Multimodal Learning with Graphs
Survey of 140 studies in graph-centric AI to establish a framework for multimodal graph learning.
Hi! I am an undergraduate at Harvard studying Computational Neuroscience and student researcher designing machine learning and bioinformatics pipelines to decipher neurodegeneration. I currently work in the Department of Biomedical Informatics at Harvard Medical School (advised by Marinka Zitnik), the Wyss Institute for Biologically Inspired Engineering (advised by George Church), and the Institute for Neurodegenerative Disease at Massachusetts General Hospital (advised by Sudeshna Das, Alberto Serrano-Pozo, and Bradley T. Hyman).
I'm passionate about using entrepreneurship to translate academic discoveries to new therapeutics and technologies that move our world forward. Beyond my research and entrepreneurial endeavors, I'm a photography enthusiast, creative writer, and avid consumer of mangoes.
Some of my most recent work is shown below. If anything piques your interest, I would love to hear from you. Please don't hesitate to reach out! To stay updated with my work and life, you can follow me on social media.
First and co-first author publications are indicated in red. For a full list of my publications, please see here.
Survey of 140 studies in graph-centric AI to establish a framework for multimodal graph learning.
Development and evaluation of a natural language processing annotation tool to facilitate phenotyping of cognitive status in electronic health records.
Plasma biomarkers for prognosis of cognitive decline in patients with mild cognitive impairment.
Cyclic multiplex fluorescent immunohistochemistry and machine learning reveal distinct states of astrocytes and microglia in normal aging and Alzheimer’s disease.
Effect of APOE alleles on the glial transcriptome in normal aging and Alzheimer’s disease.
Systematic review of human post-mortem immunohistochemical studies and bioinformatics analyses unveil the complexity of astrocyte reaction in Alzheimer's disease.
Active deep learning to detect cognitive concerns in electronic health records.
Systematic review and meta-analysis of human transcriptomics reveals neuroinflammation, deficient energy metabolism, and proteostasis failure across neurodegeneration.
Differential gene expression data from the human central nervous system across Alzheimer's disease, Lewy body diseases, and the amyotrophic lateral sclerosis and frontotemporal dementia spectrum.
Meta-analysis of mouse transcriptomic studies supports a context-dependent astrocyte reaction in acute CNS injury versus neurodegeneration.
Composition of Caenorhabditis elegans extracellular vesicles suggests roles in metabolism, immunity, and aging.
An interscholastic network to generate LexA enhancer trap lines in Drosophila.
Advised by Dr. Marinka Zitnik in the Department of Biomedical Informatics at Harvard Medical School, studying applied machine learning on network systems in biology and medicine.
Advised by Dr. George Church and Dr. Jenny Tam, applying graph AI on patient-derived cerebral organoids for drug repurposing in neuropsychiatric disorders.
Advised by Dr. Sudeshna Das at the MassGeneral Institute for Neurodegenerative Disease, developing integrative computational methods in biomedical and brain research.
Biology Fellow at Fifty Years helping great scientists leverage breakthroughs in biology to found iconic companies and solve pressing global challenges.
Leading partnerships at Nucleate Dojo to empower the next-generation of biotechnology innovators.
A publicly-available atlas of markers of reactive astrogliosis in Alzheimer's and associated bioinformatics analyses.
Open data analysis platform for Alzheimer's disease.
For the Harvard Data Analytics Group Data Science Fellowship, characterized the public pandemic discourse by applying NLP on COVID-related tweets.