Eric Zelikman is a deep learning engineer fascinated by how (and whether) algorithms learn meaningful representations. A recent graduate from Stanford’s Symbolic Systems program, Eric studies efficient, robust, and disentangled representations across ML fields. Eric hopes machine learning can teach us about non-machine learning and help us overcome the challenges facing humanity.