David is a PhD student with Máté Lengyel in the Computational and Biological Learning group at the University of Cambridge, developing and applying state-of-the-art methods for neural data analysis with a focus on studying neural variability. He has also worked at Meta Reality Labs CTRL as a research scientist intern, building and researching EMG neuromotor interfaces. Before this, he completed the Natural Sciences Tripos specializing in computational and theoretical physics, with his thesis on synchronization in simplified models of cilia supervised by Pietro Cicuta. His main interests lie in neuroscience, machine learning, and their intersection. In particular, he is excited about understanding and decoding big neural data, as well as potential computational functions in discrete spiking activity that go beyond analog neural firing rates. He also retains an active interest in physics, in particular in its interfaces with biology and machine learning. In addition, he has a keen interest in cell biology, with strong exposure to the subject prior to focussing on physics.