Hello There
I'm Felipe Jiménez

I'm a Software Engineer. I'm passionate about building software that improves people's lives.

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Android app that shows nutritional and environmental impact information about a given food by scanning its barcode. It also helps the user reach their fitness goals while also incentivizing them to pick foods that are environmentally friendlier. We developed this MVP for IBM's Call For Code Hackathon, we were regional finalists.

  • Kotlin
  • Android
  • Firebase
  • IBM Speech to Text


Chilean supermarkets price comparer. It allows users to compare prices and see the price-history of the products in the 4 biggest supermarket chains in Chile. The final idea is having an independent project that uses the data to catch market trends and detect price-fixing cartels automatically

  • Django
  • MySQL
  • Python
  • Selenium
  • HTML
  • CSS
  • Bootstrap
  • JavaScript

Ficha Facil

Translates to 'Easy medical records', it allows users to own their medical records and to share them with their doctors, . This MVP includes user login/registration, saving medical records, registering symptoms and chatting with their doctors (if both patient and doctor agree). We developed it for NTT Data's Hack the Challenge Hackathon.

  • Kotlin
  • Firebase

Python Image Processing

Does image processing both using no external libraries (through understanding the methods and modifying the pixels directly) and also with OpenCV. It includes gray scale methods, histogram equalization, thresholding, ROI extraction and patterns recognition. Everything is documented through guides

  • Python
  • WxPython
  • Pandas
  • OpenCV

Data Science

Differential Privacy concepts and real world applications

Differential privacy is a framework that allows us to share general information about a dataset, while keeping the individual's data in it private. DP introduces the riguours mathematical measurement of privacy loss. Companies like Google, Microsoft and Apple are using DP to share information about their users without compromising their privacy.


  • Differential Privacy
  • Data Science
  • Machine Learning

Comparing vanilla and differentially private Neural Networks

This article shows how to train neural networks both with and without differential privacy. We process the data appropiately and create the neural networks using TensorFlow and Keras. We then compare the results of the models in terms of accuracy and epsilon.


  • Differential Privacy
  • Data Science
  • Pandas
  • Tensorflow
  • Tensorflow Privacy


I have built mobile and web applications using the following frameworks, tools and languages:

  • Front-End

    HTML and CSS
    Vanilla Javascript

  • Back-End

    Django and Laravel
    PostgreSQL and MySQL

  • Mobile development

    Java and Kotlin
    Android Studio
    Android's XML


I'm a Chilean Software Engineer with professional experience in Django, MySQL, and PostgreSQL for backend development, and React for frontend. I'm constantly learning and have worked on projects using Next.js, Kotlin, Firebase, Unity, and Godot. I'm adaptable to new technologies and a supportive team member.

I like science fiction books, VR Games and fitness.

Sometimes I participate in hackathons and game jams.