BHII Directory

Tracy Butler Laboratory

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Tracy Butler, M.D.
  • Associate Professor of Neurology in Radiology

Dr. Tracy Butler is a neurologist/neuroscientist with clinical subspecialty training in behavioral neurology and epilepsy and research fellowship training in functional and structural neuroimaging.  She is the medical director of the Brain Health Imaging Institute (BHII) where she oversees subject assessment and clinical trials of therapies and neuroimage biomarkers of aging and neurodegeneration.  Her research uses multimodal positron emission tomorgraphy (PET) and magnetic resonance imaging (MRI) neuroimaging and complementary methods to better understand the biological basis of neuropsychiatric disorders including Alzheimer’s disease, traumatic brain injury, and as normal aging, focusing on pathophysiologic overlap among these conditions such as hormonal dysregulation, neuroinflammation and brain toxic protein (tau and amyloid) accumulation.

Farnia Feiz Photo
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Farnia Feiz, M.D., M.P.H.
  • Research Associate in Radiology

In 2020, Dr. Farnia Feiz joined the Quantitative Neuroimaging Laboratory (QNL) as clinical research manager. She helps with patient recruitment,  medical data review, and  regulatory  operations  of the QNL’s National Institutes of Health-funded  study. Prior to arriving at Weill Cornell Medicine, Dr. Feiz worked on numerous studies in neuroradiology and neurodegenerative diseases.  She holds an M.D. from Shiraz University of Medical Sciences and an M.P.H. from New York University.  

Elena Golub
  • Assistant Research Coordinator in Radiology
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Ilker Ozsahin, Ph.D.
  • Postdoctoral Associate in Radiology

Ilker Ozsahin is a postdoctoral associate in the Tracy Butler lab working on positron emission tomography (PET), computed tomography (CT), and magnetic resonance imaging (MRI) analyses for several diseases including Alzheimer’s disease. He has worked in several different physics areas such as high energy physics, solid-state physics, and medical imaging. At the University of Illinois at Urbana-Champaign, he worked on growth of carbon nanotubes. He received his Ph.D. in medical imaging in Turkey. He has extensive experience with medical imaging devices such as PET, Positron Emission Mammography (PEM), Single Photon Emission Computed Tomography (SPECT), and Compton Camera (CC), including modelling, simulation, characterization, and image reconstruction. He worked at Universidad Autonoma de Barcelona in Spain as a Ph.D. student. In addition to his Ph.D. studies, he worked as a research assistant for six years in the physics department at Cukurova University in Adana, Turkey. After earning his Ph.D., he spent two years at Harvard Medical School and Massachusetts General Hospital as a postdoctoral fellow. He worked on the simulation of a high-performance PET scanner for small animal and breast imaging, and investigated the mechanism of general anesthesia. He served as a visiting postdoctoral fellow at the University of Macau looking into multi-pinhole SPECT collimator design and implementation for brain imaging, as well as cardiac and small animal imaging via adaptive collimators. He is investigating neural network applications for neurological diseases and operational research in healthcare.

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Sarah Khan
  • Research Coordinator in Radiology

Sarah is a research coordinator in the Tracy Butler lab for The LUCINDA trial. She is a graduate of Hunter College. She previously worked at Mount Sinai on a project investigating the basis of Chronic Fatigue Syndrome. She is pursuing a master’s degree in nutrition. 

Tom Maloney
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Tom Maloney, Ph.D.
  • Senior Research Associate in Radiology

Tom Maloney is a highly experienced project and data manager for complex clinical research studies of brain function.  He has deep expertise in developing database structures and tools and facilities for smooth, flexible capture, organization and retrieval of very large, very dense, highly diverse study data from multiple research and clinical domains. His background ranges from event-related electroencephalogram (EEG) potentials, sleep regulation, cognitive performance, chronobiology and neuropsychological testing to functional neuroimaging.  He has planned and managed research and clinical operations and data migrations at Stony Brook University, the Veterans Administration, University of California, Brown University, Brookhaven National Laboratory, Mount Sinai School of Medicine, and, since 2019, Weill Cornell Medicine.  He is project manager for the LUCINDA Trial and Data Manager for the Brain Health Imaging Institute. 

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Hugh Wang, M.S.
  • Staff Associate in Radiology

Xiuyuan (Hugh) Wang has been working with Dr. Butler since 2011, first at New York University and now at Weill Cornell.  He received his bachelor's degree in biomedical engineering from Shanghai University, and a master's degree from City College of New York. He is an image analyst in the lab working on biomedical signal and image processing. 

