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
- Sensing & control for water quality
- