Because cement production is responsible for approximately 8 % of global CO2 emissions, researchers are looking for more sustainable materials to replace or partially replace cement and other traditional materials while maintaining the strength of concrete. This SuperUROP project aims to compile a data set from researches in the field, train machine learning models to predict the properties of concrete with multiple replacement materials, and validate the accuracy of the model with physical experiments.

I am participating in SuperUROP to gain more research experience and to give a proper closure to my final project for 1.054 Mechanics and Design of Concrete Structures. I believe that my background in both Civil Engineering and EECS, as well as my data science internship, will be valuable to this project. The ultimate goal of this project is to provide a tool for researchers to further advance the research field of cement replacement and come up with an economically viable and sustainable concrete mix design.