Machine Learning & Data Mining

 The code to extract the publicly available databases and to calculate the topological features for the graph databases is here.
 The code to cleanse and organize the data is here.
 The code to perform the machine learning for many (supervised and unsupervised) methods is here.
 A talk about the project is here. The first draft of the paper is here.

 Material from the graduate course at Stony Brook University. The source code for the homework is here, with many algorithms in Python/NumPy comparing
NaiveBayes vs. Logistic Regression, performing
Adaboost, and comparing
kNN vs. SVM.
 My theoretical homework, from the entire course, is here.

Information Diffusion in Twitter
A very introductory essay about graphs and information diffusion in social network, under supervision of Prof. K. Mueller. Simple examples of highdimensional space parameterizing each tweet to capture the information diffusion and graph layout.

Data Analysis in Astronomy (IDL)
Data extraction, calibration, and cleansing for astrophysical images for photometry and spectroscopy:

On the Spectroscopy Study of the Earthshine Spectra:
report
and source code.

On the Calculation of the Angular Diameter of the Sun by Michelson Radio Interferometer:
report and source code.
 On the Measurement of Stellar Fluxes on the Interstellar Dust Extinction of M35:
report and source code.