Computational neuroscience and neuroengineering; closed-loop neuromodulation; dimensionality reduction; interactive machine learning; explainable AI; neuromorphic computing; neuroethics and public engagement.
Research interests: time-frequency analysis of neural data; brain stimulation; machine learning for biological signal processing; cognition.
Research interests: closed-loop control of neural systems; neural coding; cognitive modeling.
Co-advised by Thad Starner
Research interests: computer vision; unsupervised learning.
Co-advised by Matthieu Bloch
Research interests: information theory; interactive machine learning.
Computational Neuroengineering Training Program Graduate Scholar
Research interests: machine learning; generative models; dynamical systems.