Abstract—Neuromorphic computing models the computational processes of the human brain to enable low-power, eventdriven information processing. This educational research paperpresents a comprehensive study of reservoir computing implemented using Leaky Integrate-and-Fire (LIF) neurons in theNengo simulator. We explore the theoretical basis of LIF models,system design, and implementation, followed by extensive experiments analyzing the effect of key parameters such as reservoirsize, connection probability, input rate, and integration window.Realistic data tables and energy modeling are provided todemonstrate trade-offs between accuracy and energy efficiency.Beyond technical depth, we reflect on educational outcomes,methodological insights, and broader societal implications. Thestudy combines theoretical rigor with an accessible format suitedfor undergraduate research and transfer portfolios