Engineering Consulting Projects

This section contains a non-exhaustive list of Statistics consulting projects I worked on which subject matter relates to the field of engineering. A link to the final project outcome is provided when the client allows for it.

Analysis of Crew Members Performance in NASA BASALT Mars Simulations.
August 2016 -- May 2019 · Industrial Engineering R | SAS
  • Analysis of astraunots live physiological monitoring data and performance obtained during extravehicular activity (EVA) in BASALT Mars simulations .
  • Built numerous non-parametric models for evaluating crew health and performance and comparing crew physiological data distributions.
  • Assisted client with data preprocessing, code writting for models, results interpratation and report.

Quantifying Insurance Providers Network Graphs Effect on Patient Data
January 2017 -- May 2019 · Industrial Engineering R | SAS | SQL
  • Analysis of a 5.5 years longitudinal health claim data trough a provider/patient social network analysis.
  • Investigated the effect of providers network graphs measures (degree, centrality and betweeness) on very sparse patient level count data.
  • Modelled the provider network graph effects using a zero inflated Poisson model.
  • Established the covariance structure of the various models through a Generalized Estimating Equation (GEE) method to caputure the depentence between patients in the same network clusters.
  • Used boostrap method to compute confidence region of various statistics.
  • Assisted client with code writting for models and results interpretation and reporting.

Disease Status Prediction and Growth Trend of Abdominal Aortic Aneurysms
August 2017 -- May 2018 · Biomedical Engineering R | SAS
  • Used high frequency ultrasound aneurysm data to develop prediction models of both aneurysm formation and growth trend.
  • Used a quadratic discriminant analysis and logistic regression to build two statistical models to predict disease status.
  • Validated model performance through leave one out cross validation prediction accuracy, ROC curve, specifcity and sensitivity analysis.

Engineering Teamwork Ratings Quality Assessment
August 2016 -- May 2018 · Engineering Education R | SAS
  • Developed metrics and statistical methods for accessing the quality of ratings data generated by the CATME system.
  • Built tools for automating data cleaning and analysis in SAS and R and created instruction manuals to help CATME system users run analyses independently.
  • Run live demo of new method for CATME users from different countries.
  • New tools are to be integrated into the CATME system which is currently deployed to more than 1 million users from 80 countries.
Hilda Ibriga
Hilda Ibriga
Ph.D student in Satistics and Machine Learning

My research interests include the theoretical analysis of tensors and their application to machine learning. I have also worked on applied projects in reinforcement learning for some years and have 3 years of work experience as a statistics consultant.