Diogo Dutra, Data Scientist and Machine Learning Developer in Toronto, ON, Canada
Diogo Dutra

Data Scientist and Machine Learning Developer in Toronto, ON, Canada

Member since June 19, 2019
Diogo is a machine learning engineer with a Master of Science degree in aeronautics and expertise in the whole pipeline from data visualization to model deployment. His 14+ years of international experience in research and development for defense, public safety, and aerospace industries allow him to combine new methodologies like deep learning and computer vision with traditional ones (e.g., physics, simulation, sensor fusion, Kalman filter, Fourier transform, digital signal processing).
Diogo is now available for hire


  • Ford Motor Company
    Machine Learning, Computer Vision, Deep Learning, OpenCV, ARM, Android...
  • Patriot One Technologies
    Data Science, Data Analysis, Image Processing, Technical Leadership...
  • Altran
    Agile, Google Unit Test, CMake, AUTOSAR, VS Code, OpenCV, Git...



Toronto, ON, Canada



Preferred Environment

Python 3, SciPy, Scikit-learn, Pandas, PyTorch, Jupyter Notebook, Fast.ai, Aerospace & Defense, Aeronautics, Digital Signal Processing

The most amazing...

...thing I've developed detects and identifies concealed weapons (e.g., handguns) and non-weapons (e.g., phones) on the body by combining deep learning and radar.


  • Machine Learning Developer

    2021 - PRESENT
    Ford Motor Company
    • Tasked with the research and development of future artificial intelligence applications for the next generation of autonomous vehicle infotainment systems at Ford's R&D laboratory.
    • Conceived a series of proofs-of-concept for the self-driving car, including different areas such as deep learning, computer vision, user recommendation, embedded systems, and connectivity with other devices.
    • Utilized a number of technologies, including Linux, Office365, Eclipse, Blackberry QNX, CMake, C++, Android Auto, AUTOSAR, Python, OpenCV, TensorFlow, Git, and Google Cloud Platform.
    Technologies: Machine Learning, Computer Vision, Deep Learning, OpenCV, ARM, Android, AUTOSAR, Android Auto, Google Cloud Platform (GCP), TensorFlow, Linux, QNX, Git, Python, Python 3, Python 2, Office 365, C++, CMake, Ubuntu, Windows
  • Lead Data Scientist

    2019 - 2021
    Patriot One Technologies
    • Created a deep learning model that detects concealed weapons with radar and magnetic sensors, digital signal processing, and convolutional neural network.
    • Managed a technical team (principal scientist and data scientists) on an Agile project.
    • Accumulated management roles as machine learning engineer, data science team leader together with my original role as a data scientist.
    Technologies: Data Science, Data Analysis, Image Processing, Technical Leadership, Product Development, Research, Supervised Learning, Neural Networks, Convolutional Neural Networks, Data Cleaning, Data Visualization, Data Mining, Fourier Transform, Python, Atlassian Confluence, Jira, Vector Network Analyser, Radar, Seaborn, Pandas, Scikit-learn, SciPy, PyTorch, Python 3, Anaconda, Jupyter Notebook, Git, Machine Learning, Team Leadership, Teamwork, Predictive Analytics, Predictive Learning, Object Detection
  • Senior Consultant Engineer

    2018 - 2019
    • Coded embedded C++ for the BMW and Continental future fully digital driver's dashboard, specifically the BMW Series 7 Instrument Cluster 5th Generation.
    • Updated procedures on the Confluence website such as onboarding instructions for new team members and how to set up the environment.
    • Applied Google unit tests and Python Robot framework to automate testing procedures for verification of new versions before release.
    Technologies: Agile, Google Unit Test, CMake, AUTOSAR, VS Code, OpenCV, Git, Continuous Integration (CI), Jenkins, Atlassian Confluence, Jira, ARM, C++, Python 3, Robot Framework, Teamwork, Python
  • Technology Consultant

    2017 - 2018
    Natura Brazil
    • Completed data science analysis of MRO warehouse reduced 30% stock value of spare parts without impact on stock-out.
    • Promoted industry 4.0 applications, including additive manufacturing (3D printing), augmented reality, IoT, big data, machine learning, and artificial intelligence.
    • Presented a successful business case for the acquisition of a professional 3D printer that reduced the acquisition of plastic SKUs by 66% annually.
    • Implemented three proofs of concept with augmented reality.
    • Served as the scrum master for the development and employment of a new system to request materials and services. Increased the administrative assistant team's productivity by 48% and improved access to information for the internal maintenance team.
    Technologies: SAP, Predictive Maintenance, 3D Printing, Augmented Reality (AR), Office 365, Microsoft Power BI, Azure, Leadership, Team Leadership, Agile Team Leadership, Python, Industry 4.0, Predictive Modeling, Warehouses, Forecasting, Technical Leadership, Management, Predictive Analytics, Predictive Learning, Python 3
  • Chief of Technology Office

