I study Industrial Engineering at Rutgers, where I've learned the discipline of turning messy, probabilistic data into systems that can be predicted and trusted. I began building hardware because I realized the technologies that will make the largest impacts over my lifetime are the ones that can measure, understand, and act in the physical world.

That led me to IoT, embedded systems, and robotics, but these systems hand you noisy data. The engineering challenges I enjoy most is finding signal amongst the data and training machines to make intelligent decisions with it.

My projects sit at the intersection of mechanical design, signal processing, and AI. I built a robotic arm that uses imitation learning to autonomously conduct pick-and-place tasks; StreetSide, a cellular-based waste-monitoring system that feeds real waste container data into a vehicle-routing solver; Revere, an edge device that analyzes pipe vibrations for potential leaks to prevent water damage; and UniView, a computer vision-based occupancy product that won a university-wide competition.

At Verizon, I'm conducting research to adapt the telecom network for the wave of AI-native devices (robots, drones, and IoT). I'm using a NVIDIA Jetson AGX Dev Kit to quantify the cost and latency tradeoffs of GPU versus CPU based network architectures. I'm also contributing to an emerging product that uses Verizon’s network API to allow autonomous aircraft to create flight plans within stable network regions, enabling reliable BVLOS operations.

I'm continually working to learn more physics, mechanical design, and software skills to create valuable, reliable products that survive in the real world.

Outside the lab, I weightlift, rock climb, and read about physics and philosophy.