Ibrahim Mahmoud Ahmed, Ph.D., Machine Learning Developer in Perth, Western Australia, Australia
Ibrahim Mahmoud Ahmed, Ph.D.

Machine Learning Developer in Perth, Western Australia, Australia

Member since April 22, 2019
Ibrahim is a veteran data scientist and software developer with a passion for deep learning and extensive experience in statistics and time-series. He is interested in helping businesses to take full advantage of their data and make data-driven actions.
Ibrahim is now available for hire




Perth, Western Australia, Australia



Preferred Environment

Jupyter Notebook, Windows 10, Ubuntu, Google Cloud Platform (GCP), Azure, AWS

The most amazing...

...ship berthing project I've developed for a mining company used SPLATNeT, an enabled hierarchical and spatially aware feature detection to be used by AR.


  • Machine Learning Expert for Data Science POC

    2021 - PRESENT
    • Designed and developed data processing pipelines to take 100hz data to train and evaluate models. Files were very big and used bcolz data generator.
    • Developed an autoencoder to detect anomalies in torque and current readings for a production mill. Trained autoencoder on non-event data, found what is not matching behavior as an event.
    • Built a solution with MQTT to obtain data and perform inference.
    • Supervised other developers to work on deployment and built similar models.
    Technologies: TensorFlow, Keras, Variational Autoencoders, Anomaly Detection
  • GIS Platform Architect/Engineer

    2021 - PRESENT
    Birch Infrastructure, PBLLC
    • 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.
    Technologies: Python, Data Building Tool (DBT), Prefect, ArcGIS
  • Developer

    2020 - PRESENT
    Toptal Client
    • 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.
    Technologies: Language Models, BERT, Natural Language Processing (NLP), Python 3, PyTorch
  • Machine Learning to Build Seismic Activity Classifier

    2019 - PRESENT
    Toptal Project
    • 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.
    Technologies: Computer Vision, Deep Learning, Dlib, OpenCV, Qt, C++, PyTorch, TensorFlow, Keras, Python
  • Machine Learning Consultant

    2015 - PRESENT
    Global Unmanned System
    • 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 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 problem and find possible projects.
    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, Scikit-learn, XGBoost, Keras, OpenCV, R, Python
  • Senior Data Scientist

    2018 - 2020
    Freelance Work
    • 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.
    Technologies: Transformer Models, Language Models, BERT, 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
  • Senior Data Scientist

    2019 - 2019
    Western Power
    • Built energy demand time series prediction, using multivariate half-hourly input data using LSTM/CNN neural networks.
    Technologies: ArcGIS Runtime SDK for .NET, Data Science, GIS, Agile Software Development, Artificial Intelligence (AI), TensorFlow, Keras, Python
  • Senior Spatial Engineer

    2016 - 2018
    • Helped big mining company to take advantage of its spatial data.
    • Created driver behavior analysis software for mining operation.
    • Worked with natural language processing with Keras.
    • Developed various GIS projects using ArcPY, C#.
    • Created predictive models using machine learning.
    • Completed time series data analysis.
    • Mounted edge devices on diggers in underground mine (Olympic Dam Mine) to classify the underground signs and determine if the bucket is full or empty.
    • Built data pipeline using Java to take data from data logger through Kafka into Hadoop cluster.
    • Gathered requirements, and me with mine managers and refineries to learn their problems and find possible projects.
    • Developed R/Shiny dashboard for mining, hots pot of high rack events.
    Technologies: Amazon Web Services (AWS), Cloudera, Hortonworks Data Platform (HDP), OSI Model, Data Engineering, Point Clouds, RStan, ArcGIS GeoEvent Server, 3D Image Processing, Redshift, Spotfire, Microsoft Power BI, Hadoop, ArcGIS Runtime SDK for .NET, GIS, SQL, Agile Software Development, Statistical Learning, RStudio Shiny, Kibana, Elasticsearch, AWS, Oracle, Microsoft SQL Server, Git, Apache Kafka, C#, ArcPy, Keras, Python, Esri
  • Senior Algorithm Engineer

    2014 - 2016
    • Developed Image analysis software for underwater object detection.
    • Processed point cloud data using C++/Python.
    • Created an image classification for remote sensing lidar point cloud using Python running in AWS - Fugro Roames for Ergon.
    • Created C++ numerical algorithms for echo sounder calculation.
    • Created various Julia and R regression algorithms.
    Technologies: Amazon Web Services (AWS), Data Engineering, Point Clouds, ArcGIS Runtime SDK for .NET, GIS, SQL, Artificial Intelligence (AI), Statistical Learning, MATLAB, Julia, Esri, Oracle, Microsoft SQL Server, Git, AWS, Python, C++
  • Senior GIS Developer

    2010 - 2014
    Department of Mines and Petroleum
    • Developed various GIS software to help surveyors in their work.
    • Wrote classification and regression software.
    • Developed GeoMap.WA which is used to display the department GIS products.
    • Completed point cloud data analysis.
    • Wrote various SQL server scripts to optimize retrieval of data.
    Technologies: ArcPy, .NET, GIS, SQL, Microsoft SQL Server, Microsoft Team Foundation Server, TeamCity, Git, R, Python, GPS, Esri, C#
  • Software Engineer

    2008 - 2010
    Western 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 wooden pole serviceability index.
    • Wrote classification software.
    • Wrote Oracle scripts to download data for Oracle reports and optimize database queries.
    Technologies: SQL, Java, SourceTree, Oracle, C++, C#, R
  • Senior Software Engineer

    2006 - 2008
    • 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.
    Technologies: T-SQL, SQL, COM+, ASP, SourceTree, Java, .NET, C++
  • Senior Software Engineer

