Eleonora Tamilia, PhD
Director, Epilepsy Monitoring Unit (EMU) Signal and Data Science Program, Epilepsy and Clinical Neurophysiology Division, Department of Neurology; Research Associate, Fetal-Neonatal Neuroimaging Developmental Science Center, Newborn Medicine Division
Assistant Professor of Pediatrics, Harvard Medical School
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Eleonora Tamilia, PhD
Director, Epilepsy Monitoring Unit (EMU) Signal and Data Science Program, Epilepsy and Clinical Neurophysiology Division, Department of Neurology; Research Associate, Fetal-Neonatal Neuroimaging Developmental Science Center, Newborn Medicine Division
Assistant Professor of Pediatrics, Harvard Medical School
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English
Italian
Professional History
Eleonora Tamilia received her PhD and MS in Biomedical Engineering (from University Campus Bio-Medico and University Tor Vergata of Rome, respectively) and conducted her post-doctoral training at BCH/HMS (from 2015 to 2019). She is an expert in biomedical signal processing and data analysis with particular focus on neurological disorders.
Her research work has been recognized through numerous awards from national and international committees, which include young investigator awards from the American Epilepsy Society, the International Federation of Clinical Neurophysiology and the IEEE Engineering in Medicine and Biology Society. She is also the Director of the Epilepsy Monitoring Unit (EMU) Signal and Data Science Program in Neurology.
Her current research is dedicated to the advanced analysis of electroencephalography (EEG) and magnetoencephalography (MEG) from children with epilepsy to identify new electrophysiological epilepsy biomarkers, test their clinical value for surgical treatment and translate such technological advances to the clinical practice. She also conducts research for the development of new non-invasive methods that facilitates the early diagnosis of brain injury in neonates through the combined monitoring of brain and motor activity.
Publications
Noninvasive classification of physiological and pathological high frequency oscillations in children. View Abstract
Machine learning on interictal intracranial EEG predicts surgical outcome in drug resistant epilepsy. View Abstract
Spikes on ripples are better interictal biomarkers of epilepsy than spikes or ripples. View Abstract
Overlap of spike and ripple propagation onset predicts surgical outcome in epilepsy. View Abstract
Magnetoencephalography for the pediatric population, indications, acquisition and interpretation for the clinician. View Abstract
Interictal EEG source connectivity to localize the epileptogenic zone in patients with drug-resistant epilepsy: A machine learning approach. View Abstract
Deep Learning-Based Visual Complexity Analysis of Electroencephalography Time-Frequency Images: Can It Localize the Epileptogenic Zone in the Brain? View Abstract
Deep Learning-Based Visual Complexity Analysis of Electroencephalography Time-Frequency Images: Can It Localize the Epileptogenic Zone in the Brain? View Abstract
Sleep Spindle Generation Before and After Epilepsy Surgery: A Source Imaging Study in Children with Drug-Resistant Epilepsy. View Abstract
Spike propagation mapping reveals effective connectivity and predicts surgical outcome in epilepsy. View Abstract
Electromagnetic source imaging predicts surgical outcome in children with focal cortical dysplasia. View Abstract
Functional connectivity discriminates epileptogenic states and predicts surgical outcome in children with drug resistant epilepsy. View Abstract
Non-invasive mapping of epileptogenic networks predicts surgical outcome. View Abstract
Phase-amplitude coupling between low- and high-frequency activities as preoperative biomarker of focal cortical dysplasia subtypes. View Abstract
A Role for Data Science in Precision Nutrition and Early Brain Development. View Abstract
Reply to "Added value of high-resolution electrical source imaging of ictal activity in children with structural focal epilepsy". View Abstract
Virtual implantation using conventional scalp EEG delineates seizure onset and predicts surgical outcome in children with epilepsy. View Abstract
Novel User-Friendly Application for MRI Segmentation of Brain Resection following Epilepsy Surgery. View Abstract
