Brain Health Imaging Institute Directory

Tracy Butler Laboratory

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

Dr. Tracy Butler is the medical director of the Brain Health Imaging Institute (BHII).  She is board-certified neurologist with clinical subspecialty training in cognitive neurology and epilepsy and research training in functional neuroimaging. After majoring in philosophy and neuroscience at Amherst College, Dr. Butler worked as a neuropsychology research assistant for three years at Boston University's Memory Disorders Research Center, for Dr. Laird Cermak, before attending medical school at Columbia University College of Physicians and Surgeons.  She completed her neurology residency at Columbia, then joined the Functional Neuroimaging Laboratory in the psychiatry department at Weill Cornell Medicine, headed by Drs. David Silbersweig and Emily Stern, as a National Institutes of Health (NIH)-supported postdoctoral fellow.  There she gained research training in multimodal neuroimaging (task-based and resting-state functional magnetic resonance imaging (fMRI), structural MRI, and positron emission tomography) as applied to understanding human cognition, including sex differences and neuropsychiatric disease (depression, post-traumatic stress disorder (PTSD) and schizophrenia).  She gained additional clinical subspecialty training in the overlap between neurology and psychiatry and became United Council for Neurologic Subspecialties (UCNS) board-certified in cognitive neurology and neuropsychiatry.

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Nimmi Wickramasuriya, M.D.
  • Postdoctoral Associate

Nimmi is a postdoctoral associate in the Tracy Butler lab investigating the role of hormones such as GnRH in neurodegeneration, and helping to conduct a clinical trial testing the GnRH analogue leuprolide as a treatment for Alzheimer’s disease (The LUCINDA trial). She is a graduate of Jagiellonian University School of Medicine with a background in neuroscience. In her free time, she likes to explore the great outdoors through hiking and camping. She also loves to bake Sri Lankan delicacies and share them with friends and family. 

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Sarah Khan
  • Research Coordinator

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

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

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. 

Carly Skudkin
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Carly Skudin
  • Research Coordinator Program Manager

Carly Skudin is a research coordinator working with Dr. Butler on two studies of traumatic brain injury (TBI): one which enrolls subjects with acute TBI from the emergency room (ER) and another which enrolls victims of interpersonal violence with and without chronic TBI. Carly also coordinators research projects from the Magnetic Resonance imaging Research Institute. She graduated from Colgate University. 

Gloria Chiang Laboratory

Gloria Chiang, M.D.
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Gloria Chiang, M.D.
  • Associate Professor

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

Mony de Leon, Ed.D
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Mony de Leon, Ed.D.
  • Professor of Neuroscience
  • Brain Health Imaging Institute 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. 

Lidia Glodzik Laboratory

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

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. 

chris woldstad
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Christopher Woldstad, Ph.D.
  • Postdoctoral Associate

Christopher Woldstad received his B.S. in neurobiology from the University of Texas in Austin in 2012 and his Ph.D. from the University of Nebraska Medical Center Department of Pharmacology and Experimental Neuroscience in 2019. His graduate work focused on developments in the relatively novel field of theranostics, using the latest in cutting-edge technology to combine therapeutic and diagnostic capabilities within a singular vehicle to better understand and improve human immunodeficiency virus (HIV) antiretroviral treatment paradigms.  Currently, Christopher works, among others, on projects exploring the relationship between low-grade inflammation and brain lesions.

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Christopher Mardy, MBS.
  • Assistant Research Coordinator

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.  

Adrienne Biskaduros, B.S.
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Adrienne Biskaduros, B.S.
  • Assistant Research Coordinator

Adrienne Biskaduros received her B.S. in molecular, cell, and developmental sciences from the University of California, Los Angeles, with Phi Beta Kappa distinction. She plans on applying to medical school in the future. During her undergraduate career, she worked with Milan Fiala, M.D., to study the role of the glymphatic system in various forms of dementia. Adrienne was a runner-up for the Dean's Prize in Life Sciences Research, and was a member of the review board for the Undergraduate Science Journal. She is interested in markers of inflammation in Alzheimer's disease and synaptic dysfunction. 