    2000 - 2006
    • Wrote Various C++, Java Applications for smart rider ticketing.
    • Wrote transaction processing software.
    • Supported existing software and bug fixes.
    • Generated Oracle reports.
    • Optimized various PL/SQL queries for reports.
    Technologies: T-SQL, SQL, PostgreSQL, IBM Rational Rose, Case, C#, Oracle, C++
  • Post Doctor

    1999 - 2000
    Columbia University, New York
    • 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.
    Technologies: NAG Numerical Library, MATLAB, IMSL Numerical Libraries, Fortran, C++, LabVIEW
  • Post Doctor

    1996 - 1999
    Flinders University of South Australia
    • 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.
    Technologies: NAG Numerical Library, MATLAB, Fortran, LabWindows/CVI, Windows, C++


  • Automatic Processing of Mine Micro-Seismic: Application to the Oyu Tolgoi Mine

    We've developed an automatic processing system that outperforms the analysts for routine processing in terms of processing quality and speed. Our processing scheme mixes novel approaches and a more traditional method relying on the energy variation based event detection and on the picking of arrival times. Our platform directly employs the raw events detected by the seismic system. The event detection is set to be highly sensitive. When an event is detected, a block of continuous data is extracted and the event is located using a grid-based event location method. It classifies the event into ten categories, picks the arrival times, locates the events, and calculates the source parameters. The Oyu Tolgoi mine is currently using this system to process data in a production setting. The system is deployed on Kubernetes clusters. Automatically processing seismic data requires the adoption of a holistic approach that extends to the design of the seismic array, the choice of sensors and the type and shape of the input data.

    Using convolution neural networks, mixed networks with other features available, an automatic seismic identifier was created that outperforms other models in the market.

  • Electricity Demand Prediction

    Electricity demand prediction using current population categories, and weather condition, help companies to plan their usage of electricity to reduce cost.

    Western Power had a hack-a-gig competition to help them use their smart meter collected data, weather conditions and population categories to determine their electricity demand. This helps clients to achieve minimum cost and help western Power to plan their electricity network.

    My solution was the winning solution and was written in Python, using Keras for neural network, and used Mixed input model neural network which consisted of the following inputs:
    1. Embedding of categorical fields like household categories, days to public holidays, days after a public holiday (up to 5 days).
    2. Tabular numerical data for weather condition.
    3. LSTM of the previous usage pattern of electricity.

    These inputs were then concatenated into a fully connected deep neural network with one output variable to estimate the current usage of electricity per household. The data is then aggregated, to reduce error by localities. My solution gave the best result in the competition and I won the best reward in the competition and contracted with Western Power to do the project.

  • Driver Behavior Analysis

    BHP mines have a large number of haul trucks, light vehicles, dozers, excavators, and others. There is a need to detect when drivers exceed the speed limit, do harsh breaking, and take turns at high speed. These events lead to fast wear of tires and required coaching drivers to stop doing that. Light vehicles should not approach haul trucks less than 50m unless they have positive communication since the haul truck driver may not be able to see the light vehicle. Detecting these events helps increase safety in mines.

    I wrote a C# application to collect GPS location data from various sources streamed through Kafka and then calculate the speed and orientation and using Kalman filter to reduce error in the GPS measurements and I stored the data in Elasticsearch spatiotemporal database. I then used this data to determine events using Elasticsearch database. I was the lead developer in the project.


  • Languages

    C++, C#, R, Python, SQL, Python 3, T-SQL, Java, Fortran, SPARQL
  • Frameworks

    .NET, Hadoop, RStudio Shiny, Qt
  • Libraries/APIs

    PyTorch, Keras, TensorFlow, ArcGIS, OpenCV, Scikit-learn, Dlib, Fast.ai
  • Tools

    GIS, Esri, Azure Machine Learning, MATLAB, Amazon SageMaker, ArcGIS Runtime SDK for .NET, Microsoft Power BI, Spotfire, Kibana, Azure ML Studio, Cloudera, Git, LabWindows/CVI, Protégé
  • Paradigms

    Agile Software Development, Data Science, Functional Programming, Anomaly Detection
  • Platforms

    Ubuntu, Azure, Jupyter Notebook, Oracle, Windows, Amazon Web Services (AWS), Linux, ArcGIS Server, Apache Kafka, Kubernetes, Databricks, Hortonworks Data Platform (HDP), Google Cloud Platform (GCP)
  • Storage

    Microsoft SQL Server, Elasticsearch, MySQL, PostgreSQL, AWS S3, PL/SQL, Redshift
  • Other

    Artificial Intelligence (AI), Deep Learning, Statistical Learning, ArcGIS GeoEvent Server, ArcPy, Predictive Analytics, RStan, Image Processing, 3D Image Processing, RSelenium, AWS, Uniformance Process History Database (PHD), OSI Model, Point Clouds, Reinforcement Learning, Data Engineering, Generative Adversarial Networks (GANs), NAG Numerical Library, Graph Neural Networks, Windows 10, GPS, BERT, Transformer Models, TAPAS, Natural Language Processing (NLP), OWL2, Computer Vision, Data Building Tool (DBT), Prefect, Variational Autoencoders


  • Master's Degree in Actuarial Science
    2010 - 2016
    Curtin University - Perth, Western Australia
  • Graduate Diploma in GIS
    2009 - 2010
    Curtin University - Australia
  • Ph.D. in Science and Engineering
    1992 - 1996
    Flinders University - Australia, Adelaide


  • Google Associate Cloud Engineer
    MARCH 2020 - MARCH 2022
    Google Cloud
  • Artificial Intelligence Nanodegree
    JULY 2017 - PRESENT

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