Mapping Propagation of Interictal Spikes, Ripples, and Fast Ripples in Intracranial EEG of Children with Refractory Epilepsy. View Abstract
Mapping Functional Connectivity of Epileptogenic Networks through Virtual Implantation. View Abstract
Electric Source Imaging on Intracranial EEG Localizes Spatiotemporal Propagation of Interictal Spikes in Children with Epilepsy. View Abstract
Association between semiologic, autonomic, and electrographic seizure characteristics in children with generalized tonic-clonic seizures. View Abstract
Changes in the Functional Brain Network of Children Undergoing Repeated Epilepsy Surgery: An EEG Source Connectivity Study. View Abstract
Source imaging of seizure onset predicts surgical outcome in pediatric epilepsy. View Abstract
Presurgical accuracy of dipole clustering in MRI-negative pediatric patients with epilepsy: Validation against intracranial EEG and resection. View Abstract
Noninvasive Mapping of Ripple Onset Predicts Outcome in Epilepsy Surgery. View Abstract
Abnormal Nutritive Sucking as an Indicator of Neonatal Brain Injury. View Abstract
Photoplethysmography: A measure for the function of the autonomic nervous system in focal impaired awareness seizures. View Abstract
Photoplethysmographic evaluation of generalized tonic-clonic seizures. View Abstract
Scalp ripples as prognostic biomarkers of epileptogenicity in pediatric surgery. View Abstract
Ictal and interictal source imaging on intracranial EEG predicts epilepsy surgery outcome in children with focal cortical dysplasia. View Abstract
Nutritive sucking abnormalities and brain microstructural abnormalities in infants with established brain injury: a pilot study. View Abstract
Noninvasive Localization of High-Frequency Oscillations in Children with Epilepsy: Validation against Intracranial Gold-Standard. View Abstract
Assessing the localization accuracy and clinical utility of electric and magnetic source imaging in children with epilepsy. View Abstract
Altered White Matter Connectivity Associated with Intergyral Brain Disorganization in Hemiplegic Cerebral Palsy. View Abstract
Surgical resection of ripple onset predicts outcome in pediatric epilepsy. View Abstract
Magnetoencephalographic Mapping of Epileptic Spike Population Using Distributed Source Analysis: Comparison With Intracranial Electroencephalographic Spikes. View Abstract
Magnetoencephalographic Spike Analysis in Patients With Focal Cortical Dysplasia: What Defines a "Dipole Cluster"? View Abstract
Quantifying Neonatal Sucking Performance: Promise of New Methods. View Abstract
Current and Emerging Potential of Magnetoencephalography in the Detection and Localization of High-Frequency Oscillations in Epilepsy. View Abstract
Interictal High Frequency Oscillations Detected with Simultaneous Magnetoencephalography and Electroencephalography as Biomarker of Pediatric Epilepsy. View Abstract
An Automated System for the Analysis of Newborns' Oral-Motor Behavior. View Abstract
An automated system for quantitative analysis of newborns' oral-motor behavior and coordination during bottle feeding. View Abstract
Development of goal-directed action selection guided by intrinsic motivations: an experiment with children. View Abstract
A new calibration methodology for thorax and upper limbs motion capture in children using magneto and inertial sensors. View Abstract
Technological solutions and main indices for the assessment of newborns' nutritive sucking: a review. View Abstract
An automatized system for the assessment of nutritive sucking behavior in infants: a preliminary analysis on term neonates. View Abstract
A transistors-based, bidirectional flowmeter for neonatal ventilation: design and experimental characterization. View Abstract
Design, development and experimental validation of a non-invasive device for recording respiratory events during bottle feeding. View Abstract
An MR-compatible force sensor based on FBG technology for biomedical application. View Abstract
An experimental protocol for the definition of upper limb anatomical frames on children using magneto-inertial sensors. View Abstract
A new ecological method for the estimation of Nutritive Sucking Efficiency in newborns: measurement principle and experimental assessment. View Abstract
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