Gloria Chiang Laboratory

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Gloria Chiang, M.D.
  • Associate Professor of Clinical Radiology

Gloria Chiang, M.D., is an associate professor with the Weill Cornell Medicine Department of Radiology Brain Health Imaging Institute (BHII), and with NewYork-Presbyterian Hospital (NYP). She is a board-certified radiologist with subspecialty certification in neuroradiology. Her research program focuses on combining quantitative magnetic resonance and positron emission tomography (MR) and (PET) imaging techniques with plasma and cerebrospinal fluid (CSF) biomarkers to elucidate the pathophysiology of neurodegenerative diseases.  

Mony de Leon Laboratory

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Mony de Leon, Ed.D.
  • Professor of Neuroscience in Radiology
  • BHII Director

Mony J. de Leon, Ed.D., is director of the Brain Health Imaging Institute (BHII) in the Weill Cornell Medicine (WCM) Department of Radiology at Weill Cornell Medicine, and director of the BHII’s de Leon Neuroimaging Lab. Trained in gerontology and neuroscience, his research focuses on the clinical detection of brain changes underlying cognitive dysfunction, and the characterization of mechanisms contributing to misfolded brain proteins and tissue damage in aging and Alzheimer’s disease (AD). For 40 years he has conducted National Institutes of Health-funded longitudinal brain aging studies. His team’s post-mortem validated biomarker discoveries of hippocampal atrophy and brain glucose metabolism deficits predicting clinical outcomes have contributed to the current standard diagnostic assessment of AD. 

Samantha Keil , Ph.D.
  • Postdoctoral Associate in Radiology

Lidia Glodzik Laboratory

Lidia Glodzik M.D., Ph.D.
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Lidia Glodzik, M.D., Ph.D.
  • Assistant Professor in Radiology

Dr. Lidia Glodzik is the head of the VAscular RIsk in Alzheimer’s disease (VARIA) lab. She completed her residency training in neurology at the University Hospital in Krakow, Poland, where she worked in a stroke unit. She holds a Ph.D. in medical sciences from the Jagiellonian University in Krakow. Her Ph.D. thesis dealt with metabolic changes in post-stroke mood disorders measured with magnetic resonance spectroscopy. She subsequently trained and worked in the New York University Center for Brain Health with Dr. Mony de Leon, a pioneer in Alzheimer’s disease (ADimaging, on projects related to the prediction of dementia in healthy individuals. Dr. Glodzik employs magnetic resonance imaging (MRI) and positron emission tomography (PET) imaging techniques as well as biofluids to investigate early indicators of cognitive decline. 

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Christopher Mardy, M.B.S.
  • Assistant Research Coordinator in Radiology

Christopher Mardy received his B.S in biology from the State University of New York, Albany, and later went on to receive his MBS. in biomedical science from Rutgers University, New Brunswick. Christopher is currently pursuing a degree in nursing, with the hope of furthering his research experience with the aging population.  

Amy Kuceyeski Laboratory | Computational Connectomics (CoCo) Laboratory

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Amy Kuceyeski, Ph.D.
  • Professor of Mathematics in Radiology

For more than a decade, Amy Kuceyeski has been interested in understanding how the human brain works to better diagnose, prognose and treat neurological disease and injury. Quantitative approaches, including machine learning, applied to data from rapidly evolving neuroimaging techniques, have the potential to enable groundbreaking discoveries about how the brain works. Amy is particularly interested in non-invasive brain stimulation and pharmacological interventions, like psychedelics, that may modulate brain activity and promote recovery from disease or injury. Amy is also the founder and co-director of the cross-campus working group Machine Learning in Medicine, which aims to bring together researchers in Cornell-Ithaca/Cornell-Tech and clinicians/researchers at Weill Cornell Medicine to address medicine's toughest problems. See the group's website. 

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Keith Jamison, M.S.
  • Staff Associate in Radiology

Keith Jamison is a staff associate in the CoCo Lab. He has a B.S. in computer science and an M.S. in Biomedical Engineering from Cornell University. Through his education and training, he has developed the broad range of skills and expertise necessary to discern scientifically and clinically relevant patterns from large neuroimaging datasets. While working for the Human Connectome Project (HCP) at the University of Minnesota, he helped implement and adapt preprocessing and analysis pipelines for a large number of anatomical, functional and diffusion magnetic resonance imaging (MRI) scans. He also helped design and test new scanning protocols and modalities for some of the HCP-related studies whose data they now propose to analyze. Since joining the CoCo lab in 2017, he has built upon this expertise in neuroimaging acquisition and processing to help develop modeling approaches using this neuroimaging data to better understand the functional and structural connectivity relationship, and how connectivity relates to both healthy brain function and neurological damage or disease. 

