I am completing a PhD in Quantum Chemistry at Rutgers University, where I have developed a massively parallel simulation package to predict the electronic structure of molecules and solids.
I am a self-starter, if a project sparks my interest I will just dive into it, no matter how difficult it might be. This attitude led me to aquire a wide range of skills in software development.
I have developed efficient scientific software intended to run on the most powerful supercomputers, backend code to perform statistical analysis in the cloud, and well designed apps for mobile devices.
I developed a custom cloud and stats solution for the In/Out tennis consumer device.
My software is designed to be in charge of uploading, storing, and analyzing hundreds of thousands of shots recorded by this highly anticipated device.
I created the Zest Journal and its dark side, the RagePad.
On the surface these apps are simple and fun to use, under the hood they are a technical jewel.
Embedded Quantum Espresso (eQE) is an open source extension of the popular Quantum Espresso package. Its development has been led by me during my academic career as a Quantum Chemistry PhD student @ the Pavanello Research Group.
Utilizing a divide and conquer approach for the determination of the electronic structure, eQE is extremely fast and highly parallelized.
PbcPy is an open source Python package that provides abstraction layers to remove the frustration of working with physical systems under periodic boundary conditions.
PbcPy good design and semplicity makes it a great option for other reserchers to build on.
I build this simple app for the fourth and final step of the screening processo to get admitted to the Toptal freelance network (I did).
The app itself is nothing special, a RESTful API in the backend with user authentication, and a client to access it. To make the challenge a little more fun, I decided to build the app with a framework I was unfamiliar with: React Native + Redux.
I enjoyed working with React, and I will probably use it as a fundation for my next projects.
The Sony Smart Tennis Sensor is quite accurate and records a lot of data while you play. However, I was unsatisfied with the way Sony was presenting the statistics, so I decided to build my own system.
What started as a few core Python routines, quickly evolved into a complex interactive website with an appealing interface. Unfortunately, I didn't have time to spend on it after starting to work on the In/Out Tennis project above, and the website has since been taken offline.
TenniShots has a series of advanced features: