Master of Engineering graduate specializing in power system analysis, protection & control, renewable/EV grid integration, and AI-driven predictive modeling.
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About
My work focuses on power systems analysis, protection & control, and utility-scale integration, including substation single-lines, three-line schematics, short-circuit studies, and relay coordination. Using MATLAB, Simulink, and Simscape Electrical, I model grid-connected solar PV generation and EV charging infrastructure to analyze feeder loading, system stability, and transient behavior under variable grid conditions. Complementing core utility design, I develop Python-based machine learning pipelines for predictive maintenance and asset monitoring, delivering data-driven solutions that enhance equipment reliability and grid resilience.
Core Utility & Substation Focus
Protection & Control Schematics, Relay Coordination, Short-Circuit Analysis, AutoCAD Electrical
Grid-Connected PV & EV Systems, Feeder Capacity & Loading Analysis, MATLAB / Simulink / Simscape Electrical
Predictive Maintenance, Anomaly Detection, Machine Learning, Python (Pandas, NumPy)
University of Windsor
GPA 3.9 / 4.0
Gujarat Technological University
Experience
Engineering Projects
Simulation studies, protection analysis, automation logic, and applied machine learning.
Designed a 3-phase grid network simulation in MATLAB, Simulink, and Simscape Electrical integrating solar PV and EV charging stations. Evaluated network stability, feeder loading, and smart charging strategies for utility readiness.
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Modeled lithium-ion battery SOC estimation and dynamic load behavior under UDDS and US06 driving cycles reaching 80 kW peak load using MATLAB/Simulink.
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Published research on integrating augmented reality with predictive maintenance in Industry 4.0 environments for anomaly detection.
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1st Place Winner: spoken-language recognition from mel-spectrograms using an InceptionV3 CNN — 99.67% validation and 100% held-out test accuracy across English, Gujarati, and Hindi.
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120-hour civic data project: analyzed Statistics Canada Census 2016 & 2021 and CMHC rental data in Python/Pandas to show renters carry ~2.2× the owner burden and mid-size cities now top the high-STIR list.
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Certifications & Leadership
Validated foundational AI/ML concepts and cloud services on AWS.
Data analytics, visualization, and civic reporting for community programs.
Skills
Schedule
Open to power systems, protection & control, and grid modernization roles across Canada. Pick a slot that works for you.
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