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Lab Members

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Keith Jamison, MS

Research Associate

Department of Radiology

Weill Cornell Medicine, New York, NY

PhD student

Computational Biology, Cornell University, Ithaca, NY

Keith Jamison is a staff associate in the CoCo Lab. He has a Bachelors of Science in computer science and a masters 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 at the University of Minnesota, he helped implement and adapt preprocessing and analysis pipelines for a large number of anatomical, functional, and diffusion MRI scans. He also helped design and test new scanning protocols and modalities for some of the HCP-related studies whose data we 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 that use this neuroimaging data to better understand the relationship between functional and structural connectivity, and how connectivity relates to both healthy brain function and neurological damage or disease.

Sneha Pandya

Research Associate

Department of Radiology

Weill Cornell Medicine, New York, NY

Sneha is a research associate in the field of biomedical engineering and currently working for Weill Cornell Medicine, NY. Over the past 8 years Sneha has worked closely with RajLab, WCM Multiple Sclerosis Center, and Sumit Niogi’s 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. CoCo Lab’s initiative to use quantitative methods and machine learning on multi-modal neuroimaging data to map brain-behavior relationships has mainly inspired her to be part of this lab. 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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Louisa Schilling

PhD Student, Neuroscience

Weill Cornell Medicine, New York, NY

 Louisa is a PhD candidate at Weill Cornell in the Neuroscience program. She received her B.Sc. in Neuroscience and Cognitive Science from University of Toronto in 2017. She then studied for her M.Sc. in Neuroscience at the Berlin School of Mind and Brain. Her master’s thesis work, which focused on the dynamics of striatal dopamine across learning, was completed at the Lak Lab of University of Oxford. At the CoCo Lab, Louisa is studying developmental alterations to the brain’s energy landscape in individuals with personal and familial history of mental illness. She is most interested in research that helps us to better understand and care for ourselves and each other.

Parker Singleton

Postdoctoral Fellow

Department of Radiology

Weill Cornell Medicine, New York NY

Parker is a postdoctoral fellow with the Radiology Department at WCM, which he transitioned to after completing his PhD in Computational Biology at Cornell. He transferred to us from the department of Chemistry and Chemical Biology where he obtained his MS in 2017 before spending 3 years as a high school and community college science teacher. Originally from South Carolina, he received his BS in Chemistry at the University of South Carolina in 2015. He is studying the effects that potent serotonergic compounds have on brain activity/connectivity and the development of neural-mass models to drive targeted brain therapies. He hopes his research can be used to inform theories of consciousness and to better understand, diagnose, and treat mental health disorders. 

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Lisa Iatckova

PhD Student

Physiology, Biophysics, and Systems Biology

Weill Cornell Medicine, New York, NY

Lisa is a second-year student at Weill Cornell in the Physiology, Biophysics & Systems Biology Graduate Program and a recipient of an NSF 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 BA in Neurobiology from Hunter College (CUNY) 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 that is altered in disease phenotypes. Lisa’s strongest aspiration in life is to contribute to the development of brain-computer interfaces that improve the quality of life for people with impaired physical and cognitive function (and maybe even augment natural brain capabilities of healthy people). Lisa is an avid reader (sci-fi is obviously her favorite genre), a mom of two rescue kitties Synna and Shishka, and a wife to the most supportive husband on Earth.

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Anthony Villegas

PhD Student

Neuroscience

Weill Cornell Medicine, New York, NY

Anthony is a second-year Ph.D. student in the Neuroscience program and Initiative to Maximize Student Development (IMSD) Fellow at Weill Cornell. He received his B.A. in Behavioral Neuroscience and B.A. in Biological Sciences from Hunter College (CUNY) in 2022. At Hunter, Anthony conducted research in the Burghardt Lab, where he the studied the effects of a diet enriched with curcumin, the active ingredient in turmeric, on prenatal development and cellular changes in adulthood. He also spent a summer at the University of Chicago investigating treatment outcomes of traumatic brain injury in the Lazaridis Lab. Presently, he is most interested in translational research that can lead to improvements in diagnosis, treatment, and quality of life in patients affected by neurodegenerative disorders.

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Ana Radanovic, MSc

PhD Student

Neuroscience

Weill Cornell Medicine, New York, NY

Ana is a second-year Ph.D. student in the Neuroscience program at Weill Cornell. Originally from California, she received her B.S. in Neuroscience and B.S. in Cognitive Science at UC Santa Cruz in 2018. Here, she conducted research in the Gibbs lab studying embodied cognition and humor as well as the Zuo lab studying the effects of a novel drug on fragile X mouse models. She then studied for her MSc. in Brain and Cognitive Sciences at the University of Amsterdam. Her master’s thesis work under Dr. Denis Engemann investigated the relationship between MRI and MEG based features of aging using machine learning. At CoCo lab, Ana is interested in using multimodal imaging to understand recovery after traumatic brain injury. She is interested in brain injury and disorders of consciousness, and hopes to improves prognostics and diagnostics for these conditions.

