Hello everyone :)
About
Holding a PhD in Physics with a strong focus on machine learning, simulation, and statistical data analysis, and a Master's degree in Physics with a minor in Mathematics, I have 5 years of experience in developing software in Python within international teams of scientists.
My achievements include:
- engineering machine learning models for signal detection, with contributions recognized in top-tier journals,
- designing, implementing, and deploying an open-source data-visualization package in Python,
- leading a team of scientists to evaluate the performance of a particle detector.
Links
Talks
- C. Praz and T. Fillinger, Plothist: visualize and compare data in a scalable way and a beautiful style , Python in High Energy Physics, 2024.
- C. Praz (on behalf of the Belle II collaboration), Electroweak penguins and radiative B decays at Belle II , Electroweak session of the 57th Rencontres de Moriond, La Thuile, Italy, 2023.
- C. Praz, Search for B→Kνν decays with a machine learning method at the Belle II experiment , PhD defense, Hamburg, Germany, 2022.
- C. Praz (on behalf of the Belle II collaboration), Search for the rare decay B→Kνν in the early Belle II dataset , Phenomenology Symposium, Pittsburgh, US, 2021.
- C. Praz (on behalf of the Belle II collaboration), Search for B→K(star)νν at Belle II with machine learning techniques , Deutsche Physikalische Gesellschaft Spring Meeting, Dortmund, Germany, 2021.
- C. Praz (on behalf of the Belle II collaboration), Tracking performance and interaction point properties at Belle II , 29th International Workshop on Vertex Detectors, Tsukuba, Japan, 2020.
- C. Praz (on behalf of the Belle II collaboration), B lifetimes at Belle II , 40th International Conference on High Energy Physics, Prague, Czech Republic, 2020.
Certifications
- Stanford Course on Graph Search, Shortest Paths, and Data Structures , Feb 2025.
- Stanford Course on Divide and Conquer, Sorting and Searching, and Randomized Algorithms , Jan 2025.
- Google Introduction to Docker , Oct 2024.
- IBM Introduction to Cloud Computing , Jul 2024.
- IBM Introduction to DevOps , Jul 2024.
- DevOps, Cloud, and Agile Foundations , Jun 2024.
- Developing Applications in Python on AWS , Apr 2024.
- IBM Introduction to Agile Development and Scrum , Apr 2024.
- Machine Learning with Apache Spark , Apr 2024.
- SQL for Data Science , Mar 2024.
- Machine Learning in High-Energy Physics, Jul 2020.