Developed a cross-platform mobile and web application using React Native with Expo SDK and Javascript. Implemented authentication with selfie and email using Amazon AWS Image Recognition. Built responsive and intuitive UI ensuring consistent user interface across different platforms with intuitive navigation. Managed Android and iOS mobile emulators for testing and debugging. Integrated proprietary and third party APIs with secure communication to handle authentication, data validation and user registration. Launched applications on Play Store and App Store, and deployed Web version with AWS hosting services. Monitored app to continuously improve stability and incorporate feedback from testers and users. Applied DRY principles of software development. Maintained and versioned code using Github.

Digital analysis of bills in circulation.

In this work, a novel multi-shell modelling method is proposed to compute fascicle-based fractional anisotropy (FA) that is shown accurate and robust in the centrum semiovale of human brain clinical multi-shell datasets. It does not require tractography and it is informed by the local modelling estimations provided by the method called MRDS. The effectiveness of our methodology is also shown on synthetic experiments.

Facilitating laboratory exercises, conducting assistantship classes, and providing support in reviewing homework, exams, and final projects.

Brain tractography allows estimating in vivo long-range connections between groups of neurons. However, it is well known there is a huge amount of false-positive connections in the estimators that are represented as 3D streamlines. The COMMIT framework allows reducing those false positives, however the required computational time may become very long due to the, usually, huge number of streamlines per brain-volume, and the need to process thousands of brain images to increase the statistical power of current medical studies. In this work, we provide a programming model to parallelize the COMMIT framework on the CUDA language framework. Our results demonstrate that it is possible to reduce the computational burden by one order of magnitude by using this proposal.

Application that shows current university cultural events using Instagram-like stories. Development was made in Java and XML. Administrators were able to upload the stories using a Dropbox-like web page developed in PHP. Server maintains all the information in a SQL database and sends data to the application using Json files. App is maintained on Github.

Development of a cubemap blending feature for multi-scene static lightning for the LodeStone virtual reality graphics engine using C++ and OpenGL. The LodeStone engine allows multi-platform development of VR games supporting Windows, MacOS and Linux.