Summary
Byung Cho is a Technical Staff scientist at MIT Lincoln Laboratory with a decade of experience applying acoustic remote sensing, statistical inference, and signal/image processing to challenging underwater and wide-area sensing problems. He completed a Ph.D. at MIT focused on first-principles modeling of acoustic wave propagation and scattering, with published work that spans Nature Scientific Reports, Remote Sensing, and Fish and Fisheries. At MIT he led large-scale experiment design and data acquisition, synthesizing continental-shelf-scale acoustic imagery via maximum likelihood methods and characterizing nonlinear acoustic signatures. His background blends rigorous theoretical modeling with hands-on field campaigns and practical machine-learning work from an internship at Philips where he built clinically validated classifiers and managed multi-hospital SQL systems. Based in Cambridge, MA, he brings a rare mix of deep acoustics expertise, statistical rigor, and systems-level implementation experience that enables moving research into operational sensing capabilities. An often-overlooked strength is his demonstrated ability to reconcile multi-scale physics (from second-order nonlinear effects to 100+ km imaging) into tractable inference algorithms.
10 years of coding experience
8 years of employment as a software developer
Master’s Degree, Acoustics, Master’s Degree, Acoustics at Seoul National University
Doctor of Philosophy (Ph.D.), Acoustics and Remote Sensing, Doctor of Philosophy (Ph.D.), Acoustics and Remote Sensing at Massachusetts Institute of Technology
English, Korean