Curriculum Vitae
Professional Experience
Senior Machine Learning Researcher
ASML, Veldhoven, The Netherlands
2022 – Present
- Develop machine learning models for semiconductor metrology and defect inspection
- Research interpretable AI and uncertainty quantification for industrial applications
- Mentor MSc and PhD students in collaboration with Dutch universities
Postdoctoral Researcher
TU Berlin, Berlin, Germany
2021 – 2022
- Enhanced interpretability of AI models using information-theoretic frameworks
- Developed methods for transparent ML in scientific contexts
Postdoctoral Researcher
University of São Paulo, São Carlos, Brazil
2018 – 2021
- Developed ML models to predict materials properties
- Created MeLIME, a Python package for model interpretability
Postdoctoral Researcher
UC Berkeley, Berkeley, USA
2017 – 2018
- Developed text-mined materials databases
- Built graph-based thermodynamic models for inorganic synthesis pathways
Education
Ph.D. in Physics
Universidade Estadual de Campinas (UNICAMP), Brazil
2012 – 2016
Best Ph.D. Thesis Award (2017)
Atomistic Simulation of Two-Dimensional Materials: Silicene, Graphene and Carbon Nitrides
Investigated mechanical, thermal, and electronic properties of 2D materials using DFT, DFTB, and ReaxFF-MD.
Skills: DFT, DFTB, ReaxFF, MD, ab initio thermodynamics, HPC, algorithm development
M.Sc. in Physics
UNESP, Brazil
2010 – 2012
Development of Computational Models using Cellular Automata and the Monte Carlo Method.
B.Sc. in Physics
UNESP, Brazil
2006 – 2010
Modeling disease propagation using Monte Carlo simulations.
Research Interests
- Physics-Informed Machine Learning
- Uncertainty Quantification
- Interpretable & Trustworthy AI
- Semiconductor Metrology
- Defect Inspection
- Computational Materials Science
- Hybrid Modeling
- Inverse Problems
Technical Skills
Machine Learning
- Neural Networks & Deep Learning
- Physics-Informed Neural Networks
- Uncertainty Quantification
- Model Interpretability
- Computer Vision
Scientific Computing
- Python (PyTorch, TensorFlow, NumPy)
- Computational Physics
- Molecular Dynamics
- Density Functional Theory
- High-Performance Computing
Output
- 10 patent applications filed (2024–2025)
- 30+ peer-reviewed publications (2011–2025)
- Co-supervision of MSc and PhD students with TU/e and Leiden University