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Hi, I’m Narmada 👋

I am a software developer at StrobelTEK Inc. I graduated with an M.Eng. in Computer Engineering (thesis-based) at the Memorial University of Newfoundland, Canada.

Interests
  • Autonomous navigation systems
  • Unmanned aerial vehicles
  • Self-driving cars
  • Deep Learning for aided-navigation in GPS denied environments
  • Computer Vision and Machine Learning
Contact

narmadabalasooriya@gmail.com +17092190953

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    Software Developer

    StrobelTEK Inc

    St.John's, NL, Canada


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    Research Engineer (Contract)

    ConscientAI Labs

    Colombo, Sri Lanka


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    Freelance Computer Engineer

    Upwork

    Remote


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Currently published research papers

  1. AI-based landing zone detection for vertical takeoff and land LiDAR localization and mapping pipelines
    Balasooriya, Narmada M, De Silva, Oscar, Jayasiri, Awantha, and Mann, George KI
    Drone Systems and Applications
    2024


  2. In-situ sea ice detection using DeepLabv3 semantic segmentation
    Balasooriya, Narmada, Dowden, Benjamin, Chen, Jesse, De Silva, Oscar, and Huang, Weimin
    In OCEANS 2021: San Diego–Porto
    2021
    IEEE


  3. Landing Zone Identification Using A Hardware-accelerated Deep Learning Module
    Atapattu, Sachithra, Balasooriya, Narmada M., De Silva, Oscar, Jayasiri, Awantha, Mann, George, and Gosine, Raymond
    In 77th Annual Forum & Technology Display
    2020
    The Vertical Flight Society


  4. Visualizing the consequences of climate change using cycle-consistent adversarial networks
    Schmidt, Victor, Luccioni, Alexandra, Mukkavilli, S Karthik, Balasooriya, Narmada, Sankaran, Kris, Chayes, Jennifer, and Bengio, Yoshua
    arXiv preprint arXiv:1905.03709
    2019


  5. AI for Mitigating Effects of Climate and Weather Changes in Agriculture
    Balasooriya, Narmada, Athuraliya, C.D, and Gunatilake, Janak
    In AI for Social Good Workshop at ICLR 2019
    2019


  6. Analysis of Online Customer Shipping Programs and Policies
    Edirisinghe, Gihan, Munson, Charles, and Balasooriya, Narmada
    In 49th Annual Meeting of the Decision Sciences Institute
    2018


  7. A sophisticated convolutional neural network model for brain tumor classification
    Balasooriya, Narmada M, and Nawarathna, Ruwan D
    In 2017 IEEE International Conference on Industrial and Information Systems (ICIIS)
    2017
    IEEE


Courses followed during graduate degree studies

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Deep Learning for point cloud semantic segmentation
September 2020 - December 2022
Analyzing different deep learning based semantic segmentation methods for point clouds and aerial LiDAR data. Analyzing point cloud registration methods with VLOAM architecture.
Python C++ ROS Open3D NVIDIA Jetson Google Colaboratory


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Landing zone detection using point cloud semantic segmentation
October 2020 - April 2021
Applied transfer learning to ConvPoint model artchitecture to detect landing zones using aerial point cloud data. Tested the performance on a NVIDIA Jetson AGX Xavier developer kit.
Python PyTorch Open3D NVIDIA Jetson Google Colaboratory


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Sea-ice semantic Segmentation using Deep Learning
November 2019 - December 2020
Compared the performance of Deeplabv3 model with PSPNet model for sea-ice semantic segmentation. Tested the runtime speed on a NVIDIA Jetson AGX Xavier developer kit and implemented a TFlite model for mobile application.
Python TensorFlow OpenCV NVIDIA Jetson Google Colaboratory


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ANALYTICAL TOOLS IN BUSINESS PRACTICE- Analysis of Online Customer Shipping Programs and Policies
March 2018 - September 2018
In collaboration with a project of Dr. Gihan Edirisinghe, Washington State University, USA. Development of a Python program to extract specific information from Amazon product web pages. Used BeautifulSoup python library along with other html libraries to extract data. Codes are available at request.
Python HTML


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A Sophisticated Convolutional Neural Network Model for Brain Tumor Classification
December 2016 - May 2017
Developed a model using Convolutional Neural Networks to classify brain tumors. MRI images of three tumor classes, one healthy class and one unknown tumor type were used for training and testing dataset..
Python TensorFlow TFLearn Scikit-learn


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Vision Based Obstacle Avoidance and Safety System For a Quadcopter
March 2016 - October 2016
Developed a vision based autonomous obstacle avoidance system for a quadcopter. Development of feature extraction and matching algorithm using C++. Reprogramming the firmware of the PX4Flow image sensor to obtain necessary data using C/C++.
C++ Python OpenCV



Collaborations with different research groups

  • National Research Council, Canada

    Graduate Research Student

    September 2020 - October 2022


  • ConscientAI Labs, Sri Lanka

    Research Engineer (contract)

    March 2019 - August 2019


  • Visualizing Climate Change - MILA, Canada

    Volunteer Researcher

    January 2019 - March 2019


  • Climate Change AI- How can AI Help?

    ICML 2019 Workshop - Volunteer in Organizing Committee

    2019


  • Analysis of Online Customer Shipping Programs and Policies - Washington State University, USA

    Volunteer Data Engineer

    March 2018 - September 2018


  • Women in Machine Learning Workshop

    Reviewer

    2017 and 2018


  • IFS R&D International (Pvt) Ltd, Sri Lanka

    Intern (Software Engineering)

    October 2015 - March 2016


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