    2016 - 2017
    • Turned my startup GoEpik into the most attractive Brazilian startup by 2017 while I was the CTO, by offering augmented reality for field maintenance. We were accelerated by Google and Plug and Play with an invitation to stay in Silicon Valley.
    • Conceived and coded the first prototype to visually guide the user record proofs of task completions with pictures and to ease maintenance activities such as inspection, cleaning, and lubrication. It was converted into sales for Natura and Renault.
    • Conceived and coded the second prototype to connect through video conference an expert with a field technician using an augmented reality platform with computer vision features such as adding markers, texts, and pictures in the field-of-view.
    • Benchmarked similar products and competitors for marketing positioning, including SightCall, Microsoft HoloLens, and Scope AR.
    Technologies: RESTful Development, RESTful APIs, REST, Chief of Technology Office, CTO, WebRTC, Airtable, Vuforia, Android, C#, Unity3D, REST APIs
  • Combat System Integration Engineer

    2013 - 2017
    Itaguai Construcoes Navais
    • Performed assembly and inspection specifications (AIS); setting-to-work (STW); factory acceptance tests (FAT); and integration, verification, validation, and qualification (IVVQ) activities.
    • Participated in the transfer of technology at former DCNS premises for the combat system integration activities during on-the-job training (OJT) under the new Riachuelo class (derived from the French Scorpène) for the Brazilian submarine program.
    • Translated technical documents from English and French to Portuguese.
    Technologies: IP Networks, Windows, Wireshark, HP Quality Center (QC), Translations, Project Management, PeopleTools, Requirements
  • Project and Commercial Manager

    2012 - 2013
    • Prospected a R$200,000 new contract for embedded software development from DCNS, a French Naval and Defense exporter, by working all the way from first cold contact with the client until the contract signature.
    • Led engineers who were expatriated to France for software development on the client’s premises.
    • Accumulated the responsibility for the contract prospected by me. Embedded software development for PLC under the PMI methodology to French clients.
    • Reported my project progress to stakeholders (CEO, new business director, and the French client DCNS).
    • Finished project within the deadline and its profit above expectations, from loss to 10% positive.
    • Wrote contracts (including the definition of pricing) and answers to requests for information and requests for proposals (RFI/RFQ).
    • Represented as an exhibitor in many international defense events such as the Brazilian LAAD and IDEX in the United Arab Emirates.
    Technologies: Office 95, Leadership, Team Leadership, Aeronautics, Simulations, Navigation, Sensor Fusion, Digital Signal Processing, Kalman Filters, Inertial Navigation System, GPS, MATLAB, Simulink, C, C++, CMake, ARM, Project Management, PMBOK, Aerospace & Defense, Aerodynamics, Telemetry, Pricing, Contract, Business to Business (B2B), Physics Simulations, Controls, Unmanned Aerial Vehicles (UAV), Sensor Data, GPSS
  • Aerospace Engineer

    2007 - 2013
    Denel Dynamics
    • Developed real-time data fusion for missiles and guided bombs: transfer alignment for initialization of inertial platform and aided navigation (GPS, BaroAltimeter, and aircraft INS).
    • Validated the embedded code on hardware-in-the-loop simulation, embedded on ARM using C language, and analyzed flight test data by telemetry in the field at Air Force launching base.
    • Increased the flight span duration from 1 to 10 minutes thanks to better navigation accuracy.
    • Created a novel target tracking algorithm for missile employing extended Kalman filter by performing data fusion of passive target line-of-sight signals based on 6-states extended Kalman filter with design in MATLAB and embedded in C code.
    • Automated code unit tests of in-house linear algebra and Kalman filter libraries.
    • Simulated missiles subsystems including moving parts, hydraulic, external, and internal aerodynamics (subsonic and supersonic) on Simulink.
    • Defined the technical specification of the inertial unit (gyroscope and accelerometer) for a long-range missile.
    • Translated technical documents such as textbooks, papers, and technical reports from English to Portuguese.
    Technologies: Subversion (SVN), Visual Studio, C++, C, data fusion, Kalman Filters, Inertial Navigation, Aeronautics, Unmanned Aerial Vehicles (UAV), Aerospace & Defense, Aerodynamics, Autopilot, Controls, Navigation, ARM, Simulations, Hardware-In-The-Loop Simulation, Simulink, MATLAB, Digital Signal Processing, Estimators, Embedded C, Teamwork
  • Aerospace Engineer

