Spectral gradient methods, such as the recently popularized Muon algorithm, are a promising alternative to standard Euclidean gradient descent for training deep neural networks and transformers, but it is still […]
This dissertation explores non-Hermitian control as a unified framework for photonic switching and reconfigurable light routing. First, by harnessing gain–loss modulation and parity–time symmetry breaking in hybrid III–V/silicon platforms, a […]
This will be a hybrid event with in-person attendance in Levine 307 and virtual attendance on Zoom. ABSTRACT Recent advances in generative AI have demonstrated the power of scaling: large […]
Abstract: Bioengineering of plants is critical to agriculture, molecular farming, and bio-commodities. However, current tools for bioengineering plants are limited in throughput, applicable to a narrow set of species, or […]