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Sneha Pandya, M.S.
  • Research Associate in Radiology

Sneha Pandya is a research associate in biomedical engineering. Over the past eight years, Sneha has worked closely with RajLab, Weill Cornell Medicine (WCM) Multiple Sclerosis Center, and Sumit Niogi’s WCM Lab, serving both radiology and neurology departments, while applying problem-solving techniques to current clinical problems in the imaging, diagnosis and treatment of major brain diseases. The CoCo Lab’s initiative to use quantitative methods and machine learning on multi-modal neuroimaging data to map brain-behavior relationships has inspired her to be part of this lab. The predominant drive of Sneha’s academic career has been to apply these techniques to current issues in neuroimaging. Sneha plans to expand her research pursuits by developing quantitative and machine learning models in understanding structural-functional relationships and predicting early onset of varying brain diseases. 

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Ceren Tozlu, Ph.D.
  • Instructor of Mathematics in Radiology

Ceren Tozlu is a post-doctoral associate in the Weill Cornell Medicine (WCM) Department of Radiology, and in the Cornell University Department of Statistics and Data Science and Computational Biology. She received her M.S. and Ph.D. from the Biostatistics, Biomathematics, Bioinformatics and Health department (3B-H) of Université Claude Bernard Lyon 1 in 2014 and 2018, respectively. She gave lectures to the M.S. students of Cancer, Neuroscience, Biostatistics and Public Health at Université Claude Bernard Lyon for one year and to the medical students at École Santé des Armées (Army Health School of France) for four years. Her M.S. research project focused on application of various machine learning methods to voxel-based conventional human imaging data to predict infarction risk of 3D brain tissue in acute stroke patients. Her Ph.D. thesis focused on modeling disease evolution of stroke and multiple sclerosis (MS) patients based on cross-sectional and longitudinal clinical and imaging data plotted over five years. Her post-doctoral research focuses on (1) modeling of evolution in neurological diseases, particularly in patients with stroke and MS, using statistical and machine learning methods based on demographic, clinical, regional and pair-wise functional and structural connectivity measurements, and (2) identification of the best biomarkers of disease evolution including the particular structural and functional connections contributing to differences in patients with different neurological diseases. Her post-doctoral study aims to develop a novel and personalized model to be used by clinicians to predict individual disease evolution via an application or software, to lead to personalized treatment. She was recently awarded a postdoctoral fellowship grant from the National Multiple Sclerosis Society. 

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Zijin Gu
  • Ph.D. Student in Electrical and Computer Engineering

Zijin is a Ph.D. student in the Cornell University Department of Electrical and Computer Engineering. She received her bachelor’s degree in electrical engineering from Zhejiang University, China. Her research focuses on the intersection of machine learning and neuroscience. She is particularly interested in applying innovative machine learning algorithms to brain connectivity network analysis. Her project involves developing a noninvasive, spatially unconstrained and personalized method for neuromodulation, which involves creating deep neural networks for stimuli and brain activation patterns mapping. She hopes that manipulating brain connectivity networks will help alleviate symptoms or boost recovery after neurologic injury. 

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Lisa Iatckova
  • Ph.D. Candidate in Physiology, Biophysics, & Systems Biology

Lisa is a third-year student in the Weill Cornell Medicine Physiology, Biophysics and Systems Biology Graduate Program, and a recipient of a National Science Foundation Graduate Research Fellowship in bioengineering. After three years of studying economics in construction in her hometown in Russia, she immigrated to the U.S., and graduated with a B.A. in neurobiology from Hunter College in 2019. At Hunter, Lisa also conducted research in the Goldfarb lab, where she tricked brain cancer cells into expressing mutant sodium channels, and then poked them with electrodes to learn how the mutations affected voltage-dependent fast inactivation, a key property of the channel altered in disease phenotypes. Lisa’s strongest aspiration is to contribute to the development of brain-computer interfaces that improve quality of life for people with impaired physical and cognitive function (and maybe even augment natural brain capabilities of healthy people).  

