Summary
Wayne Chi is a Doctoral Candidate at CMU and an Applied Scientist at AWS with 11 years of experience building and researching production-grade AI systems spanning generative modeling, speech/NLP, and automated planning and scheduling. He has driven latency and launch improvements by redesigning core ML orchestration backends at AWS and productionized NER, entity linking, and deep metric learning models for Health AI. Previously at NASA JPL he prototyped the Mars 2020 onboard planner, developed probabilistic execution simulations and novel scheduler search algorithms that informed ICAPS publications. His work bridges rigorous research—multiple conference publications and patents in music generation—with hands-on systems engineering across C++, Java, Python, and distributed services. Wayne holds an M.S. and dual B.S. in Computer Science and Business Administration and is pursuing a PhD, combining academic depth with measurable impact in high-stakes aerospace and cloud environments. An interesting through-line: he moves seamlessly between creating novel ML models and engineering the infrastructure that makes them robust in production.
11 years of coding experience
6 years of employment as a software developer
Master’s Degree, Computer Science, Master’s Degree, Computer Science at University of Southern California
IBSH
English, Chinese