User:Mishalsarfraz

I am an electrical engineering researcher with interests in agrivoltaics, solar energy, sustainability, sensing systems, machine learning, and open-source hardware. My work focuses on practical, research-driven solutions that combine engineering design, renewable energy, and data-driven methods to support sustainable technology development.

I am currently pursuing my second Master of Engineering in Electrical and Computer Engineering at Oregon State University, USA, with a minor in Biological and Ecological Engineering. I also hold an MS in Electronics and Embedded Systems from Lahore University of Management Sciences (LUMS), and a BS in Electrical Engineering Technology from the University of Engineering and Technology (UET), where I graduated as a Gold Medalist. My academic and technical background bridges renewable energy, embedded systems, sensing, and machine learning.

• Agrivoltaics
• Solar photovoltaic systems
• Renewable energy system design
• Plant sensing and environmental monitoring
• Machine learning for engineering applications
• Open-source hardware and practical sustainability research

• Smart Data Centers of Oregon: Agrivoltaic Siting Analysis – Currently working on a geospatial analysis project focused on approximately 165 data centers across Oregon, including major facilities associated with companies such as Amazon, Google, and Meta. Using QGIS, I am mapping data center locations, substations, wetlands, and other land-use and environmental layers to evaluate site suitability for agrivoltaic deployment. The goal of this project is to identify opportunities for agrivoltaic integration based on surrounding land characteristics and estimate potential land-use, energy, and economic benefits.

• Agrivoltaics Educational Kid-Kit for High School Students – Currently developing an agrivoltaics learning kit designed for high school students. The kit includes seeds, a small photovoltaic unit, and environmental sensors so students can grow plants, observe agrivoltaic interactions, and collect basic data. This project aims to support education, hands-on learning, and community engagement while also generating useful experimental input for future agrivoltaics research.

• Comparative Review of Agrivoltaics Research Papers – Conducting a review of agrivoltaics research literature to identify common experimental limitations, recurring methodological weaknesses, and opportunities for improvement in future studies. This project focuses on analyzing how agrivoltaic experiments are designed, what variables are often overlooked, and how experimental research in the field can be made more rigorous, comparable, and practically useful.

• Physics-Informed Neural Network (PINN) for Agrivoltaics Sap-Flow Modeling Developed and implemented a PINN-based framework to estimate hidden parameters in sap-flow equations linked to Penman transpiration modeling. This work used open meteorological datasets and supported crop-physiology analysis under standard and agrivoltaic conditions.

• Solar PV Design Project – Worked on photovoltaic module sizing, layout planning, and shading analysis for solar deployment concepts using tools such as SketchUp, HelioScope, and PV Sol. This project focused on system design, energy yield estimation, and evaluating site-specific constraints.

• PERC Solar Cell Device Simulation – Modeled solar cell structure, layers, contacts, and performance in Silvaco, including simulation of I-V curves, band diagrams, and efficiency comparisons with theoretical calculations.

• Industrial Visual Inspection System (Edge AI) – Built a manufacturing quality inspection prototype using an NVIDIA platform with CUDA-enabled workflows, PyTorch, and TensorRT.

• Neural network-based sap-flow prediction model for wheat grown in standard and agrivoltaics conditions in Pakistani climate(MS Thesis Published)
• Formulation of diverse energy strategies in Pakistan: issues and approaches(under review)
• Fractional order modeling and speed control of induction motors(under review)
• Fractional order controller design for a self-balancing two-wheeled robot and performance comparison using different optimization techniques(Published)

My technical skills include Python, C/C++, MATLAB, Verilog, PyTorch, TensorRT, CUDA, HelioScope, PVsyst, PV Sol, SketchUp, ETAP, ArcGIS/QGIS, Arduino, FPGA systems, PIC microcontrollers, and laboratory instrumentation for electronics and embedded systems.

• LinkedIn
• Google Scholar

I am always interested in discussing agrivoltaics, solar-energy systems, sustainability research, sensing tools, and open-source hardware development. I also welcome opportunities for collaboration on research, educational tools, and practical engineering projects related to renewable energy and sustainable technology. shoot me an email at mishal@oregonstate.edu for research discuss!