Behrang Koushavand, Machine Learning Developer in Calgary, AB, Canada
Behrang Koushavand

Machine Learning Developer in Calgary, AB, Canada

Member since July 6, 2022
Behrang is a geo-statistician, data scientist, and professional engineer with 10+ years of industry experience. He has deep knowledge of multivariate statistics and industry scale optimization algorithms, classical machine learning, deep learning, and computer vision. Behrang has participated in 30+ Kaggle competitions and has experience with different types of data and ML algorithms.
Behrang is now available for hire

Portfolio

  • NielsenIQ
    Amazon Web Services (AWS), Geospatial Data, Geospatial Analytics, Python, SQL...
  • Cenovus Energy
    Azure, Databricks, PySpark, Computer Vision, Python, SQL, NoSQL, MongoDB...
  • Husky Energy
    Python 3, R, TensorFlow, Azure, PySpark, PyTorch, Python, SQL...

Experience

Location

Calgary, AB, Canada

Availability

Full-time

Preferred Environment

Python 3, Fortran, Azure, AWS, Python, Keras

The most amazing...

...achievement I've accomplished is to be granted a patent on the application of computer vision in oil and gas reservoir characterization.

Employment

  • Senior Principal Data Scientist

    2022 - PRESENT
    NielsenIQ
    • Contributed to various advanced analytics projects related to geospatial data analytics projects, route-to-market, and precision.
    • Implemented a novel method for sales distribution using the linear optimization technique.
    • Implemented parallel programming for various existing codes to increase the efficiency of the current methods.
    Technologies: Amazon Web Services (AWS), Geospatial Data, Geospatial Analytics, Python, SQL, PySpark, GIS, Parallel Programming, Spark, ETL, Apache Spark, Data Engineering, Pandas, Data Wrangling, Datasets
  • Machine Learning Engineer and Data Scientist

    2020 - PRESENT
    Cenovus Energy
    • Developed several ML algorithms and shiny apps deployed to RS-connect, including a deep learning model to classify valid DTS shut-in, linear failure analysis, and predictions of the depth of geological formations using CNN.
    • Supervised a data science co-op student on various projects.
    • Co-supervised a master's student at the University of Alberta on using ML methods to predict spatial continuity parameters from data.
    Technologies: Azure, Databricks, PySpark, Computer Vision, Python, SQL, NoSQL, MongoDB, Facial Recognition, Keras, Convolutional Neural Networks, Object Detection, Cloud Infrastructure, Natural Language Processing (NLP), Artificial Intelligence (AI), Machine Learning, Visual Basic for Applications (VBA), Linear Regression, Linear Optimization, Parallel Programming, Git, Scikit-learn, GeoPandas, Geology, TkInter, AutoML, TensorFlow, Algorithms, Data Science, Cloud, Neural Networks, ETL, Apache Spark, Data Engineering, Image Processing, 3D Image Processing, Pandas, Docker, Data Wrangling, Datasets, Simulations, Physics Simulations
  • Geo-statistician and Machine Learning Engineer

    2012 - 2020
    Husky Energy
    • Developed several predictive models for subsurface data using classical machine learning algorithms and a deep learning framework.
    • Filed two patents—one has been granted, and the second is in process.
    • Led a team of four technical individuals to develop a framework and a dashboard for resource estimation and prediction.
    • Built 3D numerical models to characterize reservoir and uncertainty analysis.
    • Taught several machine learning courses in the company.
    • Received the best presentation award at the Husky tech forum. Presented three new workflows and ML models on subsurface data.
    Technologies: Python 3, R, TensorFlow, Azure, PySpark, PyTorch, Python, SQL, Facial Recognition, Keras, Convolutional Neural Networks, Object Detection, Amazon Web Services (AWS), Cloud Infrastructure, Google Cloud Platform (GCP), Natural Language Processing (NLP), Artificial Intelligence (AI), Machine Learning, Visual Basic for Applications (VBA), Linear Regression, Linear Optimization, Parallel Programming, Git, Scikit-learn, GeoPandas, Geology, TkInter, Computer Vision, Algorithms, Data Science, Team Leadership, Cloud, Neural Networks, Pandas, Data Wrangling, Datasets, Simulations, Physics Simulations
  • Research Assistant

