Verified Expert in Engineering
Machine Learning Developer
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.
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.
Senior Principal Data Scientist
- 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.
Machine Learning Engineer and Data Scientist
- 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.
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.
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.
- 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.
Geo-statistician and Machine Learning Engineer
- 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.
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.
Rock Permeability Prediction Using Computer Visionhttps://patents.justia.com/patent/11182890
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 Changeshttps://patents.justia.com/patent/20210080607
This is a pending patent.
A Linear Programming Model for Production Optimization with Input Uncertaintyhttps://www.sciencedirect.com/science/article/pii/S2095268614000792
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
Python 3, Fortran, Delphi, Python, Visual Basic for Applications (VBA), R, SQL, C
LightGBM, Apache Spark, Spark
TensorFlow, Scikit-learn, Keras, XGBoost, CatBoost, Pandas, Matplotlib, PySpark, PyTorch, PyMongo, OpenCV
Linear Programming, Data Science, Parallel Programming, ETL
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)
MATLAB, Git, CPLEX, AutoML, GitHub, AutoCAD, GIS
Azure, Databricks, Google Cloud Platform (GCP), NVIDIA CUDA, Amazon Web Services (AWS), H2O Deep Learning Platform, Docker
MySQL, NoSQL, MongoDB, Google Cloud
PhD in Geo-Statistics
University of Alberta - Edmonton, AB, Canada
Professional Engineer (PENG)
The Association of Professional Engineers and Geoscientists of Alberta (APEGA)