Machine Learning Expert for Data Science POC2021 - 2022Breadcrumb Data Limited
Technologies: TensorFlow Deep Learning Library (TFLearn), Data Science, Machine Learning, Data Featuring, Variational Autoencoders, TensorFlow, IOTA, Raspberry Pi, Autoencoders, Canbus, Data Analysis, Forecasting, Data Visualization, API Integration, Simulations, Inference, Finetuning, Recommendation Systems, Communication, Open Source, Pandas, Bash
- Developed time series anomaly detection using autoencoders for bearing and mills.
- Used a Controller Area Network (CAN bus) to build a vibration anomaly detection. The system uses the accelerometer acceleration data to estimate velocity and displacement.
- Estimated power spectrum to estimate the harmonics of vibration and use that to estimate the health of the equipment.
- Used TensorFlow to build this application and deployed it to Pi Zero and Pi 4.
Data Scientist and AI Consultant2021 - 2022S Wave International Corp
Technologies: Data Science, Machine Learning, Data Engineering, AIOps, AWS, Models, Data, Projects, Hang Tags, Transformer Models, Fast.ai, Scikit-learn, Time Series Analysis, Docker, Audio, Signal Processing, Data Visualization, API Integration, Inference, Finetuning, DeepSpeed, PyTorch-lightning, Communication, Open Source, Pandas, Bash
- Developed deep learning models to auto-tag music records using generated spectrogram images created from music records.
- Tracked and fixed bugs using Jira as a reporting tool.
- Deployed the production model in AWS Fargate with an elastic application load balancer to auto-scale the auto-tagging of music records depending on demand.
- Estimated the beat per minute using signal processing and deep learning. The project used the ViT model to classify spectrograms.
- Used PyTorch Lightning and DeepSpeed to train models using a large number of tracks.
GIS Platform Architect/Engineer2021 - 2021Birch Infrastructure, PBLLC
Technologies: Python, Data Building Tool (DBT), Prefect, ArcGIS, GPS, Docker, Google Kubernetes Engine (GKE), Data Analysis, Statistics, Data Analytics, Data Visualization, API Integration, Analytics, Datasets, Inference, Finetuning, Google BigQuery, Communication, Open Source, Data Mining, ETL, Pandas, Bash, Data Reporting
- Replicated data from Velocity Suite to BigQuery, performed many ETL operations, and generated materialized views using DBT.
- Converted geospatial data from shapefiles into BigQuery spatial.
- Generated a materialized view of LMP prices with weather information, updated hourly.
- Created Prefect flows to create jobs for data scrapping and downloading from various sources into BigQuery.
- Created APIs to perform data downloads from various sources like FRED, LMP prices, and other spatial data sources.
Developer2020 - 2021Toptal Client
Technologies: Language Models, BERT, Python 3, PyTorch, Fast.ai, Scikit-learn, Natural Language Processing (NLP), GPT-2, GPT-J, Docker, Data Analysis, Statistics, Data Visualization, Causal Inference, Text Generation, Inference, Finetuning, Communication, Open Source, ETL, Machine Learning Operations (MLOps), Pandas, Bash
- Created an API for a chatbot to train medical students with virtual patients for the Meksi project in Sydney.
- Used pre-trained BERT models with examples sent from the client.
- Created an API to infer the intent from user inquiries.
- Built a chatbot using the intent classifier, Named Entity Recognition (NER).
- Merged the Bert Response with an IBM Watson assistant response based on confidence to identify the intent. The results were 97% accurate across 512 intents.
Machine Learning to Build Seismic Activity Classifier2019 - 2021Oyu Tolgoi LLC
Technologies: Computer Vision, Deep Learning, Dlib, OpenCV, Qt, C++, PyTorch, TensorFlow, Keras, Python, Time Series Analysis, Google Kubernetes Engine (GKE), Audio, Data Visualization, Inference, Finetuning, Communication, Open Source, Azure Databricks, Pandas, Bash
- Converted seismic traces into the spectrogram to be used with image detection, a Resnet50 model.
- Built a multi-input model with the height of the event as an embedding input and spectrogram as the second input. The model and approach will be published in the scientific journal Bulletin of Seismological Society of America.
- Deployed the model successfully, and it is planned to go into production in 2020.
Machine Learning Consultant2015 - 2021Global Unmanned System
Technologies: Amazon Web Services (AWS), ArcPy, Point Clouds, Amazon SageMaker, 3D Image Processing, Image Processing, Predictive Analytics, Computer Vision, ArcGIS Runtime SDK for .NET, PyTorch, Data Science, GIS, MySQL, Agile Software Development, Deep Learning, AWS, Git, XGBoost, Keras, OpenCV, R, Python, Data Analysis, Object Detection, Video Processing, Statistics, Data Visualization, Inference, Finetuning, Algorithms, Open Source, Pandas, Bash, Data Reporting
- Developed algorithms to estimate above-ground biomass using point cloud data from drone images.
- Created object detection software for sealion detection in drone images.
- Classified images for Sandalwood detection in drone images.
- Developed various image analysis software for drone images using OpenCV.
- Created various GIS applications for satellite images and point cloud data.
- Developed a program to help ship berthing at Fremantle Port using slam algorithm and graph network.
- Gathered requirements and met with mine managers and refineries to learn their problems and find possible projects.
