I develop machine learning systems for healthcare workforce optimization and create statistical methods for experimental design. My research focuses on online learning, hierarchical modeling, and computational approaches to biomedical data analysis.
My work spans theoretical development and practical applications in statistical learning
Multi-armed bandits, hierarchical models, and uncertainty quantification in production ML systems
Experimental design, resampling methods, and statistical software for nested data structures
Biostatistics, neuroscience applications, and bioinformatics tools for biological data analysis
Statistical learning, computational biology, and data science
Hierarchical resampling provides exact statistical tests for nested experimental designs by combining bootstrap resampling within experimental units with permutation testing at the randomization level. This approach maintains Type I error control while using all available information, unlike traditional methods that either pool inappropriately or discard useful data.
A guide to planning scientific projects and asking the right research questions during your PhD, based on insights from my piece for New Science on strategic research planning. Check out the full article here.
Research in computational biology, statistical methods, and neuroscience
Neurons communicate with each other through electrochemical transmission at synapses. Microglia, the resident immune cells of the central nervous system, modulate this communication through a variety of contact-dependent and -independent means. Microglial secretion of active sialidase enzymes upon exposure to inflammatory stimuli is one unexplored mechanism of modulation. Recent work from our lab showed that treatment of neurons with bacterial sialidases disrupts neuronal network connectivity. Here, we find that activated microglia secrete neuraminidase-3 (Neu3) associated with fusogenic extracellular vesicles. Furthermore, we show that Neu3 mediates contact-independent disruption of neuronal network synchronicity through neuronal glycocalyx remodeling. We observe that NEU3 is transcriptionally upregulated upon exposure to inflammatory stimuli and that a genetic knockout of NEU3 abrogates the sialidase activity of inflammatory microglial secretions. Moreover, we demonstrate that Neu3 is associated with a subpopulation of extracellular vesicles, possibly exosomes, that are secreted by microglia upon inflammatory insult. Finally, we demonstrate that Neu3 is necessary and sufficient to both desialylate neurons and decrease neuronal network connectivity. These results implicate Neu3 in remodeling of the glycocalyx leading to aberrant network-level activity of neurons, with implications in neuroinflammatory diseases such as Parkinson's disease and Alzheimer's disease.
While hierarchical experimental designs are near-ubiquitous in neuroscience and biomedical research, researchers often do not take the structure of their datasets into account while performing statistical hypothesis tests. We present Hierarch, a Python package for analyzing nested experimental designs. Using a combination of permutation resampling and bootstrap aggregation, Hierarch can be used to perform hypothesis tests that maintain nominal Type I error rates and generate confidence intervals that maintain the nominal coverage probability without making distributional assumptions about the dataset of interest.
We have designed, synthesized, and applied a rhodol-based chromophore to a molecular wire-based platform for voltage sensing to achieve fast, sensitive, and bright voltage sensing using two-photon (2P) illumination. Rhodol VoltageFluor-5 (RVF5) is a voltage-sensitive dye with improved 2P cross-section for use in thick tissue or brain samples. RVF5 features a dichlororhodol core with pyrrolidyl substitution at the nitrogen center. In mammalian cells under one-photon (1P) illumination, RVF5 demonstrates high voltage sensitivity (28% ΔF/F per 100 mV) and improved photostability relative to first-generation voltage sensors. This photostability enables multisite optical recordings from neurons lacking tuberous sclerosis complex 1, Tsc1, in a mouse model of genetic epilepsy. Using RVF5, we show that Tsc1 KO neurons exhibit increased activity relative to wild-type neurons and additionally show that the proportion of active neurons in the network increases with the loss of Tsc1. The high photostability and voltage sensitivity of RVF5 is recapitulated under 2P illumination. Finally, the ability to chemically tune the 2P absorption profile through the use of rhodol scaffolds affords the unique opportunity to image neuronal voltage changes in acutely prepared mouse brain slices using 2P illumination. Stimulation of the mouse hippocampus evoked spiking activity that was readily discerned with bath-applied RVF5, demonstrating the utility of RVF5 and molecular wire-based voltage sensors with 2P-optimized fluorophores for imaging voltage in intact brain tissue.