João Filgueiras, Developer in Porto, Portugal
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João Filgueiras

Verified Expert  in Engineering

Artificial Intelligence (AI) Developer

Location
Porto, Portugal
Toptal Member Since
July 8, 2014

João is an accomplished researcher, AI expert, and data scientist with a special talent for breaking down large problems into solvable pieces. His background both in R&D and the industry gives him the edge in implementing state-of-the-art solutions while keeping practicality in mind.

Portfolio

AI-Penguin
Artificial Intelligence (AI), Deep Learning, Machine Learning...
infraPLAN, LLC
React, JavaScript, Ruby, Deep Learning, Machine Learning, Flask, Jupyter...
Vexxit
Python, Artificial Intelligence (AI), Machine Learning, Algorithms, Pandas...

Experience

Availability

Part-time

Preferred Environment

Jupyter, Git, Linux, Visual Studio Code (VS Code)

The most amazing...

...thing I've coded lately is a generative AI model to aid in the ideation of new concepts for sportswear.

Work Experience

Lead AI Engineer

2023 - PRESENT
AI-Penguin
  • Led a small team of experts working on generative AI, data science, and other deep learning projects.
  • Developed state-of-the-art deep learning generative models in the context of fluid dynamics.
  • Built natural language processing models to extract meaningful information from unconventional data.
  • Explored practical applications of state-of-the-art large language models such as ChatGPT in different domains ranging from law to programming.
Technologies: Artificial Intelligence (AI), Deep Learning, Machine Learning, Generative Adversarial Networks (GANs), Python, Data Science, Natural Language Processing (NLP), Large Language Models (LLMs)

Senior Data Scientist

2020 - 2022
infraPLAN, LLC
  • Developed a module for ranking and predicting water main failures for a leading utility consultant firm in the US. The module uses a specialized deep-learning model that outperforms industry-standard classical statistics models.
  • Developed other supporting machine learning models to improve data cleaning and other data-related operations.
  • Integrated the module with an existing web platform based on Ruby on Rails with a React front end. Added additional functionality to the platform to support this integration.
Technologies: React, JavaScript, Ruby, Deep Learning, Machine Learning, Flask, Jupyter, Seaborn, Pandas, Python

Tech Lead

2020 - 2021
Vexxit
  • Conceptualized and developed an AI matching algorithm to suggest professionals, such as accountants and lawyers, to clients with specific needs.
  • Created the matching algorithm using machine learning and natural language processing to understand and compare information from profiles and requests.
  • Designed the system with continuous updates and extensibility in mind. It has since been improved and tweaked with minimal effort.
Technologies: Python, Artificial Intelligence (AI), Machine Learning, Algorithms, Pandas, Natural Language Processing (NLP), APIs, REST, REST APIs

Invited Assistant Professor

2019 - 2020
University of Porto
  • Co-lectured a course on Algorithm Analysis and Design for second-year undergrad students.
  • Prepared exam exercises and questions and then graded the final exams.
  • Supervised practical classes and graded practical projects.
Technologies: Algorithms

AI Researcher

2019 - 2020
Artificial Intelligence and Computer Science Laboratory – University of Porto
  • Worked on a public interest project with the aim to modernize and optimize government agencies using AI and data science.
  • Used NLP techniques to extract useful information from unstructured text.
  • Explored a large and complex public service dataset.
  • Worked on classification problems using machine learning techniques.
Technologies: Machine Learning, Generative Pre-trained Transformers (GPT), GPT, Natural Language Processing (NLP), Jupyter, Pandas, Python, Deep Learning

Senior Software Engineer

2018 - 2019
Undisclosed Fintech Company
  • Implemented automated trading strategies for cryptocurrency markets.
  • Designed the system architecture to ensure stability and fault tolerance.
  • Implemented custom data visualization pieces to support complex trading data analyses.
Technologies: Highcharts, React, Node.js, JavaScript

Technical Screener for AI and Data Science

2018 - 2019
Toptal, LLC
  • Interviewed potential AI and data science experts looking to join the Toptal network.
  • Mentored and trained other AI and data science screeners.
  • Contributed to the creation of the screening process and continuously refined it.
Technologies: Tools

Director of Engineering

2017 - 2018
Toptal, LLC
  • Performed a key operational role within the company, as part of a team, by understanding client requirements and matching them with the best talent in the network.
  • Helped shape and improve the operational processes of the company.
  • Co-developed and tested new screening processes and development specializations to ensure the highest standards of talent quality in new areas.
  • Managed several accounts for SMB and enterprise clients all over the world.
  • Supported and advised talent working with clients.
Technologies: Tools

