nima safari

Electrical Professional Engineer (P.Eng.) with specialization in Power Systems and Machine Learning with over 5 years of experience in power system operation and planning and machine learning.

Nima adopts various regression, classification and clustering approaches (Extreme Learning Machine, Neural Networks, Deep Learning, Random Forest, Generalized Linear Models, k-Means Clustering), as well as advanced statistical analysis concepts (Information Theory), to solve a wide range of problems.

During both education and industrial career, Nima has gained extensive experience in power system software (PSS®E, ETAP and PSCAD), optimization software (CPLEX), power system optimization software (PLEXOS), programming languages (intermediate Python, Visual Basic, advanced MATLAB, fundamental SQL, intermediate C++), machine learning and deep learning libraries (Keras and Scikit-learn), text mining and image recognition libraries (Tesseract and OpenCV).