As a first-generation college student, the desire to become a lifelong learner motivates me to acquire new skills and pursue challenging opportunities. My appetite for knowledge and a bricolage of experiences have transformed me from a liberal arts graduate into an engineer and researcher situated within the field of sustainability. Currently, I am a Ph.D. Candidate in Civil Engineering with a focus in Intelligent Systems at the University of Michigan. The field of intelligent systems is just starting to bloom, and with it, I, too, will bloom into a sustainably focused, intelligent water systems researcher.
I am motivated to move society towards a more just and sustainable future. Through research, I seek to improve water management by enabling the next generation of autonomous water systems by combining domain knowledge from computing, data science, machine learning, and control theory. Through service, I work to improve diversity, equity, and inclusion at my institution and in my community.
General Research Interests
- Autonomous stormwater systems
- Real-time monitoring and control
- Improving modeling capabilities
- Data-driven policy
- Environmental justice
- I work with Branko Kerkez in the Real-Time Water Systems Lab.
- To manage stormwater and its pollutants without exponential costs, we can leverage recent technological advances, such as sensors and real-time data algorithms, to enable the next generation of autonomous water systems.
- Coordinated, autonomous stormwater systems will use sensors and actuators to adapt watersheds to individual storms, reducing flooding and maximizing treatment through real-time monitoring and control at the system-scale.
- Investigating fundamental knowledge gaps of autonomous systems water resources, environmental engineering, control theory, system system, and signal processing.
- No computational toolchains existed to evaluate the potential of autonomous water systems due to the overlapping need to model flow, water quality, and controls. To address this need, I built an open-source Python package, StormReactor, which couples the popular EPA’s Stormwater Management Model with a new generation water quality module. (Completed)
- Partnering with the Detroit Sierra Club, I developed an “Internet of Things” stormwater infrastructure sensing network using open-source solutions to monitor flooding in Detroit. A network of 20+ sensor nodes has created the largest dataset of stormwater infrastructure performance to date, shedding a light on stormwater dynamics at an unprecedented spatial and temporal scale. (Underway)
- Real-time flood inundation modeling is critical for informing citizens and emergency services during flash flood conditions. To that end, I am combining my lab’s open-source sensor data, USGS stream gauge data, and publicly accessible GIS datasets to develop a real-time flood inundation model for southeast Michigan. (Underway)
- Developing an interdisciplinary, integrated systems framework for autonomous water system.
- Improving the ability of water system managers to make informed decisions by providing real-time monitoring and control capabilities.