Lead Web Developer

2016 - 2017
ThinkProcess
  • 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 ECMAScript (ES6) and Vue 2 focusing on component re-usability.
  • Used Node.js and MongoDB to serve complex data models, including tree structures.
Technologies: MongoDB, Node.js, Vue, JavaScript

Technical Screener

2015 - 2017
Toptal, LLC
  • Interviewed hundreds of applicants looking to join the Toptal network and ensured their technical skills, work ethic, and communication skills met Toptal's standards.
  • Mentored and trained many other technical screeners.
  • Contributed to the refinement and improvement of Toptal's industry-recognized screening process.
Technologies: Tools

Full-stack Developer | Data Scientist

2014 - 2017
Agri-Esprit, SA
  • Developed multiple front-end pages using JavaScript with the Maria MVC framework.
  • Implemented a framework for building complex agronomic models to evaluate crop status and recommend suitable actions.
  • 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: Pandas, Python, jQuery, CasperJS, Node.js, JavaScript

Data Scientist | Data Visualization Expert

2014 - 2014
nuOctave
  • 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.
  • Integrated a fully featured graphical widget to allow users to build a logical query by wiring a given list of base conditions and logical nodes, such as AND/OR, using 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: Python, DC.js, Highcharts, D3.js, JavaScript

Researcher | PhD Candidate

2012 - 2014
INESC-ID
  • Developed a state-of-the-art machine learning approach to sentiment analysis using Python and scikit-learn.
  • Developed 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 scikit-learn.
  • Co-developed a web page 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: D3.js, jQuery, PHP, Machine Learning, Python, MySQL

Undergraduate Researcher

2009 - 2012
IT Porto (via Carnegie Mellon University - Portugal Programme)
  • Worked on a project designed to collect and analyze vehicular traffic data based on Bluetooth devices.
  • Created data analysis tools for Bluetooth data using Python.
  • Planned a city-wide deployment of Bluetooth traffic scanners.
  • Created the collection application in Python/C and built the back end in PHP to receive and store remote Bluetooth logs.
  • Developed web-based tools for geographic data visualization using Google Maps, PHP, and JavaScript.
Technologies: Google Maps, JavaScript, Bluetooth, PHP, Python, C

Generative AI Models for Computational Fluid Dynamics

Worked on generative AI models to complement existing computational fluid dynamics simulation approaches. Used mainly generative adversarial networks and similar models for pure generation but also super-resolution.

Music Categorization System

Developed a commercial AI pipeline to assign songs to specific playlists according to their meta-data and musical attributes. This was a complex problem given the number of potential playlists (in the hundreds) and the difficulty of categorizing music. Several clustering and data-enrichment techniques were necessary.

Complaint Ranking System

Developed a system based on machine learning to prioritize and categorize complaints for the Portuguese Authority for Food Safety. Given the number of complaints versus available officers, the system allowed considerable resource allocation optimization.

Languages

Python, JavaScript, ECMAScript (ES6), Clojure, PHP, C, Ruby, TypeScript

Frameworks

Express.js, ClojureScript, Bootstrap, Flask, Angular

Libraries/APIs

Vue, Pandas, Node.js, jQuery, Highcharts, REST APIs, DHTMLX, Scikit-learn, D3.js, jQuery UI, React, PyTorch, NumPy, SpaCy, Google Maps, DC.js, Matplotlib, Raphaël, PhantomJS, Leaflet, SciPy, TensorFlow

Tools

Jupyter, Mongoose, Git, Reagent, Jira, Atom, Sequelize, IPython, Seaborn, CasperJS, Apache Solr

Paradigms

Data Science, REST, BPMN

Platforms

Visual Studio Code (VS Code), Linux

Other

Natural Language Processing (NLP), Machine Learning, Data Visualization, Bluetooth, Artificial Intelligence (AI), Deep Learning, APIs, Generative Adversarial Networks (GANs), GPT, Generative Pre-trained Transformers (GPT), Computer Science, Programming, Large Language Models (LLMs), Algorithms, Clustering, Tools, Information Retrieval

Storage

MongoDB, PostgreSQL, MySQL

2005 - 2012

Master's Degree in Computer Science

University of Porto (Faculty of Sciences) - Porto, Portugal

JANUARY 2024 - PRESENT

Generative AI with Large Language Models

DeepLearning.AI | AWS

JANUARY 2022 - PRESENT

Generative Adversarial Networks (GANs) Specialization

DeepLearning.AI

DECEMBER 2021 - PRESENT

Deep Learning Specialization

DeepLearning.AI

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