimulation and Alzheimer’s disease, and she is interested in the role of neuroimaging in translational cognitive neuroscience. In the Chu lab, she investigates the neural mechanisms underlying seizures and cognition in developmental epilepsy and collects human neuroimaging data.
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Elizabeth Kinard, BA Clinical Research Coordinator
Elizabeth graduated from Harvard College in 2022 with a B.A. in Behavioral Neuroscience. She has previously worked as a Technical Research Assistant at McLean Hospital studying the effects of kappa opioid receptor antagonism on the escalation of oxycodone intake and relapse after withdrawal. In the Chu lab, she is interested in investigating the etiology and cognition-related consequences of Rolandic epilepsy, as well as the clinical implications of these findings to inform future treatment development.
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Jonathan Huang, BS
Clinical Research Coordinator
Jonathan graduated from the University of Richmond in 2021 with a B.S. in Biology. In college, he worked in a neurodevelopmental lab studying spinal cord degeneration using zebrafish. He is currently interested in applying computational methods to translational neuroscience. In the Chu Lab he performs multimodal data collection and cognitive tasks for the Rolandic epilepsy project and analyzes MEG imaging and behavioral data to understand the relationship between thalamocortical circuit abnormalities and attention difficulties in epilepsy.
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Grace Xiao, BS Medical School Student Research Assistant
Grace Xiao is a medical school student at Johns Hopkins. Previously, she did her undergraduate work at Harvard studying neurobiology and economics. She is interested in creating impact through research, policy and entrepreneurship. In the Chu lab, Grace assisted with collecting and analyzing neuroimaging data for the Rolandic epilepsy project and completed an Honors thesis evaluating spike morphological differences and seizure risk in epilepsy.
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Anvitha Sathya Medical School Student Research Assistant
Anvitha is currently a fourth-year student in Boston University’s Seven Year BA/MD program with a minor in English and an interest in neurological patient care. She has previously worked in labs studying neuromuscular diseases and neurological injuries. Anvitha helps with multimodal imaging and experimental data collection in children for the Rolandic epilepsy project and performs electrode localizations for projects using invasive EEG data.
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John McLaren, MD Pediatric Epilepsy Fellow
John is currently an Epilepsy Neurology fellow at Massachusetts General Hospital. He completed his undergraduate degree at Boston College, majoring in Music and Neuroscience, his Medical Doctorate at the University of Vermont College of Medicine, and his Child Neurology residency at MGH. After completing his Neurology training, he will be staying on at MGH as an Epilepsy fellow. His research interest is in diagnostics and therapeutics for children with epileptic encephalopathies.
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Yancheng Luo, MD Junior Faculty
YC (Yancheng) Luo is a graduate of the Child Neurology fellowship at Massachusetts General Hospital and current junior faculty at Boys Town National Research Hospital in Omaha, Nebraska. During his childhood neurology residency at MGH, he started working with Dr. Chu on electrophysiology data analysis and he hopes to continue this research interest in his career.
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Ana Howland Undergraduate Summer Research Assistant
Ana is currently an undergraduate student at Rice University studying Piano Performance and Neuroscience, with interests in translational research and neurological patient care. In the Chu Lab, Ana is involved in the collection of neuroimaging and experimental data and the development of an algorithm to automatically stage intracranial recordings. She assists in projects that analyze multimodal imaging data of epilepsy patients and the relationship between hippocampal rhythms and sleep-dependent memory function.
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