Farid Mirahadi, PhD

Senior Manager - AI/ML @ Workday

About

An experienced professional data/ machine learning scientist with civil engineering background with a proven track record of developing advanced insight into any business aspect. 3 years civil engineering experience in Canadian mega projects in oil & gas and mining sectors. Extensive career working in data science for more than 5 years. Excellent mathematics, statistics, programming and simulation skills put into practice on a daily basis. Hands-on experience applying several ML algorithms to real-world problems: Neural Networks, Genetic Algorithm, Clustering, Regression Models, Simulation models, Baysian Belief Networks, Decision Trees and Reinforcement Learning. Analytical minded with extensive evaluation, critical thinking, and calculation skills.

Country

Canada

City

Toronto

Industry

Computer Software

Skill

Matlab, MS Project, Fortran, C/C++, Stroboscope/EZstrobe, AutoCAD, MicroCyclone, Photoshop, Microsoft Office, ETABS, SAP2000, Construction Management, Structural Analysis, Civil Engineering, Primavera P6, Data Analysis, Surveying, Access, Project Management, Project Estimation

Experience

Senior Manager - AI/ML

Workday

2026-5 - Present · 5 mos

Toronto, ON

Senior Manager - Machine Learning

Procore Technologies

2024-1 - 2026-4 · 2 yrs 4 mos

Toronto, ON

Principal Machine Learning Engineer

Procore Technologies

2021-5 - 2024-1 · 2 yrs 9 mos

Toronto, ON

Senior ML/CV Scientist

INDUS.AI (Acquired by Procore Technologies)

2021-5 - 2021-7 · 3 mos

Toronto, Ontario, Canada

Machine Learning Scientist

INDUS.AI (Acquired by Procore Technologies)

2019-10 - 2021-4 · 1 yr 7 mos

Machine Learning Intern

INDUS.AI (Acquired by Procore Technologies)

2019-4 - 2019-10 · 7 mos

Toronto, Canada Area

Researcher / Machine Learning Scientist

University of Toronto

2016 - 2019-11 · 3 yrs

Toronto, Canada Area

Development of a real-time smart evacuation management system for high-rise buildings by merging and interfacing Python, BIM, IoT sensors and agent-based crowd simulation

Data Analyst

Pacer Promec Energy Corp.

2014-5 - 2016-8 · 2 yrs 4 mos

Calgary, Canada Area

Data Scientist / Machine Learning Engineer

Concordia University

2013-1 - 2014-4 · 1 yr 4 mos

Montreal, Quebec

• Developed a neural-network driven fuzzy reasoning model to forecast the productivity of construction operations based on managerial, environmental and operational historical data (MATLAB/Python) • Optimized the model with genetic algorithm for more accuracy (12 %) and faster computation • Methods applied: Fuzzy logic, ANN, C-means clustering, statistical fit tests, decision trees, alpha-cut technique • Enhanced the model to work with both qualitative and quantitative variables and datasets

Teaching Assistant, Surveying Course

Concordia University

2012-5 - 2013-8 · 1 yr 4 mos

• Instruction of the theoretical concepts of the fundamental surveying tasks to civil engineering bachelor students • Supervision and guidance of the trainees during fulfillment of the daily labs in the field • Helping students to map the plans and topology of the whole campus of Concordia University using total station, theodolite, AutoCAD and etc.

Teaching Assistant, Strength of Materials

Concordia University

2013-1 - 2013-4 · 4 mos

• Presentation of the theoretical concepts of the mechanics of materials syllabus offered in the course • Overseeing the students for performing the experiments due in every session

Data Scientist / Machine Learning Engineer

QatarEnergy

2012-1 - 2012-12 · 1 yr

Montreal, Canada Area

• Improved the process of variable selection, data cleaning, anomaly detection and classification of collected data from oil and gas pipelines • Developed a forecasting model for deterioration of oil and gas pipelines based on regression and ANN techniques (MATLAB/Python/R) • Methods applied: ANN, regression, variable selection, KNN, statistical fit tests, decision trees, Monte Carlo simulation • Programed a graphical user interface (GUI) for automation of oil and gas pipeline condition assessment, cost estimation and maintenance strategy selection (MATLAB/Python) • Created reports based on findings to be presented to executives at monthly meetings, making recommendations for improvement in addition to raw information.