Yi Li Laboratory

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Yi Li, M.D., Ph.D.
  • Associate Professor in Radiology

Dr. Yi Li, co-director of imaging research for the Brain Health Imaging Institute (BHII), is an associate professor of radiology in the Weill Cornell Medicine (WCM) Department of Radiology. Dr. Li, who trained as a radiologist at Shandong Medical University, earned his doctorate in nuclear medicine from the Shandong University Graduate School. In 2007, Dr. Li became co-director of the New York University (NYU) Center for Brain Health Neuroimaging Laboratory, specializing in structural and positron emission tomography (PET)-related imaging research in aging and dementia. In 2019, Dr. Li’s research team joined WCM to help found the BHII.

Tsung-Wei Hu, Ph.D.
  • Postdoctoral Associate in Radiology
Liangdong Zhou, Ph.D.
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Liangdong Zhou, Ph.D.
  • Instructor of Biomedical Engineering in Radiology

Dr. Liangdong Zhou earned his doctorate in computational science and engineering from Yonsei University. During his Ph.D. program, Dr. Zhou was trained in mathematical and computational modeling of inverse problems in medical imaging, including electrical impedance tomography (EIT), magnetic resonance elastography (MRE), and quantitative susceptibility mapping (QSM). He then joined Dr. Yi Wang's magnetic resonance imaging (MRI) lab—Wanglab—for postdoctoral training in biophysical modeling and magnetic resonance (MR) data acquisition. At Wanglab, Dr. Zhou developed Quantitative Transport Mapping (QTM), a novel perfusion quantification method. By using both MRI and positron emission tomography (PET) imaging, Dr. Liangdong, under the supervision of Dr. Yi Li, is now working on the quantitative analysis of cerebrospinal fluid clearance in neurodegenerative disease.

Laura Beth McIntire Laboratory

Laura Beth McIntire
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Laura Beth McIntire, Ph.D.
  • Assistant Professor of Pharmacology in Radiology

Dr. Laura Beth McIntire, Ph.D., is director of the Lipidomics and Biomarker Lab at the Brain Health Imaging Institute (BHII), and an assistant professor of pharmacology, in the department of radiology. Her work focuses on the contribution of lipid dyshomeostasis to Alzheimer’s disease (AD) with a focus on phosphoinositide metabolism and acyl chain remodeling. Dr. McIntire is an expert in cell biology, cellular imaging and animal models of AD with expertise in animal behavior and the generation of novel mouse strains. She has expertise in lipidomics, imaging mass spectrometry, and system-wide analyses of the lipid interactome which have led to novel insights into lipid deficits in AD progression.

Ana Paula Costa
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Ana Paula Costa, Ph.D.
  • Postdoctoral Associate in Radiology

Dr. Ana Paula Costa, Ph.D. is working with induced pluripotent stem cells and mouse models of Alzheimer’s disease. She has completed training in neuronal differentiation of induced pluripotent stem cells (iPSC) and has expertise in assays for neuronal function. She also has expertise in animal behavior and surgical techniques. She has recently completed a certified training for the analysis of biomarkers using Quanterix Simoa technology.

William Dartora, Ph.D.
  • Postdoctoral Associate in Radiology
Artur Lazarian, PhD
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Artur Lazarian, Ph.D.
  • Postdoctoral Associate in Radiology

Dr. Artur Lazarian, Ph.D., has extensive experience with mass spectrometry, molecular biology and biochemistry. His recent work has focused on desorption electrospray ionization (DESI) imaging mass spectrometry using the Waters Synapt G2-Si. Additionally, during his previous post-doc position at the Max-Planck Institute for Polymer Research, he extensively used the Waters Synapt G2-Si. In the past two years, he has expanded his expertise to include molecular modeling using Schrodinger software.

Krista Wartchow, Ph.D.
  • Postdoctoral Associate in Radiology

Silky Singh Pahlajani Laboratory

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Silky Singh Pahlajani, M.D.
  • Assistant Professor of Neuropsychiatry Research in Radiology

Dr. Silky Pahlajani is an assistant professor of behavioral neurology in the department of radiology, and an attending physician at NewYork-Presbyterian Hospital. Her primary focus is neurodegenerative disorders, specifically Alzheimer’s disease (AD), and autoimmune antibody-mediated encephalitis, including N-methyl-D-aspartate (NMDA) receptor, leucine-rich glioma-inactivated/contactin-associated protein-2 (LGI-I/CASPR2) antibody, and glutamic acid decarboxylase 65 (GAD-65) antibody, etc.  In 2015, Dr. Pahlajani completed her residency training at New York Medical College, where she also served as chief resident. She subsequently completed two fellowships: behavioral neurology/neuropsychiatry at the University of Illinois-Chicago, and central nervous system (CNS) autoimmune disorders at Lenox Hill Hospital, prior to joining the Weill Cornell Memory Disorders Program in September 2017.

