Graduated in Technical Engineer in Computer Systems (2010) and Telecommunications (2012), I was born in Barcelona, 1987. Known as a responsible and hard-worker IT professional by the companies I have worked for, my main interests are Mobile Apps.
Architectural design and development of Zyncro Messenger iOS application: a private instant messaging app similar to WhatsApp or Telegram for companies. Working with SCRUM, using technologies such as XMPP, Socket.IO, CoreData, ReactiveCocoa (Functional Reactive Programming), Mantle, CocoaPods, and Git, among others.
Continuous delivery and continuous integration: Fastlane and Jenkins respectively.
Architectural design and development of Couplace iOS/Android application: a private instant messaging app for couples. Using technologies such as XMPP(ejabberd), CoreData, CocoaPods, Smack, Volley and Git, among others.
The app offered a list of different plans, shared calendar to annotate important dates, private gallery and the social part to follow another couples and see a wall with the items shares like photos, videos, events, etc.
With the main goal of promoting new trends in the digital banking sector, I developed a mobile application able to detect those nearest mobile phone devices in order to make possible to proceed with transferences among them in a quick, comfortable an secure way. We added a security layer that enabled the validation of the operations from the smartwatch.
Techinical OAuth 2.0 and Banc Sabadell Api knowledge acquired to proceed with the requirements of the competitions.
- Design and Development of a web App.
- Design and Development of an iOS mobile App for iPhone and iPad.
The Goal of the Project: Detection and prediction of abnormal physical activities over people who have some dependency needs (old people or disabled people) through Machine Learning techniques adapted to Smartphone.
The Project was focused on a first data collecting received from the mobile device accelerometer and its further data sending to a server. This server was the one which detected the activity by the user registered trough Machine Learning.
While developing this project, the research team opted for a new concept based on teleassistance technologies which enables users to monitor the physical activity of other people. (The registered developed activities were the following: walking, running, getting up, sitting down, standing, falling down and lying)
This way, the app enables family members and caregivers to detect abnormal behaviors of the user who has the mobile device through alarms which are received via computer and personal mobile. .
- Responsible for computers and servers maintenance.
- Responsible for network maintenance.
- Logistic support