I'm a PhD student advised by
Rich Baraniuk in the
DSP group at Rice University, and I'm currently working on probabilistic frameworks for deep learning with
Ankit Patel in the Department of Neuroscience at Baylor College of Medicine. Our group is interested in designing generative models that can explain the successes and shortcomings of modern deep learning architectures from first principles. New and improved architectures can then be synthesized via statistical inference in these models. My research is focused on applying this strategy to gated recurrent neural networks.
