BHII Directory

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 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. 

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 (AD) imaging, 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. 

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.  

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. 

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. 

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. 

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. 

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. 

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).  

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.

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.

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.

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.

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.

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.  

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. 

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).

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.

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.

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.