Summary
Elsie Cortes is a PhD candidate in computer science with nine years of experience specializing in physics-based modeling and physics-informed neural networks, particularly for wave propagation and optical cloaking. She combines applied mathematics rigor with practical computational engineering to build optimized, high-accuracy models and bespoke neural architectures. Known for improving algorithmic efficiency and expanding projects into novel directions, she enjoys designing tools that clarify and extend scientific inquiry. Based in California, she thrives in collaborative, open-research environments and is eager to join a university or research group tackling interdisciplinary problems at the intersection of simulation and deep learning.
9 years of coding experience
Bachelor of Science - BS, Computer Science, Bachelor of Science - BS, Computer Science at University of California, Merced