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For any of the below resources, please contact me in case you require any further details or clarification.

Selected Projects and Presentations

• Data Science
  • Analysis of Smoking Hazard and Socioethnographic Factors Influencing Smoking in the American Youth (Report)
  • Study of uptake rate of cigarette smoking, as well as risk of consuming other tobacco products, in a representative sample of American teenagers, surveyed throughout all states.
  • Bayesian Modelling of Data Correlated in Time and Space (Report)
  • Harnessing the INLA framework to fit a semi-parametric temporal model to examine CO2 emissions, and a spatial correlation model to examine the usefulness of satellite data in the study of Malaria incidence in Africa.
  • Fresh Over Rotten: The Value of a Critic's Pick in Hollywood (Report) (Presentation)
  • Study of how critical perception in Hollywood movies can translate to revenue differences, based on different features
• Machine Learning
  • Attention-based Implementations of RNNs for Machine Translation Task (iPython Notebook)
  • Implementation of several attention-based architectures to solve a straightforward machine translation task, with a discussion of their merits and short-comings.
  • Exploration of the Model-Agnostic Meta Learning (MAML) Algorithm in a Regression Setting (iPython Notebook)
  • Fascinating algorithm which allows for straightforward transfer learning (task-to-task adaptation) with the only requirement being a model trainable by gradient descent.
  • MNIST Handwritten Digit Classification Problem *N<P* using MCMC (Report)
  • We use MCMC to overcome one of the most challenging hurdles in machine learning with reasonable success: When the number of your training cases is less than the number of parameters to be estimated.
• Probabilistic (Monte Carlo) Computation
  • Bayesian Hierarchical Inference using Metropolis and Gibbs Sampling Algorithms (Report)
  • Fitting a Bayesian hierarchical model with fundamental MCMC algorithms to determine production differentials, studying the chain's convergence rate and properties
  • Implementations of an LCG Pseudorandom Generator, and Importance and Rejection Samplers (Report)
  • Exploration of probabilistic computation and pseudo-randomness

Professional

• Subject Matter Knowledge
  • One Page Introduction to Prime Brokerage

Preferred Quick Guides

• Data Wrangling with tidyr and dplyr (R)
• Great LaTeX Cheatsheet
• Official RMarkdown Cheatsheet (R)
• Machine Learning Digest (Domingos)

Media Presence and Features

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