Gholson Glass helps clients navigate the rapidly evolving patent landscape for machine learning and artificial intelligence-based innovations, in both the United States and internationally. He studied mechanical and electrical engineering at MIT, and his practice reflects both disciplines. Alongside his artificial intelligence and machine learning work, he protects mechanical and materials-driven products for fluid handling, packaging and industrial applications, and the manufacturing processes and controls behind them.

With over a decade of experience in helping clients protect their machine learning-based inventions – predating the introduction of the Transformer architecture – Gholson brings deep technical knowledge spanning a wide range of subject matter areas, including artificial intelligence and machine learning model development and architectural design, as well as user-facing deployments and system implementations.

Gholson's mechanical and materials patent work also spans more than a decade. He has prepared and prosecuted patent applications for flexible and extruded tubing, hose and coupling assemblies, reinforced and overmolded structures, injection-molding and hot-runner equipment, and offshore, subsea and marine-survey systems. These matters turn on the engineering decisions behind a successful physical product: polymer and elastomer selection, component geometry and tolerances, joining and assembly, manufacturability, and durability under pressure, stress and repeated use.

Additional areas of significant experience include cellular and wireless communications systems and optimizations, network architecture, and communication protocol enhancements, including technologies considered as standardization candidates as well as those ultimately adopted into the 3GPP standards for 5G NR and beyond.

Prior to joining Polsinelli, Gholson interned at NASA's Goddard Space Flight Center, researching optimal telerobotic control station design and implementation, and while at MIT, wrote code that ran in space.