Liam is available for hire
Hire LiamLiam Bui
Verified Expert in Engineering
Deep Learning Developer
Location
Toronto, ON, Canada
Toptal Member Since
October 24, 2019
Liam is passionate about building data products that help organizations extract insight from data. He has worked with operations research, computer vision, and machine learning/deep learning projects, from data collection, data processing to model training, evaluation, and deployment. He has attained the Certified Machine Learning Specialty award by AWS and is a Certified Analytics Professional (CAP) awarded by the Institute for Operations Research and Management Sciences (INFORMS).
Portfolio
Toptal
SciPy, Jupyter Notebook, Scikit-learn, Python
Fugro
Amazon Web Services (AWS), Amazon SageMaker, Object Detection, Computer Vision...
Terramera
Keras, TensorFlow, OpenCV, Scikit-learn, Python
Experience
Availability
Part-time
Preferred Environment
Git, Bitbucket, Spyder, Eclipse, Ubuntu, Windows
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.
Work Experience
Data Scientist
2020 - PRESENT
Toptal
- Implemented Liquid chromatography-mass spectrometry data processing and machine learning models to detect targeted proteins in blood samples, facilitating faster disease 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.
- Provided advice on data science use cases and data collection protocols for machine learning model development/evaluation.
Technologies: SciPy, Jupyter Notebook, Scikit-learn, Python
Machine Learning Engineer (Computer Vision)
2020 - PRESENT
Fugro
- Developed deep learning object detection models and object tracking prototypes with Python and TensorFlow on Amazon SageMaker to detect and track traffic objects, reducing manual processing cost by 50%.
- Architected data processing workflow with multiple parallel compute jobs using AWS Batch and Step Functions, reducing processing time ten times.
- Implemented computer vision algorithms in C++ and OpenCV to improve automated pavement distress extraction.
- Improved data processing pipeline and implemented bundle adjustment to estimate a road object’s GPS coordinate based on vehicle’s position/orientation, inertial measurement unit (IMU) data, and camera intrinsic/extrinsic parameters.
- Standardized team’s DevOps and MLOps processes with Jenkins, Docker, and MLflow.
Technologies: Amazon Web Services (AWS), Amazon SageMaker, Object Detection, Computer Vision, MLflow, Docker, Jenkins, OpenCV, Python, C++
Senior Machine Learning Engineer
2018 - 2019
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 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) 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: Keras, TensorFlow, OpenCV, Scikit-learn, Python
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 the diagnosis.
- 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: Scikit-learn, SciPy, Python, Scala, Zeppelin, Apache Hive, Spark, Hadoop
Data Analytics Engineer
2012 - 2016
DBS
- Developed SAS code to extract data from Teradata SQL databases and perform statistical analysis for the 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: QlikView, SQL, SAS, Java
Business Intelligence Developer
2011 - 2011
Hutcabb Consulting
- Implemented inventory modeling and demand forecasting function in a Decision Support System with Java Servlet to facilitate optimal inventory decision making.
- Supported infrastructure design and deployment for the Decision Support System.
- Streamlined data processing from multiple data sources by developing Data Extract, Transform, and Load (ETL) pipeline with Microsoft SQL Server Integration Services (SSIS).
Technologies: SQL Server Integration Services (SSIS), SQL, Java
Experience
Automated Worm Counting with Deep Learning
Built an image processing pipeline and deep learning model to automatically count dead and live worms in microscopic images, reducing the worm counting time from two days (manual counting) to one hour (automated counting with Computer Vision).
Automated Plant Health Evaluation with Computer Vision
Built an image processing pipeline to automatically segment out individual plants in a greenhouse and classify the plants' health.
Grape Sugar Content Estimation with Multispectral Imaging
Built a multispectral imaging prototype and machine learning models to predict grape sugar content based on multispectral reflectance.
Plant Traits Estimation with 3D Imaging
Collaborated with the robotics team to build a 3D imaging prototype and implement an image processing pipeline to perform 3D reconstruction of plants and calculate leaf count and angles.
Drug Efficacy Prediction
Built a chemo-informatics pipeline to extract 1D, 2D, and 3D molecular descriptors of chemical molecules and predict their efficacy against certain diseases in plants.
Fall Detection with Signal Processing
Implemented signal processing algorithms and built machine learning models to detect when an elder falls based on biomedical signal data collected from wearable sensors.
Skin Lesion Classification
Implemented a prorotype to demonstrate the use of Computer Vision and Machine Learning to assist diagnosis by classifying whether a skin lesion is malignant vs benign.
Clinical Text Extraction
Implemented a prorotype to demonstrate the use of Natural Language Processing to extract relevant clinical information from clinical text.
Skills
Libraries/APIs
Keras, TensorFlow, Scikit-learn, OpenCV, SciPy
Paradigms
Data Science
Other
Computer Vision, Machine Learning, Deep Learning, Image Processing, Statistics, Big Data, Image Recognition, Artificial Intelligence (AI), MLflow, Object Detection, Statistical Analysis, Analytics, Operations Research, Inventory Management, Forecasting, Financial Analysis, Technology, Computer Science
Languages
Python, Java, SQL, SAS, C++, Scala
Frameworks
Spark, Flask, Hadoop
Tools
Scikit-image, Spyder, Bitbucket, Git, Jenkins, Amazon SageMaker, Tableau
Platforms
Ubuntu, Eclipse, Zeppelin, Docker, Jupyter Notebook, Linux, Windows, Amazon Web Services (AWS), QlikView
Storage
Apache Hive, SQL Server Integration Services (SSIS), MySQL, PostgreSQL, Cassandra, MongoDB
Education
2016 - 2017
Master's Degree in Computer Science
Simon Fraser University - British Columbia, Canada
2012 - 2013
Master's Degree in Technology Management
National University of Singapore - Singapore, Singapore
2008 - 2012
Bachelor's Degree in Computer Science, Business Analytics (Dual degree)
Nanyang Technological University - Singapore, Singapore
Certifications
SEPTEMBER 2021 - SEPTEMBER 2024
AWS Certified Machine Learning Specialty
Amazon Web Services
MAY 2017 - PRESENT
HIPPA Business Associate II (Non-Clinical) v11
Litmos
MAY 2017 - MAY 2023
Certified Analytics Professional (CAP)
Institute for Operations Research and the Management Sciences
APRIL 2010 - PRESENT
SAP Certified Business Associate with SAP ERP 6.0
SAP