Department of Radiology
Weill Cornell Medicine, New York, NY
Cornell University, Ithaca, NY
Lab Members
Keith Jamison, MS
Research Associate
Department of Radiology
Weill Cornell Medicine, New York, NY
PhD candidate
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.
Ke Huang, PhD
Postdoctoral Fellow
Department of Radiology
Weill Cornell Medicine, New York, NY
Ke is a postdoctoral fellow at the CoCo Lab. She earned her M.S. in Statistics from Texas A&M University (TAMU) in 2019 and her Ph.D. in Applied Statistics from the University of California, Riverside (UCR), in 2024. At TAMU, Ke applied statistical methods to analyze epidemiological data, focusing on cardiovascular diseases, obesity, and women’s health issues. During her time at UCR, she conducted research on the statistical learning theory of deep learning, developing AI and machie learning methods to analyze medical data. Currently, at the CoCo Lab, Ke uses computational and AI techniques to analyze human brain data, with a focus on understanding how brain structure and function are influenced by life events, particularly in relation to women’s brain health.
Louisa Schilling
PhD Candidate
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.
Lisa Iatckova
PhD Candidate
Physiology, Biophysics, and Systems Biology
Weill Cornell Medicine, New York, NY
Lisa is a PhD candidate 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 Candidate
Neuroscience
Weill Cornell Medicine, New York, NY
Anthony is a Ph.D. candidate 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.
Ana Radanovic, MSc
PhD Candidate
Neuroscience
Weill Cornell Medicine, New York, NY
Ana is a Ph.D. candidate 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.
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.
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 puberty, menstruation, 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.
Christie Gillies
PhD Candidate
Neuroscience
Weill Cornell Medicine, New York, NY
Christie is a Ph.D. candidate 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's current research is focused on understanding the sex-specific role of brain networks in stroke recovery patterns. Specifically, 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 post-stroke. Christie's overarching research goal is to create a meaningful impact in advancing our understanding of brain mechanisms underlying injury or disease, and to leverage these insights to enhance recovery, with a particular focus on addressing disparities in women's health research.
Haomiao Chen
PhD Student
Electrical and Computer Engineering
Cornell University, Ithaca, NY
Haomiao is a PhD candidate in the Department of Electrical and Computer Engineering at Cornell University. He completed his BS degree in Physics with a minor in Computer Science at the University of Illinois at Urbana-Champaign (UIUC) in 2023. During his time at UIUC, Haomiao conducted research on Cryo-EM reconstruction under the supervision of Prof. Zhizhen Zhao and worked on embodied AI projects with Prof. Julia Hockenmaier. Additionally, he gained industry experience through a summer internship at Meta Reality Lab, focusing on computational photography. Currently, at CoCo Lab, Haomiao's research interests lie at the intersection of machine learning and neuroscience. He is particularly intrigued by the relationship between brain responses and stimuli, aiming to predict neural activation based on given stimuli and to generate stimuli that achieve targeted neural activation. He is co-mentored by Mert Sabuncu.
Marie Hédo, M.Sc.
PhD Student
Computational Biology
Cornell University, Ithaca, NY
Marie is a first-year PhD student in the Computational Biology program at Cornell University. She received her B.Sc. in Psychology, majoring in Cognitive Neuropsychology from Tilburg University in the Netherlands. Following that, she completed an M.Sc in Cognitive and Clinical Neuroscience with a specialization in Cognitive Neuroscience from Maastricht University. Marie joined the CoCo lab to conduct her master’s thesis research, where she analyzed changes in brain dynamics and the brain’s energy landscape in children with ADHD. Her current research interests focus on exploring sex-specific symptomatology and alterations in brain dynamics and energy landscapes related to childhood psychopathology.
Co-Mentored PhD Students
Amanda Simon (Paola Calderon, WCM Neuroscience)
Masters Students
Natalia Avendano-Prieto (TUM)
Former PhD students
Parker Singleton (Postdoctoral Fellow, University of Pennsylvania)
Suniyya Waraich (Postdoctoral Fellow, UCSD)
Zijin Gu, PhD (Research Scientist, Apple Inc)
Emily Olafson, PhD (Postdoctoral Fellow, Genentech)
Elvisha Dhamala, PhD (Assistant Professor, Northwell Health)
Meenakshi Khosla, PhD (Assistant Professor, UCSD)
Gia Ngo, PhD (Staff Scientist, Tech Startup)
Former Masters students
Xuemin Zhu, MSc (ECE, Cornell University)
Alumni
Qinxin Wang (Tsinghua University, China)
Nate Roy
Chidinma Ohadoma
Alec Galin
Yuchang Tian
Evelyn Goldwasser
Cristina Rubino
Sophie Card
Sarah Dennis
Catherine Cai
Georgia Russello
Alex Lin
Yiran Li
Jason Chen
Bella Nevarez
Emma Lu
James Campbell
Puneet Velidi
Elaine Wu