Summary
Leo Adams is a software engineer with 10 years of experience specializing in data engineering, firmware, and applied machine learning for real-time systems. Based in Palo Alto, he has built adaptive EV charging infrastructure and one of the region’s most comprehensive charging databases, contributing firmware for power-line communication and cloud pipelines for real-time ingestion and visualization. He implemented unsupervised anomaly detection using an LSTM autoencoder and leverages Grafana for operational insight and cost optimization. A Georgia Tech CS master’s and a background in image reconstruction at Stanford Radiology Lab (Python, C++, CUDA, dense optical flow) give him both theoretical depth and hands-on systems experience. His interest in the humanities informs a pragmatic, ethics-minded approach to technical problem solving and product design.
10 years of coding experience
Gunn High School
Master's degree Computer Science, Master's degree Computer Science at Georgia Institute of Technology
Bachelor's degree Computer Science, Bachelor's degree Computer Science at Willamette University