Ray Razlighi Laboratory | Quantitative Neuroimaging Laboratory

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Ray Razlighi, Ph.D.
  • Associate Professor of Neuroscience in Radiology

In 2009, Dr. Qolamreza "Ray" Razlighi earned his doctorate in electrical engineering and image processing from the University of Texas. During this time, Dr. Razlighi introduced a new causal Markov random field (MRF) model—Quadrilateral MRF (QMRF)—which has dramatically influenced medical and commercial image analysis, resulting in 12 publications and one patent to date. Dr. Razlighi’s advanced knowledge of neuroimaging and neuroscience started with one year of postdoctoral training at the Brain Imaging Laboratory of the Molecular Imaging and Neuropathology Division, New York State Psychiatric Institute, Columbia University. His education continued with two years of postdoctoral training in the Cognitive Neuroscience Division, Department of Neurology, Columbia University. 

Dr. Razlighi has been involved in many neuroimaging projects focused on implementing mathematical models and methods for magnetic resonance imaging (MRI) and functional magnetic resonance imaging (fMRI) data analysis. These include the development of a method for extracting brain features related to the cortical folding pattern; the development of a new non-stationary maximum a posteriori (MAP) QMRF (MAP-QMRF) classifier for brain image segmentation; analysis of fMRI data in a subject’s native space (thereby circumventing the problematic spatial-smoothing step, particularly in studies comparing young/old); and the investigation of inter-hemispheric averaging in resting-state fMRI data analysis. During his postdoctoral training, Dr. Razlighi participated in numerous neuroscience and neuroimaging courses.  

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Hani Hojjati, Ph.D.
  • Instructor of Electrical Engineering in Radiology

Hani Hojjati, Ph.D., is a postdoctoral associate in the Weill Cornell Medicine Department of Radiology. In 2011, Dr. Hojjati earned his  bachelor’s degree in electrical engineering from the Mazandaran University of Iran; from 2011 to 2013, he earned his  master's degree in electrical engineering from the BabolNoshirvani University of Technology (NIT); and from 2014 to 2018, he continued his education at NIT, earning a doctorate in electrical engineering.  

At NIT, Dr. Hojjati’s thesis focused on predicting Alzheimer's disease (AD) using multimodal neuroimaging methods and machine learning approaches. By employing neuroimaging and multimodal forecasting techniques, he determined accurate predictors for identifying mild cognitive impairment (MCI) versus AD. Using resting-state functional and structural magnetic resonance imaging (MRI) as tools, he enhanced the accuracy of predicting AD.  

In 2019, Dr. Hojjati started one year of postdoctoral neuroimaging training at the University of Tennessee Health Science Center Department of Pediatrics. In 2020, he entered a second postdoctoral training program at the Weill Cornell Medicine Department of Radiology. His current research involves using multimodal neuroimaging methods, including structural MRI, and amyloid/tau positron emission tomography (PET), to understand the association between neurodegeneration and amyloid/tau pathologies in the brains of both healthy control and MCI subjects. An award-winning researcher, Dr. Hojjati has published more than 12 journal articles and book chapters and presented at 19 conferences.  

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Sindy Ozoria, B.A.
  • Assistant Research Coordinator in Radiology

A graduate of Daemen College, Sindy Ozoria modeled her individualized studies degree after the history and philosophy of science program at the University of California, Los Angeles.  Ozoria, an assistant research coordinator, is interested in applying translational science to  vulnerable populations using computational,  cognitive,  and theoretical neuroscience tools.  

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Siddharth Nayak, Ph.D.
  • Postdoctoral Associate in Radiology

From 2010 to 2014, while pursuing his bachelor’s degree in biomedical engineering at the National Institute of Technology in Orissa, India, Dr. Nayak became interested in biomedical signal processing research. From 2014 to 2020, he pursued this path, earning a doctorate in interdisciplinary neuroscience from the National Cheng Kung University of Tainan, Taiwan. In June 2021, he became a postdoctoral researcher in the Weill Cornell Medicine Department of Radiology 

While earning his Ph.D., Dr. Nayak, who won numerous travel awards to international conferences, used electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) to studthe role of emotional processes on response inhibition. In addition to EEG and fMRI, he is interested in numerous biomedical signals, including electrocardiogram (ECG) and electromyography (EMG). Dr. Nayak, who has worked on linking heart-rate variability (HRV) with EEG, aims to better understand the human brain’s cognitive processes by integrating multimodal imaging technologies.  

