Engineering Projects & Technical Portfolio
Engineering Projects & Technical Portfolio
My Ph.D. research focuses on GaN-based power converters, electromagnetic interference (EMI/EMC), converter control, PCB design, simulation, experimental validation, and data-driven modeling. As part of this research, I have designed and simulated single-phase and three-phase inverter systems using MATLAB/Simulink and ANSYS Simplorer, enabling investigation of converter operation, switching behavior, control strategies, and system-level performance.
For the experimental GaN converter platform, I have worked with the Si8271 isolated gate-driver IC and implemented PWM and control signals using the ESP32 microcontroller. I have also used Rigol laboratory signal-generation and measurement equipment to generate and evaluate square-wave/PWM signals for the investigation of different switching and control strategies.
In addition to ESP32-based implementation, I have experience programming STM32 microcontrollers, providing practical exposure to embedded control platforms commonly used in power electronics and industrial applications.
For software development and engineering analysis, I use Visual Studio Code for ESP32, embedded systems, and Python development. Python has been extensively applied to:
Common-mode (CM) EMI analysis
Fast Fourier Transform (FFT) and frequency-domain analysis
Processing experimental and simulation data
Engineering calculations and automated data processing
Scientific and publication-quality plotting
Development and evaluation of data-driven and machine-learning models
The research also includes the implementation of machine-learning techniques within a hardware-based power-converter modelling and validation framework, where experimental and simulated converter data are used to support intelligent analysis and performance evaluation. Further technical details of this work will be added after the associated research is published.I have also developed a collection of reusable Python engineering plotting and data-analysis examples, available through my public GitHub repository.
My Ph.D. work further includes the design, simulation, PCB implementation, and experimental testing of GaN-based DC–DC power-converter prototypes, including PWM control, gate-driver circuits, parasitic analysis, EMI mitigation, embedded control, machine-learning-assisted analysis, and validation of simulation models against experimental measurements.
My master's research focused on power-system modeling, renewable-energy integration, and transmission-grid analysis using ETAP.
The research was based on modeling the Jhampir wind-power transmission network in Pakistan, incorporating generation data from approximately 16–18 wind power plants connected within the region. Using ETAP, I performed power flow and grid performance analyses under different operating conditions to evaluate the influence of large-scale wind power generation on the transmission network. The study also investigated the planned expansion of the grid through the addition of a 250 MVA transformer to support the development and reinforcement of the 220/132 kV transmission system.
The work included:
ETAP-based transmission-network modelling
Integration of multiple wind-power plants
Power-flow analysis
Bus-voltage and loading assessment
Transformer-loading analysis
Evaluation of different grid operating conditions
Analysis of transmission-system expansion
Assessment of renewable-energy integration into the power grid
This research provided substantial experience in power-system planning, renewable-energy integration, transmission networks, and electrical-grid simulation.
My Bachelor’s project focused on industrial power-system operation, demand-side management, PLC-based automation, and load-priority control.
The project considered an electrical distribution system from an approximately 11 kV industrial supply network to individual consumer/load groups. Power-flow and operating scenarios were analyzed to understand system behavior under different generation and load conditions. A hardware prototype was developed using a Delta PLC, for which I programmed approximately 8–10 pages of Ladder Logic to implement automatic load management and switching strategies.
The controller was designed to respond to different levels of available generation and grid constraints. Load-shedding scenarios of approximately 10%, 20%, 30%, and 40% were implemented according to predefined load priorities. The control philosophy ensured that critical, industrial, and priority loads remained supplied for as long as system conditions permitted, while lower-priority loads were progressively disconnected.
The prototype also considered:
Normal grid operation
Different levels of load shedding
Priority-based load switching
Industrial and critical-load protection
Partial grid disturbances
Complete blackout conditions
Sequential restoration of electrical loads
Grid recovery and resynchronization scenarios
This project provided practical experience in PLC programming, ladder logic, demand-side management, power-system operation, automation, protection logic, and electrical load management, particularly for grids where generation shortages and scheduled load shedding can significantly influence system operation.
I have also worked on the design and implementation of an industrial induction-motor protection system, which subsequently resulted in a research publication. The project involved protection logic, sensing and measurement, control implementation, fault detection, interfacing, and experimental validation.
My academic and research work has provided practical experience across:
Power Electronics:
GaN converters, DC–DC converters, single-phase and three-phase inverters, PWM control, gate drivers, switching analysis, PCB development, and converter testing.
Control and Embedded Systems:
ESP32, STM32, Delta PLC, Ladder Logic, PWM generation, embedded programming, converter control, and automated switching systems.
Power Systems:
ETAP, transmission and distribution networks, 220/132 kV substations, wind-power integration, power-flow studies, transformers, demand-side management, and load shedding/restoration.
Simulation and Engineering Software:
MATLAB/Simulink, ANSYS Simplorer, ANSYS Q3D, ANSYS HFSS, ETAP, Python, and Visual Studio Code.
Data Analysis and Programming:
Python-based FFT analysis, common-mode EMI evaluation, engineering calculations, automated data processing, visualization, and publication-quality scientific plotting.
Experimental Engineering:
PCB prototyping, laboratory measurements, signal generation, converter testing, EMI/EMC evaluation, hardware debugging, and validation of simulation models against experimental results.
Conducted EMI analysis of GaN-based power converters.
Common-mode (CM) and differential-mode (DM) noise modeling and mitigation.
EMI-aware PCB design and parasitic management.
RLGC extraction and parasitic-aware converter modeling.
LISN-based conducted emission measurements.
FFT and frequency-domain signal analysis.
Electric-field and magnetic-field simulation using HFSS.
Shield optimization and electromagnetic field control.
Correlation of simulation and experimental EMI results.
MATLAB, Simulink, Python, HFSS, Q3D, SIwave, and Twin Builder workflows.
Hardware validation and laboratory testing of power electronic converters.
Project Summary
GaN-Based EMI Mitigation Research
Objective
Investigate electromagnetic interference mechanisms in high-frequency GaN power converters and develop mitigation strategies through shielding, parasitic-aware design, and simulation-driven optimization.
Tools
Ansys HFSS, Q3D Extractor, MATLAB/Simulink, Python
Activities
EMI characterization
Common-mode and differential-mode noise analysis
Shielding strategy development
Experimental validation
Converter optimization
Outcome
Successfully developed and validated EMI reduction methodologies. Detailed technical results are currently part of ongoing PhD research and will be publicly available following thesis completion and publication.
Note: Due to ongoing doctoral research and publication requirements, detailed numerical results, simulation datasets, and unpublished validation data are not publicly disclosed. Additional technical details can be discussed during interviews subject to academic and intellectual property constraints.