Graduate Students
Sarah Banker, B.A.
Ph.D. candidate (co-mentored by Dr. Jennifer Foss-Feig and Dr. Daniela Schiller)
B.A. in Neuroscience and Behavior, Wesleyan University
I am interested in understanding the neural mechanisms of aberrant social behavior and decision-making in psychiatric disease. Specifically, my research aims to combine computational modeling, human neuroimaging, and clinical assessment to examine impairments in social interaction in Autism Spectrum Disorder (ASD) and Misophonia.
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Alexandra Fink
Graduate Assistant
Ph.D. candidate in Neuroscience
Alexandra Fink is a Neuroscience PhD Candidate at the Icahn School of Medicine at Mount Sinai, where she is co-mentored by Ignacio Saez, PhD and Xiaosi Gu, PhD. Alexandra specializes in integrating multi-region human intracranial electrophysiology and computational psychiatry to investigate aberrant reward processing in psychiatric disorders, specifically Major Depressive Disorder. Her main PhD project aims to elucidate the behavioral and neurophysiological correlates of counterfactual reward processing in humans with MDD. She graduated from Duke University with a B.S. in Neuroscience in 2020, where she studied conserved brain network features between two mouse models of MDD using multi-region electrophysiology under Kafui Dzirasa, MD, PhD. After completing her PhD, Alexandra hopes to bring her expertise in electrophysiology and computational modeling of behavior to the biotechnology sector.
Qixiu Fu, B.A.
Research Assistant (co-mentored by Dr. Helen Mayberg)
B.A. in Experimental and Research Psychology (with Honors), New York University
Arianna Neal, B.S.
M.D./Ph.D. candidate
B.S. in Psychology and Neuroscience, Yale University
I've always been fascinated by how neurochemical and molecular interactions in the brain can give rise to the mind that creates such complex higher-order cognitive states -- such as mood, emotion, and learning -- as well as how computational models can be used to elucidate and interrogate the mechanisms underlying these cognitive processes. I am specifically curious about the neurocomputational and neurochemical signatures of happiness and how invasive voltammetric methods can be used to probe the neurochemistry of happiness as it varies along naturalistic variables.
Samuel Powell
M.D./Ph.D. Candidate
Samuel ("Sam") Powell is a dual-degree MD-PhD student at the Icahn School of Medicine at Mount Sinai. His work in the Gu Lab is in collaboration with Dr. Harold Koenigsberg at the Center for Mood and Personality Disorders, where he is studying new psychotherapy treatments for borderline personality disorder and the neural and computational mechanisms by which they improve this condition. In the Center for Computational Psychiatry, Sam studies the application of machine learning approaches to psychotherapy, focusing on natural language processing of transcripts as well as analysis of vocal acoustic mirroring. Sam received his PhD in neuroscience under the combined mentorship of Kristen Brennand, PhD and Schahram Akbarian, MD, PhD, and he studied the effects of genetic risk loci for schizophrenia on chromatin dynamics in human iPS cell-derived neurons. In his volunteer work, Sam is a psychotherapist who also provides supervised medication management to psychiatric outpatients in the Mental Health Clinic of the East Harlem Health Outreach Partnership (EHHOP) at Mount Sinai. In the summer of 2024, Sam will be starting a research-track residency in psychiatry.
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Ivan Wolanksy
M.D. Candidate
B.A. in Data Science, Columbia University
I am interested in utilizing data science and artificial intelligence to explore new ways of understanding psychiatric illnesses. I hope to help create tools that can be used in clinical settings to assist mental health professionals in making diagnoses, in addition to creating biomarkers that can be used to more concretely make diagnoses.
Alexis Baptiste
PREP Scholar
B.S. in Neuroscience concentration in Psychology, Loyola University New Orleans
I am interested in understanding the neural mechanisms underlying psychiatric disorders in relation to self-concept, self-identity, and social identity in order to create alternative holistic treatments to alleviate mental illness. Additionally, I am interested in understanding the association between learning, negative emotional stimuli, and neuroplasticity using neuroimaging and computational modeling techniques. I intend to obtain a MD/PhD or PhD degree with a focus in Neuroscience in the future.
Mu Li, M.S.
Master's Student in Biomedical Science
M.A. in Experimental and Research Psychology, New York University
My interests and goals involve the application of computational models, artificial intelligence, and neuroimaging techniques in the study of psychiatric disorders. I aim to explore distinctions in behavior and neural mechanisms between individuals with psychiatric disorders and those who are healthy, utilizing these methods. Additionally, I'm focused on investigating the relationships between cognitive decline and changes in behavior and neural mechanisms within psychiatric disorders. Ultimately, to detect and predict the onset of the disease, as well as to develop diagnostic and treatment methods. Currently, I'm examining differences in computational and neural mechanisms related to social controllability and relationships within populations affected by borderline personality disorder (BPD) and avoidant personality disorder (AvPD).
Atmana Joshi, M.S.
Master's Student
I am currently a graduate student in the Master of Science in Biomedical Sciences program at Mount Sinai. I completed a Bachelor of Science in Informatics with Pre-Med from Indiana University. My professional and academic background is in clinical information systems and healthcare data analytics. I have previously served as a Data Analyst for Regenstrief Institute and as a Clinical Informatics Specialist at Oak Street Health. My previous research experience was focused on public health sectors like rural/urban healthcare access and physician workforce distribution. Currently, I’m working on a project that explores differences in social decision making in medical vs recreational cannabis users. It aims to look at social controllability estimation by using the consequential future outcomes to compute action values.