Summary
Natasha Jeppu is an Applied Scientist II at AWS with a decade-long focus on automated reasoning, formal verification, automata learning and program synthesis, grounded in a PhD from the University of Oxford. She has built scalable model-learning pipelines from execution traces to reason about system correctness and safety, and has contributed to tooling such as CBMC while identifying proof-runtime optimisations. Her background includes applied verification work for embedded and automotive systems at MathWorks and TUM, reflecting an ability to move formal methods from research into practical toolchains. Based in the UK, she combines deep theory with hands-on engineering at scale and is actively seeking industry opportunities to embed formal methods into production systems. An inquisitive explorer of formal methods, she describes herself on GitHub simply as a "Formal Methods Explorer," signalling a continual curiosity beyond conventional verification roles.
10 years of coding experience
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at University of Oxford
High School, High School at National Public School
Bachelor of Technology - BTech, Computer Science, Bachelor of Technology - BTech, Computer Science at National Institute of Technology Karnataka