- I developed a plan for the release of our flagship software almost from scratch. This included identifying potential customers through face to face meetings, fieldwork and social media research. - I developed a quantitative model on the possible profitability of our market niche. - For social media research I used Natural Language Processing with Python in order to identify key phrases and sentiment. - I learned some of the basics of trading.

• I studied neutron stars to find out whether their interiors have exotic forms of materials never seen before on Earth, such as pure quark matter. This work led to the following achievements:• I have analyzed data sets as large as ∼ 500 MB using some of Python’s data science such as numpy, scipy, matplotlib, and pandas, in the context of very multidimensional data (as much as 36 relevantfeatures).• I created and maintained a relational database to consolidate my simulation data that was originally stored in tens of thousands of CSV files. I used Python to extract, upload, and plot database data.• I have developed forecasting models in the context of astrophysics, where (based on past observational data) I came up with models that predicted future observations, which entailed using regression models, hypothesis testing, and even sophisticated Bayesian statistics.• I developed a parallelized, machine learning code using MPI that implements Bayesian statistics to choose the best model suitable to empirical data (in this case astrophysical neutrinos) in ordertoforecast future signals.• I was lead developer of Burn-UD, a hydrodynamic, multiphysics combustion code that follows the burning of a nuclear matterto quark matter. I wrote tens of thousands of lines of code in Java and Python.• I gave 9+ talks in international conferences. I had seven articles published in peer reviewed journals. I was first author of five of these

I supervise and deliver pedagogical excersizes/and experiments, to help students learn physics.

- I wrote algorithm in C++ to calibrate particle detectors at FermiLab, in particular, to filter out the noise caused by electrons in these detectors. I also used ROOT, a C++ framework for data analysis in the context of particle physics.