    2007 - 2012
    University of Alberta
    • Developed a novel workflow to measure geological uncertainty at long-term production optimization and published several papers on this subject.
    • Published several peer-reviewed and conference papers about geostatistical methods in mining and oil and gas engineering.
    • Acted as a teacher assistant in a few university courses, including reserve estimation methods.
    • Acted as a software developer for Newmont Mining Corp, Denver, USA.
    Technologies: Research, Programming, R, MATLAB, Python, Fortran, Data Science, Geology, Engineering, Linear Programming, Parallel Programming, Algorithms, Pandas, Algebra, Convex Optimization, Optimization Algorithms, Data Wrangling, Datasets, Simulations, Physics Simulations

Experience

  • Rock Permeability Prediction Using Computer Vision
    https://patents.justia.com/patent/11182890

    I developed a workflow to estimate the permeability ratio using rock photos and computer vision. I simulated a lot of synthetic images and trained a deep learning model.

    Later, I built a standalone app deployed at the company for all of the users.

    This workflow has been patented.

  • Computer Vision to Detect Reservoir Changes
    https://patents.justia.com/patent/20210080607

    I developed a framework to automatically detect reservoir changes over time using 4D seismic data. In this project, a 2.5D image segmentation framework was developed to detect 3D reservoir changes over time.

    This is a pending patent.

  • A Linear Programming Model for Production Optimization with Input Uncertainty
    https://www.sciencedirect.com/science/article/pii/S2095268614000792

    I developed a technique to maximize the net present value of a long-term production plan in the presence of uncertainty and a stockpile. The model was a mixed-integer linear optimization problem. A paper was published on the topic.

  • Kaggle Competitions
    https://www.kaggle.com/behrang

    I have been involved in some Kaggle competitions. I have achieved Kaggle Master and was part of the top 10%.

    Some of the competitions were:

    • Homesite Quote Conversion: Which Customers Will Purchase a Quoted Insurance Plan?
    • Rossmann Store Sales: Forecast Sales Using the Store, Promotion, and Competitor Data
    • Google Landmark Retrieval $ Recognition 2020
    -HuBMAP - Hacking the Kidney: Identify Glomeruli in Human Kidney Tissue Images
    -The Winton Stock Market Challenge
    -G2Net Gravitational Wave Detection: Find Gravitational Wave Signals from Binary Black Hole Collisions

Skills

  • Languages

    Python 3, Fortran, Delphi, Python, Visual Basic for Applications (VBA), R, SQL, C
  • Frameworks

    LightGBM, Apache Spark, Spark
  • Libraries/APIs

    TensorFlow, Scikit-learn, Keras, XGBoost, CatBoost, Pandas, PySpark, PyTorch, PyMongo
  • Paradigms

    Linear Programming, Data Science, Parallel Programming, ETL
  • Other

    Computer Vision, Geology, TkInter, Machine Learning, Deep Learning, Integer Programming, Optimization, Geospatial Analytics, Engineering, Facial Recognition, Convolutional Neural Networks, Object Detection, Artificial Intelligence (AI), Linear Regression, Linear Optimization, University Teaching, Algorithms, Neural Networks, 3D Image Processing, Datasets, GeoPandas, Natural Language Processing (NLP), AWS, Cloud Infrastructure, Team Leadership, Cloud, Machine Vision, Image Processing, Algebra, Convex Optimization, Optimization Algorithms, Data Wrangling, Simulations, Physics Simulations, GPU Computing, Research, Programming, Geospatial Data, Data Engineering, Chatbots, OCR
  • Tools

    MATLAB, Git, CPLEX, AutoML, GIS
  • Platforms

    Azure, Databricks, Google Cloud Platform (GCP), Amazon Web Services (AWS), H2O Deep Learning Platform, Docker
  • Storage

    MySQL, NoSQL, MongoDB, Google Cloud

Education

  • PhD in Geo-Statistics
    2007 - 2012
    University of Alberta - Edmonton, AB, Canada

Certifications

  • Professional Engineer (PENG)
    DECEMBER 2014 - PRESENT
    The Association of Professional Engineers and Geoscientists of Alberta (APEGA)

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