Department of Radiology
Weill Cornell Medicine, New York, NY
Cornell University, Ithaca, NY
Lab Members
Keith Jamison, MS, PhD
Research Associate
Department of Radiology
Weill Cornell Medicine, New York, NY
Keith Jamison is a Research Associate in the CoCo Lab. He received his B.S. in Computer Science, M.Eng. in Biomedical Engineering, and Ph.D. in Computational Biology from Cornell University. His work combines neuroimaging, machine learning, and scientific software development to study individual differences in brain structure and function. Before joining the CoCo Lab, Keith worked on the Human Connectome Project at the University of Minnesota, where he helped implement and adapt preprocessing and analysis pipelines for large-scale anatomical, functional, and diffusion MRI datasets, and contributed to the development and testing of new scanning protocols. In the CoCo Lab, Keith develops computational methods for modeling relationships between structural and functional brain connectivity. His recent work focuses on using machine learning to integrate multimodal neuroimaging data, characterize subject-specific patterns of brain organization, and support collaborative studies of neurological disease, injury, aging, and brain health.
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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.
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.
Amy Kuceyeski, PhD
Professor
Department of Radiology
Weill Cornell Medicine, New York, NY
Computational Biology
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 was the founder and for over a decade the 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.
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.
Daniel Chong, M.S.E.
PhD Student
Electrical and Computer Engineering
Cornell University, Ithaca NY
Daniel is a Ph.D. student in the Electrical and Computer Engineering Department at Cornell University. He earned both his B.S. in Electrical Engineering and Computer Science and his M.S.E. in Electrical Engineering from Johns Hopkins University in 2023. At Johns Hopkins, he conducted research under Dr. Mounya Elhilali applying machine learning to pediatric lung auscultation screening. He is also in the Pathways program at NASA Johnson Space Center, where he has contributed to astronaut health research and robotic flight control projects during his undergraduate and graduate studies. His current research interests lie in the field of NeuroAI, investigating how principles of brain computation and cognition can play a role in advancing future AI systems.
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Yunrui Zhang
PhD Student
Electrical and Computer Engineering
Cornell University, Ithaca, NY
Yunrui is a PhD student in the Department of Electrical and Computer Engineering at Cornell University. She received her B.Eng. in Automation Engineering from Tsinghua University in 2024. During her time at Tsinghua, Yunrui conducted research in Prof. Gangtie Zheng’s lab on multi-modal image-guided surgical robotics and in Prof. Rebing Wu’s lab on quantum control algorithms. She also spent a summer as a research intern in Prof. Fan Lam’s lab at the University of Illinois Urbana-Champaign, where she developed CNN-based MRSI reconstruction algorithms. At CoCo Lab, Yunrui’s research focuses on applying cutting-edge AI/ML methods to study human brain mechanisms, particularly fMRI brain-behavior mapping and the encoding and decoding of brain responses during naturalistic viewing. Yunrui is co-advised by Prof. Mert Sabuncu. Yunrui's personal website can be found here.
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Willian De Faria
MD-PhD Student
Tri-I Program
Weill Cornell Medicine, New York, NY
Willian is an MD/PhD student interested in the intersection of cognitive neuroscience, AI, and medicine. Prior to joining Weill Cornell, he worked in the lab of Dr. Nancy Kanwisher where he used computational modeling of MEG data to identify signals related to visual processing, particularly with respect to the physical properties of objects and scenes. After completing two years of medical school, he became interested in dementia and neurodegeneration and how it presents differently in men and women. In the CoCoLab, he will use novel deep learning approaches on functional and structural connectomes to identify early biomarkers of Alzheimer's Disease (AD). In doing so, he hopes to translate this work to (1) better design clinical trials of AD treatment, and (2) discover novel neuronal substrates that distinguish sex-specific differences in neurodegeneration. In his spare time, he volunteers at the Weill Cornell Center for Human Rights and roots for the New York Knicks!
Safaa Mouline
PhD Student
Biomedical Engineering
Cornell University, Ithaca, NY
Safaa is a first-year PhD student in the Biomedical Engineering Department at Cornell University. She earned her B.S. in Bioengineering and B.A. in Computer Science from the University of California, Berkeley in 2025. During her undergraduate studies, she used computational techniques to study proteins. During a summer in the Vanni Lab at the University of Fribourg, she investigated protein aggregation propensities using molecular dynamics simulations, and in Professor Mofrad’s lab at Berkeley, she worked on protein function prediction using protein large language models. At the CoCo Lab, Safaa is currently using structural and functional brain connectivities to predict aphasia outcomes. She is broadly interested in the intersection of machine learning and neuroscience.
Former PhD students & Postdoctoral fellows
Ke Huang, PhD (Assistant Professor, University of Massachusetts Lowell)
Lisa Iatckova, PhD
Louisa Schilling, PhD (Data Scientist, Google)
Ceren Tozlu, PhD (Research Scientist, Sanofi)
Hussain Al-Bukhari, PhD
Amanda Simon, PhD (Consultant, Beghou Consulting)
Parker Singleton, PhD (Senior Data Scientist, University of Pennsylvania)
Suniyya Waraich, PhD (Postdoctoral Fellow, UCD)
Zijin Gu, PhD (Member of Technical Staff, OpenAI)
Emily Olafson, PhD (Principal Scientist - Imaging, Genentech)
Elvisha Dhamala, PhD (Assistant Professor, Northwell Health)
Meenakshi Khosla, PhD (Assistant Professor, UCSD)
Gia Ngo, PhD (Head of Engineering, Klutch AI)
Former Masters students
Xuemin Zhu, MSc (ECE, Cornell University)
Natalia Avendano-Prieto (TUM, Germany)