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João Filgueiras

João Filgueiras

Porto, Portugal
Member since February 22, 2014
João is an accomplished researcher and prototype developer with a special talent for breaking down large problems into solvable pieces. His background in R&D gives him the edge in implementing efficient, effective, and sophisticated yet clean solutions.
João is now available for hire
  • JavaScript, 7 years
  • Highcharts JS, 4 years
  • MongoDB, 3 years
  • Node.js, 3 years
  • Data Visualization, 3 years
  • Machine Learning (ML), 2 years
  • Vue.js, 1 year
  • ES6, 1 year
Porto, Portugal
Preferred Environment
Linux, Atom, Git
The most amazing...
...thing I've coded is a machine learning classifier to classify opinions in a text as positive/negative/neutral, and to infer personal attributes of its author.
  • Web Developer
    2016 - PRESENT
    • Implemented a web-based business process management system that allows management, visualization, and reporting of business processes and supporting documents.
    • Developed the front-end using ES6 and Vue.js 2.x with a focus on component re-usability.
    • Used Node.js and MongoDB for the back-end.
    • Built complex data models with MongoDB, including tree structures.
    • Integrated and customized a BPMN diagram editor.
    Technologies: Vue.js, Node.js, MongoDB, HTML5, CSS3
  • Full-stack Developer
    Agri-Esprit, SA
    2014 - PRESENT
    • Developed multiple front-end pages using JavaScript with the Maria MVC framework.
    • Developed a library to display notifications and alerts from a server on certain pages according to categories using WebSockets.
    • Evaluated a big data storage and data mining tool to work with massive collections of data in the domain of large-scale agriculture.
    • Implemented a framework for web front-end testing using CasperJS, specific to the company's software product.
    • Worked on data visualizations and a process management editor using the BPMN notation.
    Technologies: JavaScript, Node.js, CasperJS, jQuery
  • Data Scientist/Data Visualization Expert
    2014 - 2014
    • Implemented data processing and visualization tools for advanced pattern finding in financial market data using HighCharts and JavaScript on a web app.
    • Created several data visualizations for financial market data on a web app using HighCharts and JavaScript.
    • Implemented a fully featured graphical widget to allow a user to build a logical query by wiring a given list of base conditions and logical nodes such as AND/OR, using just basic SVG shapes and D3.js.
    • Implemented interactions with several different APIs to build interactive front-end sections of the web app.
    • Implemented a Python application to explore and analyze pattern data.
    Technologies: JavaScript, D3.js, HighCharts, DC.js, Python
  • Researcher/PhD Student
    2012 - 2014
    • Developed a state-of-the-art machine learning approach to sentiment analysis using Python and Sklearn.
    • Developed of a web page for data visualization and dissemination using PHP, jQuery, and HighCharts.
    • Created a state-of-the-art machine learning-based approach to infer demographic attributes of the author of a given text using Python and Sklearn.
    • Co-developed a webpage to showcase different text-mining tools using Python, Bootstrap, jQuery, and D3.js.
    • Co-developed rich data visualizations for interconnected political mandates using D3.js.
    Technologies: Python, Machine Learning, PHP, jQuery, D3.js
  • Undergraduate Researcher
    IT Porto (via Carnegie Mellon University - Portugal Programme)
    2009 - 2012
    • Developed a C/Python application to perform and log Bluetooth discoveries.
    • Created data analysis tools for Bluetooth data using Python.
    • Planned a city-wide deployment of Bluetooth traffic scanners.
    • Developed a server-side application to receive and store remote Bluetooth logs using PHP.
    • Developed web-based tools for data visualization of geographic data using Google Maps, PHP, and JavaScript.
    Technologies: C, Python, PHP, Bluetooth, JavaScript, Google Maps
  • Accrue WebApp (Development)

    Developed data visualizations, filters and front-end data processing for a sophisticated and innovative webapp that allows the user to look for patterns and trends in financial market data. This project required heavy knowledge of Highcharts/Highstock, DC.JS, Crossfilter, D3.JS, jQuery and Python for auxiliary tools.

  • POPSTAR Website (Development)

    Developed and co-designed the POPSTAR website showing the trends of the Portuguese public opinion on politics. The website was developed using PHP, jQuery, and heavily customized Highcharts.

  • Author Profiling Classifier (Development)

    Developed a machine learning classifier that, using solely the features of a given text, predicts the gender, age group and political affiliation of its author. This was also developed within the text classification framework using Python and scikit-learn.

  • Sentiment Analysis Classifier (Development)

    Developed a sentiment analysis classifier (i.e. given a text determine whether it expresses a positive, neutral, or negative opinion) that ranked 3rd in a scientific competition with over 40 participants. It was implemented using Python and scikit-learn.

  • Text Classification Framework (Development)

    Developed a text classification platform in Python containing several thousand lines of code implementing a variety of state-of-the-art algorithms to parse, pre-process, extract features, and train machine learning classifiers from textual documents.

  • BlueMiner - Bluetooth Data Analysis Tool (Development)

    Developed an analytics tool that takes BlueDiscovery logs and aggregates data reporting origin/destination matrices, speed, volume, and Bluetooth device types. It was developed in Python using a PostgreSQL database.

  • BlueDiscovery - Bluetooth Monitoring Tool (Development)

    Implemented BlueDiscovery, a Bluetooth monitoring tool that constantly performs and logs Bluetooth discoveries. This tool was used in a city-wide network of sensors to capture Bluetooth devices in cars and infer the traffic speed and volume. It was developed in C.

  • Languages
    ES6, JavaScript, Python, TypeScript
  • Frameworks
    Express.js, Bootstrap, Angular
  • Libraries/APIs
    jQuery, Node.js, Vue.js, Highcharts JS, DHTMLX, D3.js, jQuery UI, Scikit-learn, Raphaël, DC.js, Crossfilter
  • Tools
    Mongoose, Git, JIRA, Atom, Apache Solr, Emacs, CasperJS, PhantomJS
  • Paradigms
    Data Science, Imperative programming, Object-oriented Programming (OOP)
  • Misc
    Data Visualization, AJAX, Machine Learning (ML), BlueZ
  • Platforms
  • Storage
    MongoDB, MySQL, PostgreSQL
  • Master's degree in Computer Science
    University of Porto (Faculty of Sciences) - Oporto, Portugal
    2005 - 2012
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