DAVID ABRAHAM

Software Engineer

David received his BSc. in Electrical and Computer Engineering with first class honours in 2021, specializing in Control Systems Engineering at the University of the West Indies. He is an avid gamer and soccer fan who enjoys mixing music in his spare time. However, it was his keen interest in modern technology that propelled him to his degree and more so, pursuing a role at Virtana.

As a past intern and company collaborator, David has dabbled with OpenCV, embedded systems and AWS cloud services in his contributions to Ventri and Virtana’s Drone VSLAM research. He has since translated this experience to client-facing projects, utilizing tools like ROS and Docker to create solutions to camera hardware and calibration related problems. David believes computer science and engineering to be the ever-growing future and his work thus far has persuaded his interest in Data Science and Cloud Technology as a potential masters degree. He is excited to continue expanding on the knowledge and experience that accompany working alongside the Silicon Valley veteran and his like-minded team of techies.

Past Projects:

  • Calibration:

    •  Wrote a variety of C++/Python scripts to implement and improve OpenCV camera undistortion for a high FOV camera.

    • Partnered in the tool development for analyzing Luxonis camera hardware timestamping accuracy and latency. (2022, DepthAI, C++)

  • DevOps:

    • Wrote a variety of Bash scripts to manage the building, running and updating of various project dependent Docker container images.

    • Implemented the Gitlab CI/CD pipeline to account for these images stored on a remote Google container registry.

  • Embedded IoT:

    • Partnered in the design and development of alternative hardware solutions to improve the accuracy of low-cost hardware sensors. (2022, Circuit Design, ADCs)

    • Explored the use of software/algorithmic approaches to improve sensor accuracy by performing scaling and remapping of ADC-acquired sensor data, incorporating linear and polynomial regression analysis. (2021, Pandas, Matplotlib/Plotly, Linear Regression)

    • Created a Python notebook to improve engineer workflow for uploading and extracting salient sensor data to characterize performance.

    • Involved in the maintenance and addition of features to the AWS cloud backend (IoT, AppSync, DynamoDB, Lambda, Amplify) for an IoT-enabled ESP32-based device.

    • Contributed to the implementation of QoL features for a low cost IoT device by addressing technical debt across the tech stack (including Amazon FreeRTOS, AWS cloud backend and ReactJs front end).

  • Perception:

    • Designed and implemented a custom ROS approach to VSLAM using AprilTag fiducials. (2020, ROS, C++, OpenCV)