Mohammad Noshad's office at Harvard wasn't a place where things got built fast. It was a place where things got understood deeply - signal processing, photonics, the mathematics of how information travels through light. He published. He cited. He won awards. Then he left.
The pivot wasn't dramatic. It was logical. Noshad had spent years at the intersection of sensors, AI, and optical systems. When the COVID-19 pandemic exposed how badly hospital infection control had stalled - still relying on manual cleaning schedules, human judgment, and mercury-lamp UV carts that required rooms to be evacuated - he saw a gap that his exact skill set could fill.
In 2020, Noshad co-founded Shyld AI with his brother Morteza, a Stanford-trained engineer with deep expertise in edge computing. They bootstrapped the first device themselves. The concept was simple in ambition, intricate in execution: mount a sensor array on a hospital ceiling, give it enough compute to run AI inferences in real time, train it to identify contaminated surfaces based on room activity patterns, and arm it with UV-C LEDs precise enough to disinfect targeted zones without irradiating the humans below.