    2007 - 2008
    • Retrofitted the propulsion system for the F5-BR jet fighter and AMX (A-1M) jet bomber, including field tests with the airplane anchored to the ground and its turbine operating with afterburner on.
    • Created a simulation of the Rolls-Royce Spey Mark 807 engine in MATLAB to support other departments such as aerodynamics.
    • Managed propulsion system project requirements with DOORS software.
    Technologies: Datcom, DOORS, Subversion (SVN), Simulink, MATLAB, Aerodynamics, Aeronautics, Aerospace & Defense, Propulsion, Teamwork, Simulations


  • Covid-19 Triage by Hemogram

    Created this classifier to help the hospitals to triage the suspects of Covid-19 from a simple blood test! It is faster and spares many SARS-CoV-2 test kits. It can save lives and costs at the same time during the peak of the coronavirus pandemic.

  • Diagnose Pneumonia

    What if we could speed up the diagnosis process? A novel classifier was trained with a dataset of X-ray images from children's chests. Now, it labels any x-ray image as either normal, bacterial pneumonia, or viral pneumonia. The result is an automated diagnosis that can accelerate the clinical care for children with world-class precision.

  • Fake Face Generator

    Trained generative adversarial networks (GAN) using a dataset of celebrities' photos to learn how to create a fake human face. This same technique can be used to generate any real content like images, texts, simulations, or signals.

  • Concealed Weapon Detector

    Applied computer vision and digital signal processing techniques on the radar for classification. The novel model finds meaningful contrasts between weapons and decoys of a person in movement. CNN can be used to analyze images and any other signals such as video, audio, radar, and sonar.

  • AI Writer

    What if artificial intelligence could kickstart an original text, so you do not have to start a new one from scratch? I created this website that the user enters a few keywords, and it gives back some related suggestions of text with titles. I used Heroku, RESTful, and asynchronous tasks to deploy this model online.

  • Online Product Recommender for eCommerce

    Created a recommendation engine for a cloud-service online retailer based on a collaborative filter. Any online business must leverage its database to find out and deploy a better user experience to drive consumption. Unsupervised learning is ideal to find customer segments, which can be used to predict common preferences.

  • Flight Delay Predictor

    The passengers on the world's busiest airways now know if their flight will delay with 15 minutes of margin. I created this supervised learning model considering a 2-year long hourly dataset of airport departures, arrivals, and weather.

  • Quadcopter Autopilot

    The Parrot quadcopter just gained an autopilot. This new reinforcement learning knows how much power each rotor must apply in order to stabilize the drone thanks to thousands of simulated runs. Let me know if you need specific maneuvers or autopilot for any other vehicle.

  • Bike Sharing Demand Forecast

    Now, the owner of a bike-sharing company from Washington can make better decisions on how many bikes to buy. This forecast helps the owner to avoid losing revenue by having too few or skyrocketing the operational costs by having too many. I created this model by training an RNN over a 2-year hourly rental and weather data. RNNs are suitable to predict any time-series data such as demand, weather, and stock options.

  • Retailer Customer Segmentation

    A retailer from Portugal wanted to lower the frequency of deliveries to reduce cost without considerably disturbing its clients. It was achieved by finding its customer segments and selecting which would not be significantly impacted by three weekly deliveries instead of five. Unsupervised learning is ideal to find customer segments and understand their specific purchase behaviors.

  • Painting Style Copier

    The style transfer technique allows the convolutional neural network to learn independently the content from one picture and the style from another. Later, I gradually applied the style from the painting to the content of the picture with the octopus.

  • Missile Autopilot (Navigation, Guidance, and Command)

    Designed, embedded, and tested in the field with telemetry during real launches algorithms for missiles and smart-bombs, including aided navigation (GPS, BaroAltimeter, and IMU), transfer alignment, data fusion, target position estimation, and Extended Kalman Filter.

  • Sentiment Analysis for movie reviews

    Created a predictive model to read a movie review and classify it as POSITIVE or NEGATIVE. The model applies text processing techniques and a neural network. This technique is also reusable for other applications such as product reviews or stock market discussions.

  • Brandify, Online Addition of Logo on Background of An Awesome Ad Image

    Online advertisement opens room for custom experience based on the user's known preferences. This opportunity is explored by offering an automated way to change the image on website banners with the brand based on which user is accessing the website.

    This methodology is achievable by reusing a trained ResNet101 (transfer learning) for image segmentation, followed by image processing to find the best spot on the background to place the logo.

  • Video Special Effects

    I developed the core of the video processing technology for one of the Big Five Giant American tech companies. Now you can use your camera to create custom special effects that relies on background removal and augmented reality animations. This technique is transferable to online streaming data such as filters.