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Ceren Tozlu, PhD

Instructor

Department of Radiology

Weill Cornell Medicine, New York, NY

Ceren is an Instructor in the Department of Radiology of Weill Cornell Medicine and at Department of Statistics and Data Science and Computational Biology of Cornell University. She received her Bachelor’s degree at Galatasaray University in mathematics in 2013, and M.S. and Ph.D. degrees at Biostatistics, Biomathematics, Bioinformatics and Health department (3B-H) of Université Claude Bernard Lyon 1 in 2014 and 2018, respectively. She gave lectures for the M.S. students of Cancer, Neuroscience, Biostatistics and Public Health at Université Claude Bernard Lyon 1 and for the medical students at École Santé des Armées (Army Health School of France) for 4 years.

Her M.S. research project focused on the application of various machine learning methods on the voxel-based conventional human imaging data to predict the infarction risk of 3-dimensional brain tissue in acute stroke patients. Her Ph.D. thesis focused on modeling the disease evolution of stroke and Multiple Sclerosis (MS) patients based on cross-sectional and longitudinal clinical and imaging data plotted over 5 years.

Her post-doctoral research focused on (1) modeling of the disease evolution in the neurological diseases, particularly in patients with stroke and multiple sclerosis, using statistical and machine learning methods based on their demographic, clinical, regional and pair-wise functional & structural connectivity measurements, and (2) the identification of the best biomarkers of the disease evolution including the particular structural and functional connections that contributes to the differences in patients with a particular neurological disease. Her post-doctoral study aimed to develop a novel and personalized model to be used by the clinicians to predict individual disease evolution, thus to decide personalized treatment. Her early career research will focus on investigating the effects of menopause on brain health in both healthy women and women with multiple sclerosis.

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Biotechnology Building, 101D

526 Campus Road

Ithaca, NY 14850

Amy Kuceyeski, PhD

Professor

Department of Radiology

Weill Cornell Medicine, New York, NY

Computational Biology & Statistics and Data Science
Cornell University, Ithaca, NY

For over a decade, Amy has been interested in understanding how the human brain works in order 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 ground-breaking discoveries about how the brain works. Amy has particular interest in non-invasive brain stimulation and pharmacological interventions, like psychedelics, that may be used to modulate brain activity and promote recovery from disease or injury.

Amy is a co-director of the AI core for the Ann S. Bowers Women's Brain Health Initiative, an institute spanning several top academic centers that is poised to shed light on the mystery that is the female brain. The initiative will focus on understanding how the brain is changed by oral contraceptives, pregnancy, motherhood, menopause and aging/dementia. Finally, Amy is the founder and co-director of the cross-campus working group Machine Learning in Medicine, which aims to bring together ML/AI researchers in Cornell-Ithaca/Cornell-Tech and clinicians and researchers at WCM to address medicine's toughest problems. See the group's website here.

Co-Mentored Graduate Students

Suniyya Waraich (Jonathan Victor, WCM Neuroscience)

Amanda Simon (Paola Calderon, WCM Neuroscience)

Graduate Rotation Students

Marie Hedo (Maastricht University)

Natalia Prieto (Maastricht University)

Haomiao Chen (ECE Cornell)

Undergraduate Students

Nate Roy

Chidinma Ohadoma

Alec Galin

Yuchang Tian

Evelyn Goldwasser

Dara Neumann

Marian Caballo

Qinxin Wang (Tsinghua University, China)

Former PhD students

Zijin Gu, PhD (Postdoctoral Fellow, Apple Inc)

Emily Olafson, PhD (Postdoctoral Fellow, Genentech)

Elvisha Dhamala, PhD (Assistant Professor, Northwell Health)

Meenakshi Khosla, PhD (Postdoctoral Fellow, MIT)

Gia Ngo, PhD (Staff Scientist, Tech Startup)

Alumni

Cristina Rubino

Sophie Card

Sarah Dennis

Catherine Cai

Georgia Russello

Alex Lin

Yiran Li

Jason Chen

Nicholas Vartanian

Bella Nevarez

Danny Vieira

Syed Hussain Ul Bukhari

Emma Lu

James Campbell

Puneet Velidi

Elaine Wu

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Christie Gillies

PhD Student

Neuroscience

Weill Cornell Medicine, New York, NY

Christie is a second-year Ph.D. student in the Neuroscience program at Weill Cornell. She earned her B.S. in Neuroscience from the University of Michigan in 2022 with a minor in music. At Michigan, she worked as an undergraduate researcher in Dr. Sami Barmada's lab, investigating how the RNA-binding protein, Matrin 3, contributes to the pathology of amyotrophic lateral sclerosis (ALS) and fronto-temporal dementia (FTD). In the Coco lab, Christie is interested in patterns of functional connectivity reorganization and dynamic energy landscapes in the brain during stroke recovery. Additionally, she is exploring ways to leverage autoencoders to enhance dimensionality reduction in structural and functional brain connectivities, with the goal of creating more robust and clinically relevant representations of brain connectivity. Christie's overarching research goal is to contribute to advancements that can positively impact individuals affected by neurological diseases and disorders

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