Alexander (AJ) joined NVIDIA as a research intern in summer 2025, working on a user-scheduable programming language for high-performance spatial queries (e.g. ray tracing, closest point queries, or collision detection). He is broadly interested in improving the performance of visual computing applications with domain-specific languages, compilers, and architectures.

He is a Ph.D. student at Stanford advised by Fred Kjolstad working on these topics, and he received his undergraduate and master’s degrees from MIT, working with Jonathan Ragan-Kelley and Andrew Adams on fast vector instruction selection algorithms.