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Posts by Collection
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publications
Using machine learning on clinical data to identify unexpected patterns in groups of COVID-19 patients
Published in Nature Scientific Reports, 2023
We leverage JH-CROWN: The COVID Precision Medicine Analytics Platform Registry to identify subgroups of COVID-19 patients who are at high risks for severe disease progression.
Recommended citation: Cowley HP, Robinette MS, Matelsky JK, Xenes D, Kashyap A., Ibrahim NF, Robinson ML, Zeger S, Garibaldi BT, Gray-Roncal W. Using machine learning on clinical data to identify unexpected patterns in groups of covid-19 patients. Scientific Reports, 13(1). February 2023. https://doi.org/10.1038/s41598-022-26294-9 https://www.nature.com/articles/s41598-022-26294-9
Trade-offs in concentration sensing in dynamic environments
Published in Biophysical Journal, 2024
We model a eukaryotic cell sensing a chemical secreted from bacteria and develop analytical calculations and stochastic simulations of sensing in this environment. We find that cells can have a huge variety of optimal sensing strategies ranging from not time averaging at all to averaging over an arbitrarily long time or having a finite optimal averaging time.
Recommended citation: Kashyap A, Wang W, Camley BA. Trade-offs in concentration sensing in dynamic environments. Biophysical Journal, 123(10). May 2024. 10.1016/j.bpj.2024.03.025 https://www.cell.com/biophysj/fulltext/S0006-3495(24)00205-4
talks
Building a Research Agenda for Justice Informatics
Published:
Co-facilitator of the workshop put on by the Justice Informatics group, focused on assessing the state of justice-oriented research practices in the informatics field.
Investigating racial inequality in drug prescriptions for patients with endometriosis
Published:
Podium abstract at the World Congress on Endometriosis (2023) on racial disparities in drug prescriptions for patients with endometriosis
Synthesizing Gaps and Priorities for a Justice Informatics Research
Published:
Co-presenter of the Justice Informatics Collaborative’s podium abstract; we presented our principles of justice-oriented biomedical informatics research synthesized from our previous workshop and suggested next steps for various stakeholders interested in incorporating justice into their work.
Machine learning for time-series biomedical data
Published:
I was a guest lecturer for Columbia University’s Machine Learning for Healthcare class. My lecture covered processing of various types of time-series biomedical data and provided an overview of machine learning methods suitable for time-series data (e.g. RNNs, transformers, survival analysis).
teaching
Acculturation to Programming and Statistics
Teaching Assistant, Columbia University, 2023
I was a TA for Acculturation to Programming and Statistics in the Departemnt of Biomedical Informatics at Columbia University. This class is caters to students from a wide variety of mathematical and computational backgrounds and provides tools for navigating the informatics landscape. For this class, I created and delivered weekly lectures and semiweekly lab assignments.
Machine Learning for Healthcare
Teaching Assistant, Columbia University, 2024
I was a TA for Machine Learning for Healthcare in the Departemnt of Biomedical Informatics at Columbia University. This class offers a survey of various machine learning topics, with an emphasis on biological and clinical applications. For this class, I designed weekly homework assignments and mentored students for their final project.