Individual Fellow Initiatives

The challenges facing modern engineers are more complex than ever. Current engineering issues such as
algorithmic bias, data security and privacy, and sustainability do not only require technically skilled engineers,
but also engineers who are conscious about structural inequities and biases.

The goal of this project is to train the next generation of environmental engineers in computing and statistical techniques to solve big data problems. Current undergraduate students in the Department of Civil, Architectural and Environmental Engineering have little to no exposure to computational and statistical methods for data analysis (e.g., big data collected from sensor networks). I proposed to integrate computational techniques in several courses throughout the Environmental Engineering Degree.

This project entailed the creation of a curricular context and physical space for collaborative interdisciplinary teaching and research for faculty and students interested in Russian, East European and Eurasian studies. This was achieved in two ways. First, I transformed the required gateway course to our major, “Introduction to Russian, East European and Eurasian Studies,” which had been a disjointed “parade of faculty” course with disconnected guest speakers.