Amy Kuceyeski Laboratory | Computational Connectomics (CoCo) Laboratory

Amy Kuceyeski Photo
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Amy Kuceyeski, Ph.D.
  • Associate Professor of Mathematics

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

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

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.
  • Postdoctoral Associate

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
  • Collaborator

Zijin is a third-year 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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Emily Olafson
  • Ph.D. Candidate in Neuroscience

Emily is a third-year Ph.D. student in neuroscience at Weill Cornell Medicine. She completed her B.Sc. in neuroscience at McGill University, where she studied cortical phenotypes of autism spectrum disorder from structural brain images. In the CoCo Lab, she is studying how the brain’s functional and structural networks change after an ischemic stroke. She hopes her research will be used to better understand how brain activity changes occurring post-stroke impact patient outcomes, and to help identify potential targets for noninvasive therapies. 

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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).  

Parker Singleton Photo
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Parker Singleton
  • Ph.D. Candidate

Parker is a Ph.D. candidate and National Science Foundation Graduate Research Fellow in computational biology at Cornell University (CU). He transferred from CU’s Department of Chemistry & Chemical Biology, where he obtained his M.S. in 2017, before spending three years as a high school and community college science teacher. Originally from South Carolina, he received his B.S. in chemistry from the University of South Carolina in 2015. He is studying the effects potent serotonergic compounds have on brain activity landscapes using network control theory. He hopes his research can be used to inform theories of consciousness and to better understand, diagnose and treat mental disorders. 

Yi Li Laboratory

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

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.

Liangdong Zhou, Ph.D.
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Liangdong Zhou, Ph.D.
  • Postdoctoral Associate

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

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

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.

Artur Lazarian, PhD
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Artur Lazarian, Ph.D.
  • Postdoctoral Associate

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.

Silky Singh Pahlajani Laboratory

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

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 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.  

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

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.   

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Antonio Fernandez Guerrero, Ph.D.
  • Postdoctoral Associate

From 2005 to 2011, Antonio Fernandez Guerrero, Ph.D., studied theoretical physics at the Complutense University of Madrid, graduating at the top of his class. From 2011 to 2012, Dr. Guerrero continued his education at Complutense University, earning a  master’s degree in biomedical physics and, once more, graduated at the top of his class. During this period, he collaborated with Madrid’s Cajal Blue Brain Project, using magnetoencephalography (MEG) to study the effective connectivity patterns of mild cognitive impairment. Because of his excellent grades,  Complutense University offered Dr. Guerrero the opportunity to pursue a doctorate in computational biology; however, he rejected the offer, opting instead to pursue neuroscience, his greatest scientific passion.  

In 2013, Dr. Guerrero began his doctoral studies at the University of Zurich. Before transitioning to neuroscience, he studied sleep onset transition in humans using electroencephalogram (EEG) under Professor Peter Achermann. Using EEG power spectral density changes, Dr. Guerrero investigated how functional and effective patterns could be correlated or tracked during the sleep onset transition—both in normal conditions and under sleep deprivation. He also co-wrote a paper on cosmology and completed the  two-year  sleep neuroscience program. 

In 2021, under the supervision of Dr. Ray  Razlighi, Dr. Guerrro became a Weill Cornell Medicine postdoctoral student, conducting quantitative analyses on functional magnetic resonance imaging (fMRI). Currently, he’s focused on how negative blood-oxygenation-level dependent (BOLD) (NBR) response, or functional connectivity, impacts the brain’s executive functions, or cognitive reserve. He also studies how this, in turn, compares amongst different populations, particularly old and young populations. Dr. Fernandez Guerrero has worked with EEG, MEG, and fMRI, giving him a broad experience with the most common neuroscience techniques.  

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Hani Hojjati, Ph.D.
  • Postdoctoral Associate

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

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

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

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. 

Nayoung Kim
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Nayoung Kim, Ph.D.
  • Postdoctoral Associate

Nayoung Kim is a postdoctoral associate of radiology at Weill Cornell Medicine. She received a Ph.D. from Edward P. Fitts Industrial and Systems Engineering at North Carolina State University in 2019. She received a master’s degree in management engineering from the Korea Advanced Institute of Science and Technology (KAIST) in 2014, and a bachelor’s degree from Industrial and Systems Engineering at KAIST in 2011. She conducts basic and applied research in neuroscience and brain-computer interaction (BCI) with electroencephalography (EEG). She is currently working in Dr. Shah’s laboratory studying neural mechanisms underlying disorder of consciousness (DoC), as well as mechanisms of recovery. Her current research is focused on EEG-centered methodology to track and predict long-term neurological recovery. Her research has been supported by federal agencies including the National Institutes of Health, the National Science Foundation (NSF) and the Air Force Research Laboratory (AFRL).