Nahid Ghofrani

Nahid Ghofrani Email:-https://www.linkedin.com/in/nahid-ghofrani/ Phone:- Calgary, AB T3H 2Z6 Summary Data scientist with experience in machine learning, image processing and quantitative analytics. Analytical and result-oriented with effective verbal and written communication, technical presentation and self-management skills. Qualification Data Mining, Machine learning and Deep Learning (Neural Networks, Decision Forests, SVM) Data Visualization: Tableau, PowerBI Quantitative analysis and mathematics Computer programming: Python, C++, OpenCV, MATLAB, SQL Python libraries: Pandas, Numpy, SciPy, Scikit-learn, TensorFlow Education M.Eng. Electrical Engineering, 2014 University of Calgary, Calgary, AB B.Sc., Electrical Engineering-Electronics, 2006 Isfahan University of Technology, Isfahan, Iran Certificates (On campus) Data Science Certificate, 2019 Northern Alberta Institute of Technology (NAIT) Python Programming Certificate of Completion, 2019 Southern Alberta Institute of Technology (SAIT) Professional Experience Data Scientist, 2019-Present Alberta Environment and Parks, Calgary, AB Identify the most accurate global climate models (GCM) to forecast Alberta climate change Analyzed large datasets and extracted parameters from expert team of climate change detection and indices (ETCCDI) Developed a Python program to compare two mathematical algorithms and identify the best model with maximum climate change coverage by using convex hull method Developed a Python program to identify the most accurate model for forecasting climate change by using Hidden Markov, Bayesian and Maximum Likelihood algorithms Image Processing Researcher, Computer Science Department, 2017 University of Calgary, Calgary, AB Detection and elimination of mirroring artifacts in four dimensional MRI (4D-Flow MRI) images Improved data processing performance by converting 4D geometrical model data into 2D model using stretched curved planar reformation (CPR) method Improved image quality by 60% using a mathematical search algorithm to eliminate data redundancy in 4D to 2D converted geometrical models Research Assistant,- Electrical Engineering Department, University of Calgary, Calgary, AB Create an indoor locating method using image processing Created a method to locate the image acquisition device using Bayesian machine learning method on image data set Improved indoor locating accuracy up to 90% by combining Lucas Pyramids and Hough image processing methods Teaching Assistant,- Electrical Engineering Department, University of Calgary, Calgary, AB Electrical Engineer,- Negin Espadana Mining and Mineral Processing Co., Isfahan, Iran Improved electromagnetic iron separator efficiency up to 25% by conducting research on modification of electrical and mechanical adjustment components Conducted a business process analysis project to design a real time monitoring system for a mineral processing factory on time and within the budget Machine Learning and Signal Processing Researcher,- Isfahan University of Technology, Isfahan, Iran Design a diagnostic platform for computer-aided cervical cancer detection Created the best data sets as an input for the machine learning process by applying feature extraction methods and Genetic algorithm Researched for the most accurate method for image classification by comparing Neural Networks, Support Vector Machines, and Clustering machine learning methods Designed a diagnostic application to automate image capturing, processing and classification with 93% accuracy in cancer stage diagnosis Other Experience Store Manager, 2018 SoftMoc, Calgary, AB Store Manager,- Naturalizer, Calgary, AB