As a postdoctoral researcher, Dr. Nayak studies the relationship between glucose metabolism as measured by fluorodeoxyglucose (FDG) positron emission tomography (PET) (FDG-PET) and the activation and deactivation of the blood-oxygenation-level dependent (BOLDsignal. When he is not researchingDr. Nayak enjoys taste-testing coffee variants and gorging on food from around the world.  

Sudhin Shah Laboratory

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Sudhin Shah, Ph.D.
  • Assistant Professor of Neuroscience in Radiology

Sudhin Shah, Ph.D., is an assistant professor of neuroscience in the department of radiology within the Brain Health and Imaging Institute at Weill Cornell Medicine (WCM). She received her B.Sc. in electrical engineering from Drexel University followed by a M.Sc. in biomedical engineering from Columbia University. She received her Ph.D. in systems neuroscience from the Weill Cornell Graduate School of Medical Sciences at Cornell University. She completed her postdoctoral training at WCM as well. Dr. Shah is also the Scientific Director of cognitive recovery research at Blythedale Children’s Hospital. She is an affiliate faculty member with the Consortium for the Advanced Study of Brain Injury at WCM. She has served on several National Institutes of Health scientific review panels, and as an invited reviewer for several journals. She has also served as a research mentor for more than 10 medical and graduate students. 

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Samuel Louviot, Ph.D.
  • Postdoctoral Associate in Radiology

Samuel Louviot is a postdoctoral associate of radiology at Weill Cornell Medicine. He received a Ph.D. in neuroscience from the University of Lorraine in France. During his Ph.D., he performed human in vivo intracerebral studies of the biophysics of transcranial electrical stimulation (tES), and the effect of tES on electrophysiology in epilepsy and face recognition. He received a master’s degree and a bachelor’s degree in biomedical engineering from the University of Lorraine, and an associate degree in electrical engineering from Lycée Pierre Mendes France. He works at Dr. Shah’s laboratory studying neuromodulation of mechanisms underlying attention and disorders of consciousness (DoC).

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Ludvik Alkhoury, Ph.D.
  • Postdoctoral Associate in Radiology

Ludvik Alkhoury is a postdoctoral associate of radiology at Weill Cornell Medicine. He received a B.S. in electrical engineering from the University of Balamand (UOB), Lebanon. He then joined the Data Fusion Lab (directed by Professor Moshe Kam) at the New Jersey Institute of Technology (NJIT) in 2018. In 2023, he received a Ph.D. in electrical engineering from the Helen and John C. Hartmann Department of Electrical and Computer Engineering at NJIT. His doctoral research focused on wearable health monitoring sensors and methods to extract non-invasive high quality vital signs (such as heart rate and oxygen saturation) during extensive human motion. He is currently working in Dr. Sudhin Shah’s laboratory to study the brain's response to language in children with brain injuries.

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Abigail Patchell, B.S.
  • Clinical Research Coordinator in Radiology

Abby is a clinical research coordinator at Weill Cornell Medicine. She received a B.S. in cognitive and behavioral neuroscience from Villanova University. During her undergraduate experience, she conducted research concerning language variation and cognitive processing strategies, striving to expand the literature on underrepresented groups. Abby is currently working in Dr. Sudhin Shah’s laboratory as a research coordinator. She assists with electroencephalography (EEG) focused studies investigating both pediatric disorders of consciousness and impairments in attention following traumatic brain injury in adults.

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Giacomo Scanavini, Ph.D.
  • Postdoctoral Associate in Radiology

Giacomo Scanavini is a postdoctoral associate in radiology at Weill Cornell Medicine. He holds a Ph.D. in physics from Yale University with a focus on high-energy physics. During his academic journey, he conducted research on neutrino properties, utilizing Liquid Argon Time Projection Chambers (LArTPCs) at Fermi National Laboratory (Fermilab). Currently, Giacomo works in Dr. Shah's laboratory, where he is investigating disorders of consciousness among individuals ranging from young children to adolescents with the goal of developing brain-computer interfaces (BCIs) to enhance essential daily tasks, such as communication.