Summary
Claudio Spiess is a PhD candidate and graduate student researcher at UC Davis with nine years of software and machine learning experience focused on ML for software engineering (ML4SE). He has led empirical research into LLM calibration for code tasks and crafted datasets and models for program synthesis, code retrieval, and code similarity, with first-author publications at ICSE'25 and FSE'23 SRC. Claudio combines deep-learning engineering (PyTorch, HuggingFace, Accelerate) with strong data-analysis skills (Pandas, scikit-learn, NumPy) and production experience deploying ML services and observability tooling on AWS and GCP. Earlier roles as a software engineer and intern sharpened his full-stack instincts—building Rails/React apps, REST APIs, and visualization tools for embeddings—while also reducing technical debt at scale. He blends rigorous academic methodology with production-minded solutions and a knack for turning dynamic analysis artifacts into practical code-retrieval systems.
9 years of coding experience
2 years of employment as a software developer
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at University of California, Davis
Bachelor of Science - BS, Computer Science, 3.85/4.0, Bachelor of Science - BS, Computer Science, 3.85/4.0 at College of Charleston
Bachelor's degree, Computer Science, 94.55/100, Bachelor's degree, Computer Science, 94.55/100 at Free University of Bozen-Bolzano
German, English, French, Dutch, Italian, Spanish