Portfolio
A collection of 12+ computational research projects organized into five thematic series. Each project includes source code, a formal report, and reproducible results.
Physics-based modeling of turbine wakes, multi-turbine flow interactions, and energy capture optimization in wind farms.
Simulates turbine wake effects using physics-based models to understand how upstream turbines reduce wind speed for downstream turbines in large wind farms.
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Models the aerodynamic interactions between multiple turbines, analyzing how turbine placement and spacing affect overall farm performance.
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Quantifies total energy captured by a wind farm under varying wind conditions, comparing optimal vs. suboptimal turbine configurations.
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Compartmental and stochastic models of epidemic dynamics with vaccination strategies and age-structured population analysis.
Implements the classic SIR compartmental model extended with vaccination to analyze herd immunity thresholds and epidemic control strategies.
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Extends the SEIR framework to incorporate age-stratified populations, modeling differential susceptibility and contact patterns across demographics.
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Uses Monte Carlo methods to simulate stochastic epidemic outcomes, capturing the inherent randomness in disease transmission events.
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Solar PV output modeling, zero-dimensional climate models, grid load forecasting, and electricity dispatch optimization.
Models photovoltaic energy output as a function of solar irradiance, temperature, and cloud cover using physics-based PV performance equations.
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Implements a zero-dimensional energy balance model to study global temperature response to radiative forcing, greenhouse gases, and albedo changes.
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Applies time-series forecasting techniques to predict electricity demand, comparing ARIMA and Prophet models for short-term load prediction.
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Linear, quadratic, and nonlinear optimization techniques applied to real-world problems in supply chains, finance, and chemical engineering.
Formulates and solves a supply chain distribution problem as a linear program to minimize transportation costs subject to supply and demand constraints.
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Uses quadratic programming to construct an optimal investment portfolio that maximizes return for a given risk level, applying Markowitz mean-variance theory.
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Estimates kinetic parameters of a chemical reaction system by fitting ODE models to experimental data using nonlinear least squares optimization.
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Flagship project integrating weather-driven solar PV simulation, electricity demand modeling, and optimal generator dispatch via linear programming into a unified pipeline.
An end-to-end computational pipeline that links weather-driven solar PV output simulation with electricity demand modeling and optimal generator dispatch using linear programming. This capstone synthesizes methods from all prior series into a single integrated framework.
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