  • Virtual Try-on

    Planned the scope of the proof-of-concept and minimum viable product for a startup that is about to launch a new mobile shopping experience by combining augmented reality, photogrammetry, artificial intelligence, and virtual try-on.


  • Languages

    Python 3, C++, Python, C, SQL, Simulink, C#, GPSS, Embedded C, Python 2, Bash Script, Bash
  • Libraries/APIs

    PyTorch, Pandas, Scikit-learn, NumPy, Matplotlib, SciPy, FFmpeg, OpenCV, WebRTC, REST APIs, Beautiful Soup, Fast.ai, TensorFlow
  • Tools

    Seaborn, Radar, Microsoft Power BI, MATLAB, Git, AutoML, Jira, OpenAI Gym, Atlassian Confluence, CMake, HP Quality Center (QC), Wireshark, DOORS, Composer, GitHub, PeopleTools, Android Auto
  • Paradigms

    Data Science, Management, Agile, REST, Continuous Integration (CI), PMBOK, RESTful Development
  • Platforms

    Jupyter Notebook, Anaconda, Windows, Heroku, Azure, Linux, Visual Studio Code, Android, Vuforia, Docker, Amazon Web Services (AWS), Google Cloud Platform (GCP), Ubuntu
  • Other

    Digital Signal Processing, Kalman Filters, Aerospace & Defense, Aeronautics, Flight Control, Supervised Learning, Machine Learning, Predictive Modeling, Regression, Data Analysis, Deep Learning, Convolutional Neural Networks, Autoencoders, Learning Transfer, Metrics, Translations, Neural Networks, Artificial Intelligence (AI), Computer Vision, Classification, Deep Neural Networks, Product Development, Analysis, Trend Analysis, Image Processing, Navigation, Autopilot, Unmanned Aerial Vehicles (UAV), Inertial Navigation, data fusion, Fourier Transform, Signal Processing, Visualization, Statistical Modeling, Research, Image Recognition, Sensor Fusion, Inertial Navigation System, Decision Tree Classification, Decision Tree Regression, Decision Trees, Linear Regression, Polynomial Regression, Mathematics, Physics, Simulations, Controls, Entrepreneurship, Unsupervised Learning, Clustering, Generative Adversarial Networks (GANs), Writing & Editing, GPU Computing, Graphics Processing Unit (GPU), Time Series, Product Forecasts, Sales Forecasting, Augmented Reality (AR), Hardware-In-The-Loop Simulation, Statistics, Data Analytics, CTO, Chief of Technology Office, Logistic Regression, Numerical Simulations, Aerodynamics, Aircraft Engineering, Finance, Administration, Projects, Reinforcement Learning, Data Inference, Analytics, Deployment, Natural Language Processing (NLP), Trend Forecasting, Time Series Analysis, Recurrent Neural Networks, Product Lifecycle Management (PLM), Business Cases, Annotations, Grammar & Language Creation, Texting, APIs, Kaggle, Online Sales, eCommerce, Markov Model, Deep Reinforcement Learning, Style Transfer, Vector Network Analyser, Google Unit Test, Office 365, 3D Printing, Predictive Maintenance, SAP, Airtable, IP Networks, Datcom, Bokeh, AWS, Data Visualization, Data Mining, Data Cleaning, Technical Leadership, Engineering, Web Scraping, scrapping, Scraping, RESTful APIs, Recommendation Systems, Text Processing, Text Classification, Leadership, Team Leadership, Agile Team Leadership, GPS, ARM, Telemetry, Propulsion, Industry 4.0, Warehouses, Forecasting, Requirements, Teamwork, Pricing, Contract, Business to Business (B2B), Physics Simulations, Sensor Data, Estimators, Predictive Analytics, Predictive Learning, Predictive Text, Image Segmentation, AUTOSAR, QNX, MPEG, Scripting, Videos, Object Detection, Articles, Planning, MVP Design, Minimum Viable Products (MVP), POC, Proof of Concept (POC), Lean Startups, Startups, Virtual Reality (VR), Photogrammetry, 3D, Fashion
  • Frameworks

    Unity3D, Flask, Robot Framework
  • Industry Expertise

    Project Management, Marketing
  • Storage



  • MBA in Entrepreneurship
    2011 - 2013
    FGV - Brazil
  • Master's degree in Aerospace Engineering
    2006 - 2010
    Institute of Aeronautical Technology - Brazil
  • Bachelor's degree in Mechanical Engineering
    2001 - 2005
    Institute of Military Engineering - Brazil


  • AI Product Manager
    JUNE 2020 - PRESENT
  • Deep Learning
    JUNE 2019 - PRESENT
  • Machine Learning
    JUNE 2018 - PRESENT
  • Data Science Essentials
  • Translator English Portuguese
    JUNE 2017 - PRESENT

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