Welcome!
I am a research scientist with more than 10 years of experience in advanced statistical theories for geosciences. I am the author and lead developer of the GeoStats.jl project, as well as various other open source projects that are widely used by geoscientists around the world.
My career goals include:
- Advancing the field of machine learning and artificial intelligence to account for challenges that are unique to the geosciences
- Establishing new methodologies for uncertainty quantification and decision making involving the use of natural resources in the planet
To achieve these goals, I’ve founded Arpeggeo®, a software company that offers consulting services and high-performance products designed with extensive scientific research.
In this website, I plan to highlight some of the projects that I am working on, and share what I am learning as blog posts. Feel free to follow my post updates in your RSS feed reader using the link at the bottom of this page.
Work experience
- [2022–present] Chief Executive Officer, Arpeggeo®, Rio de Janeiro, BRA.
- [2025–2026] Postdoctoral Fellow, UFRJ, Rio de Janeiro, BRA.
- [2021–2022] Postdoctoral Fellow, IMPA, Rio de Janeiro, BRA.
- [2018–2020] Research Scientist, IBM Research, Rio de Janeiro, BRA.
- [2017] Teaching Assistant, Stanford University, California, USA.
- [2016] Summer Intern, Landmark Solutions, Texas, USA.
Education
- [2014–2018] Stanford University Ph.D., Geostatistics
- Thesis: Morphodynamic Analysis and Statistical Synthesis of Geomorphic Data: Application to a Flume Experiment
- [2011–2014] UFPE M.Eng., Civil Engineering
- Dissertation: The Inverse Problem of History Matching
- [2007–2011] UFPE B.Eng., Mechanical Engineering
- Course project: A 3D Finite Element Analysis Solver
Awards
- [2022] Frontiers in Applied Mathematics and Statistics Award
- [2021] IMPA Fellowship
- [2018] Syvitski Modeler Award
- [2013] SwB Scholarship
- [2012] PRH-26/Petrobras Scholarship
- [2007] PRH-26/ANP Scholarship