Liam Bui, Deep Learning Developer in Vancouver, BC, Canada
Liam Bui

Deep Learning Developer in Vancouver, BC, Canada

Member since September 15, 2019
Liam is a Certified Analytics Professional (CAP) with over six years of experience in machine learning and data analytics. He has worked with data science, machine learning, deep learning, Computer Vision, and image processing projects from data collection and processing to model training, evaluation, and deployment. He is passionate about building products to help organizations extract insight from data.
Liam is now available for hire

Portfolio

  • Terramera
    Python, Scikit-learn, OpenCV, TensorFlow, Keras, RDKit
  • Phemi Systems
    Hadoop, Spark, Hive, Zeppelin, Scala, Python, SciPy, Scikit-learn
  • DBS Bank
    Java, SAS, SQL, QlikView

Experience

Location

Vancouver, BC, Canada

Availability

Part-time

Preferred Environment

Windows, Ubuntu, Eclipse, Spyder, Bitbucket, Git

The most amazing...

...project I've worked on used Computer Vision to automatically count dead versus live worms in microscopic images, eliminating the need for manual counting.

Employment

  • Senior Machine Learning Engineer

    2018 - PRESENT
    Terramera
    • Researched deep learning models for object detection (Mask-RCNN, U-Net) using Python and TensorFlow to automate pest counting processes.
    • Implemented multispectral image processing pipelines for plant health evaluation using Computer Vision and machine learning techniques, including geometric transformation and keypoint descriptor for image alignment and stitching, stereovision for depth estimation, color threshold and watershed for segmentation, and regression and tree-based models for plant trait estimation, in Python, OpenCV, and Scikit-learn.
    • Developed a multispectral imaging prototype and implemented machine learning models to estimate grape sugar content based on multispectral reflectance, in Python, OpenCV, and Scikit-learn.
    • Implemented machine learning models for drug dose-response modeling, drug synergy analysis and prediction using cheminformatics and machine learning libraries (Scikit-learn, RDKit, PubChemPy) to accelerate the drug discovery process in plant health research.
    • Provided advice on experimental design and implemented statistical analysis pipelines with Python, Rpy2, and StatsModels to automate various statistical analyses for plant health research.
    Technologies: Python, Scikit-learn, OpenCV, TensorFlow, Keras, RDKit
  • Data Scientist

    2017 - 2017
    Phemi Systems
    • Developed distributed data processing and analytics prototypes using Spark (Scala), Hive and Zeppelin to demonstrate fast query and analytics on terabytes of clinical data.
    • Proposed machine learning and deep learning demos using Python, Scikit-learn, and TensorFlow to show how medical imaging data can be analyzed to support diagnosis.
    • Researched time-domain/frequency-domain signal processing and machine learning algorithms for fall detection based on biomedical signal data collected from wearable sensors using Python and Scikit-learn.
    • Implemented a natural language processing pipeline in Scala and Apache cTAKES - a library with both rule-based and machine learning techniques, to extract clinical information from unstructured medical text.
    • Developed term partitioned index mechanism in Java to enable fast document search in Accumulo.
    Technologies: Hadoop, Spark, Hive, Zeppelin, Scala, Python, SciPy, Scikit-learn
  • Data Analytics Engineer

    2012 - 2016
    DBS Bank
    • Developed SAS code to extract data from Teradata SQL databases and perform statistical analysis for Card and Unsecured Lending sales and marketing.
    • Liaised with the modeling team to deploy predictive models (Recommender System, Location Analytics) for targeted marketing, leading to two times the lift in the customer response rate in digital campaigns.
    • Proposed experimental design and hypothesis testing on different content factors to improve customer engagement in email marketing.
    • Developed Java analysis reports and QlikView dashboards to provide technology and operations teams with insight on process improvement and risk control.
    • Performed process mapping and simulation modeling to optimize business processes, resulting in a 10% reduction in operating costs.
    • Led infrastructure design and deployment for an enterprise data management system.
    Technologies: Java, SAS, SQL, QlikView

Experience

Skills

  • Libraries/APIs

    Keras, TensorFlow, Scikit-learn, OpenCV
  • Other

    Computer Vision, Machine Learning, Deep Learning, Image Processing, Statistics, Big Data, Statistical Analysis
  • Languages

    Python, Java, SQL, Scala
  • Frameworks

    Spark, Flask, Hadoop
  • Tools

    Scikit-image, Tableau
  • Platforms

    Linux, Windows, Amazon Web Services (AWS), QlikView
  • Storage

    MySQL, PostgreSQL, Cassandra, MongoDB

Education

  • Master's degree in Computer Science (Big Data, Machine Learning)
    2016 - 2017
    Simon Fraser University - Canada
  • Master's degree in Technology Management
    2012 - 2013
    National University of Singapore - Singapore
  • Bachelor's degree in Computer Science, Business Analytics (Dual degree)
    2008 - 2012
    Nanyang Technological University - Singapore
Certifications
  • HIPPA Business Associate II (Non-Clinical) v11
    MAY 2017 - PRESENT
    Litmos
  • Certified Analytics Professional (CAP)
    MAY 2017 - MAY 2020
    Institute for Operations Research and the Management Sciences
  • SAP Certified Business Associate with SAP ERP 6.0
    APRIL 2010 - PRESENT
    SAP

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