About
I like building things with AI. My work sits at the boundary of machine learning research and production software — taking ideas from papers and turning them into systems that actually work at scale.
Most recently I was at Amazon, where I helped launch and scale Bedrock Batch Inference to 100B tokens/day. Before that I spent time at Carnegie Mellon working on NLP problems like factuality in summarization and transformer optimization for edge devices.
Now I'm building Dyno Apps, a no-code mobile app platform powered by AI coding agents. I'm interested in how LLMs can go beyond chat interfaces and become reliable tools for building software.
Education
- Carnegie Mellon University — M.S. in Artificial Intelligence and Innovation, 2023
- University of Cambridge — B.A. Bioengineering, M.Eng. Computer and Information Engineering, 2021