I'm a PhD candidate in Computer Science at the University of California, Davis. My work revolves around applying machine learning techniques, especially from the natural language processing community, to software engineering problems.
🧠 Expertise: Machine Learning, Research, Python, ML4SE, AI4Code
🔗 [Personal website] - [LinkedIn]
🎓 Education
- PhD Candidate in Computer Science, Advised by Prem Devanbu at University of California, Davis (Dec. 2026)
- Bachelor in Computer Science & Engineering at Free University of Bozen-Bolzano (Sep. 2019)
- Computer Science Study Abroad at College of Charleston (Dec. 2017)
👨💻 Experience
- Research Scientist Intern at IBM Research
- Researched language model programming and automated prompt program optimization, resulting in AutoPDL system. Published AutoML'25 (1st author).
- Graduate Student Researcher at UC Davis
- Investigated confidence vs correctness (calibration) of LLMs for code eg GPT3.5 in program synthesis, line completion, and defect detection tasks. Built dataset of Python functions for prompting & evaluating model completions. Published ICSE'25 (1st author).
- Designed and trained custom HuggingFace/PyTorch BERT model for embedding dynamic analysis artifacts for source code retrieval using FAISS and evaluated performance. Built dataset of open source projects under instrumentation. MS Thesis. Published FSE'23 SRC (1st author).
- Teaching: ECS 160 Software Engineering, ECS 171 Machine Learning: Held discussion section & office hours, produced & graded homework, proctored & graded exam, answered student questions on discussion forum
- Machine Learning Intern at Overstock
- Built & deployed Streamlit app to analyze embedding spaces used in product recommender systems.
- Designed & implemented 3 core features: nearest neighbor visualizations, linear & classification probes, and catalog coverage analysis for recommender systems ML team, optimizing their development and debugging workflow.
- Reduced time to evaluate product embeddings from approx. 1 day to 10 minutes, increasing engineering productivity
- Junior Software Engineer at Floryn BV
- Created system for monitoring ML model outputs & explaining decisions to non-technical stakeholders e.g. through the use of SHAP.
- Developed features & improvements on Ruby on Rails and React/TypeScript apps that managed over €185 million euros in outgoing loans at one of the Netherland's fastest growing startups with over €78 million in funding
🛠️ Skills
- Programming Languages: Python, Ruby, C, SQL (Postgres), Java, TypeScript
- Frameworks: PyTorch, Tensorflow, Flask/FastAPI, Rails, React, Node.js
- Developer Tools: Git, Docker, Terraform, AWS, CircleCI, VS Code
- Libraries: pandas, NumPy, Huggingface, Matplotlib, plotly