Myrl G. Marmarelis
I am serving as a postdoctoral scholar in the Computing + Mathematical Sciences department at the California Institute of Technology (Caltech). My mentors are Anima Anandkumar, R. Michael Alvarez, and Frederick Eberhardt. In May 2024, earned my PhD in Computer Science from the University of Southern California while working at the Information Sciences Institute under the supervision of Greg Ver Steeg, Aram Galstyan, and Fred Morstatter. My contributions continue to focus on robust causal inference and high-dimensional statistics. I have been fortunate to forge collaborations across multiple disciplines, including a project with Heinz-Josef Lenz using clinical-trial data, a project with Neda Jahanshad using the UK Biobank, and a project with Abigail Horn on mobility data.
I spent the summer of 2024 as a statistics engineer at Eppo, building a pipeline for long-term metric prediction in experiments. I had previous internships in machine learning and data engineering at Bloomberg and Research Affiliates.
Separately, I have spent time developing an end-to-end system for realtime monitoring of ultradian rhythms, those few-hour cycles in the human body that seem to modulate alertness. My eventual goal is to promote long-term wellness and health through novel uses of comfortable, noninvasive, and affordable wearables.
Selected Publications
Recorded Talks
Causality Discussion Group (August 2023) for the UAI '23 work.
UAI 2023 single-track oral presentation on Partial Identification of Dose Responses with Hidden Confounders.
USC Biostatistics Seminar (April 2023) on Latent Factor Discovery with Transcriptomics Data with Greg.
Aspirations
I am trying to make my work relevant in the battle against climate change, or improving public health. Feel free to reach out for possible collaborations.
Open Source
RankedChoices.jl --- A Julia package to facilitate analysis of ranked preferences.
rolling-quantiles --- A Python package to quickly stream rolling quantiles via a backend written in C.