Bernardt Duvenhage, Machine Learning Developer in Rocky Mountain House, AB, Canada
Bernardt Duvenhage

Machine Learning Developer in Rocky Mountain House, AB, Canada

Member since October 21, 2020
Bernardt is passionate about developing technology that fundamentally improves lives and broadens our knowledge. He led teams and developed software for computer vision, natural language understanding, modeling and simulation, and computer graphics projects. Bernardt has experience programming in C++ and Python, using frameworks such as scikit-learn and PyTorch for machine learning and deep learning, transformers, TorchVision, CUDA, OpenGL, Open Scene Graph, OpenCV, and NLTK.
Bernardt is now available for hire




Rocky Mountain House, AB, Canada



Preferred Environment

C++, Python, MacOS, Linux

The most amazing...

...project I've developed is a natural language understanding and computer vision service used to build conversational agents in low-resource languages.


  • Machine Learning Lead, Conversational AI Systems

    2017 - PRESENT
    Praekelt Consulting
    • Developed a natural language processing and computer vision service that is being used to build task-oriented conversational agents for low resource languages. Technologies include transformers, PyTorch, TorchVision, Flask-RESTful, and PostgreSQL.
    • Created intent classification, sentiment, and entity extraction models that rely on a variety of deep learning and classical machine learning techniques to accommodate a wide variety of languages. Used transformers, sklearn, PyTorch, and TensorFlow.
    • Developed a machine vision-based quality assurance application with a machine vision camera interface. The technologies include TorchVision, Flask-RESTful, GeniCam, and React. Used deep transfer learning to improve sample efficiency of clients' data.
    Technologies: Data Analytics, REST APIs, Google Cloud, BigQuery, Google BigQuery, Deep Neural Networks, Neural Networks, Data Science, Natural Language Processing (NLP), Artificial Intelligence (AI), Google Cloud Platform (GCP), Flask-RESTful, Python, Computer Vision, Natural Language Understanding (NLU), Machine Learning, Sentiment Analysis, Text Classification, Image Classification
  • Research Group Leader and Principal Research Scientist, Optronic Sensor Systems

    2014 - 2017
    Council for Scientific and Industrial Research
    • Developed a real-time image processing framework as well as image enhancement, target detection, object tracking, and state estimation algorithms.
    • Developed software interfaces to hardware devices like cameras, pan-tilt-zoom systems, communication radios, and real-time clocks.
    • Led the company's image processing team of full-time employees and students, published some papers, and helped with talent management and screening.
    Technologies: 3D Math, OpenGL, Embedded Software, Assembly, OpenSceneGraph, GLSL, OpenCV, C++
  • Senior Research Scientist, Optronic Sensor Systems

    2008 - 2014
    Council for Scientific and Industrial Research
    • Developed models for a physically based optronics scene simulator. The models were developed in C++ and an in-house 3D modelling tool.
    • Developed physically based renderers for the long and medium wave infrared bands. The full software and hardware accelerated renderers were developed in C++ and OpenGL with GLSL. The rendering algorithms ranged from simple to path tracing.
    • Developed physically based renderers for the short wave (reflective) and visual bands. The software and hardware accelerated renderers were developed in C++ and OpenGL with GLSL. The rendering algorithms ranged from simple to path tracing.
    Technologies: 3D Math, Physically based rendering, OpenGL, C++
  • Senior Research Scientist, Modelling and Simulation

    2004 - 2008
    Council for Scientific and Industrial Research
    • Developed a faster than real-time distributed modelling and simulation framework for wargaming type simulations. The simulation framework was implemented in C++ and employed TCP communication between the nodes.
    • Developed vehicle and equipment models for wargaming type simulations. The models ranged from behavioural to physically based and were implemented in C++.
    • Developed a 3D simulation viewer and analysis tool using Open Scene Graph and OSGEarth.
    Technologies: Simulations, Algorithms, OpenSceneGraph, Modeling, OpenGL, C++


  • A Natural Language Understanding and Computer Vision Cloud Service

    A Python-based cloud service for training and deploying natural language understanding and computer vision models for task-oriented conversational agents. I was responsible for developing the data science workflow, model, and data management as well as the production service. I was also responsible for implementing and training a number of models for image segmentation and classification, intent detection, sentiment, and entity extraction. The technologies used include PyTorch, TorchVision, TensorFlow, SKlearn, Pandas, swagger/OpenAPI, Flask, and PostgreSQL.

  • Real-time Image Processing Framework

    An image processing and machine vision framework implemented in C++, CUDA, and GLSL and optimized for real-time execution on multiple simultaneous high-resolution camera streams. The framework also included my own long-range and low light image enhancement algorithms, image stabilization, object detection, and target tracking implementations as well as software interfaces to hardware devices like machine vision cameras, pan-tilt-zoom systems, and communication radios.

  • Physically-based Path Tracing Renderer

    A physically-based renderer for indoor scenes written in C++. The renderer used path tracing and other ray tracing variants to create simulated images of indoor and outdoor scenes for a surveillance modeling application. The implementation included area and skylights, various bidirectional scattering functions, and acceleration structures to support large complex scenes, as well as concepts such as flux, radiance, irradiance, and brightness.


  • Languages

    Python, C++, GLSL, Assembly
  • Libraries/APIs

    PyTorch, REST APIs, TensorFlow, Flask-RESTful, OpenCV, OpenGL, Scikit-learn, NLTK, NumPy, Pandas
  • Platforms

    Linux, MacOS, Google Cloud Platform (GCP)
  • Other

    NLU, Computer Graphics, Machine Learning, Computer Science, Artificial Intelligence (AI), Natural Language Processing (NLP), Neural Networks, Text Classification, Image Classification, AI Design, Computer Vision, Modeling, Google BigQuery, Data Analytics, Simulations, Lego Mindstorms, Lego Powered UP, Facial Recognition, Facial Tracking, Video Capture, Image Recognition, Neural Rendering, Visual Computing, Sentiment Analysis, Mathematics, Physics, Molecular Biology, Hardware Development, Data Engineering, Deep Reinforcement Learning, Deep Learning, Natural Language Understanding (NLU), Embedded Software, Physically based rendering, Torchvision, Transformers, Image Processing, Hardware Drivers, GUI, Ray Tracing, Algorithms, 3D Math, Deep Neural Networks, Generative Adversarial Networks (GANs)
  • Tools

    BigQuery, OpenSceneGraph
  • Paradigms

    Data Science
  • Storage

    Google Cloud


  • PhD in Computer Science
    2008 - 2015
    University of Pretoria - South Africa


  • NLP Specialization (In Progress: 3/4 Course Certificates Completed)
  • Deep Reinforcement Learning for Enterprise Nanodegree
  • Google Cloud Certified - Professional Data Engineer
    SEPTEMBER 2018 - OCTOBER 2020
    Google Cloud
  • Deep Learning 5-course Specialization by

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