Research
I am a postdoctoral researcher at Zuckerman Institute, Columbia University working with Dr. Liam Paninski and the International Brain Laboratory (IBL). My research interests lie at the intersection of computational neuroscience and machine learning. My current research is focused on improving analysis methods for high-density extracellular recordings through the application of modern machine learning methods. I am also working on novel approaches for analyzing the neuronal dynamics underlying behavior and video tracking of behavior.
News
- Our paper “Towards robust and generalizable representations of extracellular data using contrastive learning” was accepted at NeurIPS 2023.
- Our paper Bypassing spike sorting: Density-based decoding using spike localization from dense multielectrode probes was accepted at NeurIPS 2023 as a spotlight paper.
- New preprint: Ultra-high density electrodes improve detection, yield, and cell type specificity of brain recordings.
- New preprint: DARTsort: A modular drift tracking spike sorter for high-density multi-electrode probes
- New preprint: Lightning Pose: improved animal pose estimation via semi-supervised learning, Bayesian ensembling, and cloud-native open-source tools.
- New IBL preprint: Spike sorting pipeline for the International Brain Laboratory.
- New IBL preprint: Reproducibility of in-vivo electrophysiological measurements in mice
- I joined the International Brain Laboratory (IBL).
- I am working as a postdoctoral researcher at Zuckerman Institute supervised by Dr. Liam Paninski.
- I completed my PhD and published my thesis: Scalable software and models for large-scale extracellular recordings
- Our paper Targeted Neural Dynamical Modeling was accepted at NeurIPS 2021.
- Our paper Building population models for large-scale neural recordings: opportunities and pitfalls was published in Current Opinion in Neurobiology.
- Our paper SpikeInterface, a unified framework for spike sorting was published in eLife.
- Our paper SpikeForest: reproducible web-facing ground-truth validation of automated neural spike sorters was published in eLife.