Chemistry Analytics consultant. Evaluation and interpretation of complex data problems to support data-driven decisions. Specialties: Machine learning, multivariate statistics, quality control (QC), spectroscopy, process monitoring, anomaly detection, design of experiment (DOE) and signal processing.

• Lead the development and implementation of an on-line optical spectroscopy systems for the monitoring of raw and production material, while leading a multidisciplinary research teams from proof-of-principle to production deployment. • Lead the evaluation and modification of a stablished QC SOP in a production environment and achieved a 200-fold time reduction, a ~$0.6M/year in QC cost savings, in compliance with regulations. • Lead the development and implementation of an “anecdotal” QC colorimetric visual cue in the production environment into a quantitative and measurable, by optical spectroscopy, metric with a gage R&R under 15%. • Developed Machine Learning models for the determination of Food Doneness during the cooking process the technology was patented and transferred to the business. • Developed robust chemometric models and calibration strategies for the elemental quantification of mineral cores using LIBS. • Developed robust analytical strategies for the rapid determination of acetate in hyperpolarized solutions for molecular imaging.• Developed robust chemometric models based on spectrophotometric methods for the quantification of seasoning content in potato chips. • Work in multidisciplinary research teams as client-facing analytics and chemometrics subject matter expert with focus on analytical methods and instrumentation for quality control. • Work in multidisciplinary research teams with focus on analytical methods and instrumentation. • Sensing materials research and development. Specialties include hands-on sensor and materials testing, evaluation, and characterization using SixSigma-DFSS approaches for DOE. • Extensive experience with chemometrics implemented on classification, data visualization, signal processing, and multivariate analysis such as, principal components analysis, linear discriminant analysis, classical and partial least squares, hierarchical clustering analysis, neural networks, support vector machines and others.

Infochemistry and InfoBiologySingle Molecule Detection and Single Cell Analysis

Preparation and characterization of attoreactorsHigh density arrays of attosensor

Design of materials for optical and electro-optical sensing of ionsRational design of sensor arrays for detection of ions