Behrang is available for hire

Behrang Koushavand

Verified Expert in Engineering

Machine Learning Developer

Location

Calgary, AB, Canada

Toptal 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.

Artificial Intelligence (AI)Algorithms Machine Learning Computer Vision Deep Learning Visual Basic for Applications (VBA)Fortran Keras Python 3 TensorFlow Delphi Python Pandas Data Wrangling User Interface (UI)

Portfolio

NielsenIQ

Amazon Web Services (AWS), Geospatial Data, Geospatial Analytics, Python, SQL...

Cenovus Energy

Azure, Databricks, PySpark, Computer Vision, Python, SQL, NoSQL, MongoDB...

Zebra Analytics, LLC

Artificial Intelligence (AI), Generative Adversarial Networks (GANs)...

Experience

Machine Learning - 10 years Computer Vision - 5 years Scikit-learn - 5 years TensorFlow - 5 years Deep Learning - 5 years Python 3 - 5 years Generative Pre-trained Transformers (GPT) - 3 years Natural Language Processing (NLP) - 3 years

Availability

Part-time

Preferred Environment

Python 3, Fortran, Azure, Amazon Web Services (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.

Work Experience

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, Matplotlib, ChatGPT, OpenAI, OR-Tools, Consulting, Minimum Viable Product (MVP), APIs, Python 3, Git, Scikit-learn, Azure, GeoPandas, CPLEX, Integer Programming, Optimization, Databricks, Artificial Intelligence (AI), Convex Optimization, Optimization Algorithms, GitHub

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, Generative Pre-trained Transformers (GPT), GPT, 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, User Interface (UI), Matplotlib, GitHub, 3D, OR-Tools, Minimum Viable Product (MVP), Python 3, Deep Learning, Geospatial Analytics, Engineering, GPU Computing, Graphics Processing Unit (GPU), NVIDIA CUDA, Image Recognition

AI Developer

2023 - 2023

Zebra Analytics, LLC

Trained for TensorFlow to detect different elements from the plan.
Deployed a model to the GCP server for training and inference.
Created a web app using Flask and deployed it with a Docker container into a GCP VM.
Helped and mentored a client with their first cloud solution (GCP).
Wrote 8 Jupyter notebooks to pre-process the images, train the models, and evaluate the results and a stand-alone notebook to make inferences on new data.
Helped a client to collect the data and annotate it to achieve their goal.

Technologies: Artificial Intelligence (AI), Generative Adversarial Networks (GANs), Convolutional Neural Networks, Algorithms, OR-Tools, Optimization, Optimization Algorithms, Python, Neat, Generative Design, Python 3, TensorFlow, Git, Computer Vision, Deep Learning, Keras, Object Detection, Cloud Infrastructure, Google Cloud Platform (GCP), GPU Computing, Google Cloud, Cloud, Image Processing, Docker, User Interface (UI), GitHub, Graphics Processing Unit (GPU), Vertex, NVIDIA CUDA

AI Developer

2023 - 2023

Zebra Analytics, LLC

Reviewed literature on the subject of generative plans and layout generation and devised out-of-shelf temporary solutions.
Ran two inferences using a publicly available trained model on custom data.
Provided a plan for the next step, guided the customer on how to label their data, and helped them prepare their custom dataset for the next step.

AI Specialist

2023 - 2023

Oluwadolapo Obatoyinbo

Defined a few projects for the client for an AI and computational geoscience software prototype and wrote and explained each step. Assisted the client in collecting the data and preparing for the next step.
Prepared documents and communicated several technical details.
Presented the team with a clear scope of the work and guided them through different technical processes.

Technologies: Datasets, Machine Learning, Deep Learning, Simulations, Physics Simulations, 3D Modeling, Consulting

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: 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), GPT, Generative Pre-trained Transformers (GPT), 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, User Interface (UI), GitHub, 3D, OR-Tools, Minimum Viable Product (MVP), 3D Modeling, 3D CAD, Python 3, Deep Learning, Integer Programming, Optimization, Geospatial Analytics, Engineering, GPU Computing, GIS, Graphics Processing Unit (GPU), Image Recognition, OpenCV

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, OR-Tools, 3D Modeling, 3D CAD, Integer Programming, Optimization, Artificial Intelligence (AI), Graphics Processing Unit (GPU)

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, Matplotlib, PySpark, PyTorch, PyMongo, OpenCV

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), Cloud Infrastructure, Team Leadership, Cloud, Machine Vision, Image Processing, Algebra, Convex Optimization, Optimization Algorithms, Data Wrangling, Simulations, Physics Simulations, User Interface (UI), 3D, GPT, Generative Pre-trained Transformers (GPT), OR-Tools, Consulting, 3D Modeling, 3D CAD, Graphics Processing Unit (GPU), Vertex, Image Recognition, GPU Computing, Research, Programming, Geospatial Data, Data Engineering, Chatbots, OCR, ChatGPT, OpenAI, Minimum Viable Product (MVP), APIs, Generative Adversarial Networks (GANs), Neat, Generative Design, Augmented Reality (AR)

Tools

MATLAB, Git, CPLEX, AutoML, GitHub, AutoCAD, GIS

Platforms

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

Storage

MySQL, NoSQL, MongoDB, Google Cloud

Education

2007 - 2012

PhD in Geo-Statistics

University of Alberta - Edmonton, AB, Canada

Certifications

DECEMBER 2014 - PRESENT

Professional Engineer (PENG)

The Association of Professional Engineers and Geoscientists of Alberta (APEGA)