Welcome to the Keeley Lab! Here, we use methods statistics and machine learning to understand complex neuroscience and behavioral data. We are located at the Lincoln Center campus at Fordham University in New York City.
I am an Assistant Professor at the Department of Natural Sciences at Fordham University. I do research at the interface of machine learning and neuroscience. My work primarily focuses on bayesian statistical methods for high dimensional neural data sets with a focus on latent variable models. I also work with Reality Labs Research to develop model behavioral in high dimensional psychophysical tasks.
I did my Ph.D. at NYU's Center for Neural Science in the labs of John Rinzel and Andre Fenton, and then worked as a postdoctoral researcher with Jonathan Pillow.
Summer 2023 Lab Schedule
6/1 contrastive PCA and it's applications to biomedical data (Deenan He)
6/8 Hidden Markov Models (Arina Medvedeva)
6/15 TBD (Rabia Gondur)
6/22 TBD (Stephen Keeley)
Summer 2022 Lab Schedule
6/28 Factor Analysis and the Expectation Maximization Algorithm (Gabriel Yancy)
7/5 Variational Inference (Rabia Gondur)
7/12 Probabilistic PCA and Bayesian PCA (Deenan He)
7/19 Bayesian Linear Regression (possible intro to Gaussian Processes) (Stephen Keeley)
7/26 Convolutional Neural Networks (Jin Qian)
8/2 Variational Autoencoders and VAEs in neuroscience (Rabia Gondur)
8/9 Disentangling the flow of signals between populations of neurons (Gabriel Yancy)
8/18 Project outline - Using an appropriate prior to learn partitioned loadings in multi-region factor models for neural data (Deenan He)
8/26 Project outline - Augmenting GP-VAEs to jointly model neural activity and limb tracking in drosophila (Rabia Gondur)