Grocery shopping is a routine task that people perform to fulfill their needs for food. We suspect many people would like to do grocery shopping with the grocery list to save their money and time. While creating a grocery list, people have to follow some steps such as checking the ingredients inventory available in their homes, planning meals for few days or weeks, creating a grocery list based on their meal plan and ingredients inventory status, and looking out for deals or offers, which can be utilized in their grocery purchases. These steps can be repetitive and involve people’s manual effort and a considerable amount of time to carry out effectively that makes the creation of a grocery list difficult to accomplish every time considering people’s busy modern lifestyles. As many grocers begin to leverage technology, they have an opportunity to understand the relationship between the people buying behavior from their purchasing history and stores’ grocery information to make profit-driven decisions and promote the reduction of food waste in stores. This thesis presents SmartGrocer, a context-aware personalized grocery system that dynamically gathers user context including their past purchase history and budget, and store context including clearance grocery inventory that consists of those ingredients that are soon-to-expire or being on sale to recommend personalized coupons to users. The personalized coupons are automatically applied to the missing ingredients of recipes thereby reducing the recipes’ cost and recommending them according to the user’s food budget. Recommendation of personalized coupons to users is an effective promotional strategy to not only saving the user’s money but also promoting the reduction of food waste in stores, which eventually drives more profit to the grocery retail businesses. SmartGrocer also automates the whole process of creating a grocery list with minimal effort and time expended by the user by leveraging the user and store context. / Graduate