Senior Data Scientist2018 - 2020Freelance Work
Technologies: Transformer Models, BERT, Language Models, Reinforcement Learning, Uniformance Process History Database (PHD), OSI Model, Data Engineering, ArcPy, Point Clouds, RStan, Image Processing, Predictive Analytics, Kubernetes, Microsoft Power BI, ArcGIS Runtime SDK for .NET, PyTorch, Data Science, GIS, SQL, Agile Software Development, Deep Learning, Artificial Intelligence (AI), Statistical Learning, Databricks, Azure ML Studio, Azure Machine Learning, C++, R, Python, Scikit-learn, Time Series Analysis, Signal Processing, Forecasting, Statistics, Data Analytics, Data Visualization, Physics Simulations, Inference, Finetuning, Open Source, ETL, Azure Databricks, Machine Learning Operations (MLOps), XGBoost, Pandas, Bash, Data Reporting
- Developed refineries predictive maintenance using machine learning in Databricks, Azure Machine Learning service, and Azure Machine Learning Studio.
- Built time series prediction using Keras and PyTorch for anomaly detection.
- Built time series prediction with LSTM/CNN using multivariate one-minute sensors data.
- Developed a PowerBI dashboard for mining with Fleet Management System.
- Built a sound and vibration equipment health using a convolution neural network.
- Managed external contractors to evaluate cloud technology and perform a proof-of-concept solution to common anomaly detection in time series data and apply it to all pumps in the refinery.
Senior Data Scientist2019 - 2019Western Power
- Built energy demand time series prediction with multivariate half-hourly input data using LSTM/CNN neural networks.
- Created a production solution to use forecasted weather data to forecast demand deployed to AWS Fargate.
- Project-managed through Jira tickets and code stored in Bitbucket.
Senior Spatial Engineer2016 - 2018BHP
- Helped a big mining company to take advantage of its spatial data.
- Created driver behavior analysis software for a mining operation.
- Worked with natural language processing with Keras.
- Developed various GIS projects using ArcPy and C# arcobjects.
- Created predictive models using machine learning and Apache Spark (data bricks).
- Completed a time series data analysis using Kalman filters for vehicle tracking.
- Mounted edge devices on diggers in an underground mine (Olympic Dam Mine) to classify the underground signs and determine if the bucket was full or empty.
- Built a data pipeline using Java to take data from the data logger through Kafka into the Hadoop cluster.
- Gathered requirements and met with mine managers and refineries to learn about their problems and find possible projects.
- Developed an R Shiny dashboard for mining, a hotspot of high-rack events.
Senior Algorithm Engineer2014 - 2016Fugro
- Developed image analysis software for underwater object detection.
- Processed point cloud data using C++/Python for both underwater objects and above ground.
- Created image classification for a remote sensing LiDAR point cloud using Python running in AWS and Fugro Roames for Ergon.
- Created C++ numerical algorithms for echo sounder calculation using Armadillo C++, OpenBLAS, and algorithms including Kalman filter, LAZ smoothing, and classification.
- Created various Julia and R regression machine learning applications.
Senior GIS Developer2010 - 2014Department of Mines and Petroleum
- Developed various GIS software to help surveyors in their work.
- Wrote classification and regression software for a GIS application.
- Developed GeoMap.WA, which is used to display the department's GIS products.
- Developed projects to do point cloud data analysis using ArcGIS software.
- Wrote various SQL server scripts to optimize retrieval of data.
Software Engineer2008 - 2010Western Power
- Supported GIS software to show Western Power Assets in Western Australia.
- Created predictive models for wooden pole maintenance and inspection using R.
- Developed and helped in the establishment of the wooden pole serviceability index.
- Wrote classification software for pole top fire prediction and pole serviceability index.
- Wrote Oracle scripts to download data for Oracle reports and optimize database queries.
Senior Software Engineer2006 - 2008Comsec
Technologies: T-SQL, SQL, COM+, ASP, SourceTree, Java, .NET, C++, Quantitative Finance
- Served as a senior software engineer and worked with various kinds of share trading software.
- Developed and designed NAB Equity Lending's online margin lending software.
- Supported various kinds of online trading software and managed funds.
- Created a SQL Server and Oracle database that shared procedures and database optimization.
- Participated in the design of NAB Equity Lending's migration to the Commsec Apollo project.
- Provided bug fixes and problem-solving for issues with trading software.
Senior Software Engineer2000 - 2006ERG
Technologies: T-SQL, SQL, PostgreSQL, IBM Rational Rose, Case, C#, Oracle, C++, Bash
- Wrote Various C++ and Java applications for smart rider ticketing.
- Wrote transaction processing software in C++ to run under Solaris Unix and Windows operating systems.
- Supported existing software and bug fixes, code debugging, code executing speed (profiling), and peer review.
- Generated Oracle reports for Ventura bus travel times, loading, and peak time analysis.
- Optimized various PL and SQL queries for reports using Toad and Oracle query analysis.
Postdoctoral Research Fellow1999 - 2000Columbia University, New York
Technologies: NAG Numerical Library, MATLAB, IMSL Numerical Libraries, Fortran, C++, LabVIEW, Time Series Analysis, Signal Processing, Physics Simulations, Simulations
- Conducted research on the Columbia Linear Machine (CLM) as a postdoctoral research fellow at Columbia University.
- Supervised PhD and honor students and assisted with lectures and labs.
- Worked with LabVIEW on their National Instrument (NI) products control experiment.
- Looked after the lab supplies and placed orders to maintain operations.
- Wrote signal processing software (filtering) for probe measurements to remove noise.
- Wrote scientific papers and published the results of experiments.
Postdoctoral Research Fellow1996 - 1999Flinders University of South Australia
Technologies: NAG Numerical Library, MATLAB, Fortran, LabWindows/CVI, Windows, C++, Signal Processing, Simulations
- Supervised PhD students and honour students during their studies.
- Wrote numerical analysis software for signal processing.
- Helped with lectures and lab tutorials and demonstrations.
- Maintained the lab by ordering supplies and repairs.
- Wrote scientific papers and published results of experiments.