Welcome. I am currently a senior software algorithms engineer at TDK USA Corporation, where I work on multimodal language modeling.
My own research interests center on subquadratic neural network architectures, particularly state space models. I am drawn to the question of how sequence models can capture long-range structure without paying the quadratic cost of attention, and to what the inductive biases of these architectures reveal about the sequences they are asked to model.
I hold a joint PhD between the Machine Learning Department and the Program in Neural Computation at Carnegie Mellon University, where my research focused on neural manifolds and the mechanisms underlying multi-task learning and catastrophic forgetting. I also hold a master's degree in machine learning from Carnegie Mellon.
Prior to this, I worked at a startup called Neubay, building deep learning models. I did my undergraduate at the University of Washington in computer science and neurobiology. During this time, I conducted research developing new methods for brain-computer interfacing.