Madrid, Community of Madrid, Spain
• Data exploration and experimentation • Predictive modelling of tabular / structured data using the tools of machine learning • Proof of concept (PoC) prototype models • regression techniques with conformal prediction intervals, well calibrated classification I am open to working on scientific datasets as well as business data, building either simple, robust and explainable models, or performant models aimed at getting the very best out of your data. Prior to solving data science problems I worked as an academic researcher in the physical sciences, with 20 years of experience in the field of computer simulation of liquids using the molecular dynamics and Monte Carlo techniques. I have co-authored over 40 scientific publications (h-index=24).
Predictive modeling using TabPFN
asignaturas / subjects: • aprendizaje automático / machine learning • inteligencia artificial / artificial intelligence
SMLC is a new initiative whose objective is to facilitate the incorporation or refinement of high performance predictive machine learning models in scientific works. Bespoke data modeling solutions to produce publication quality results.
* Predictive modelling of tabular / structured data using the tools of machine learning * Experimental, development, proof of concept (PoC) and prototype models * EDA, visualization, feature selection, feature engineering and analysis
CESTE, Escuela Internacional de Negocios (Centro Universitario)
Predictive modelling of pulmonary capillary wedge pressure (PCWP) from clinical data.
I have contributed over 200 notebooks to the kaggle community. I have also won three competition medals, and hosted over 25 Community competitions.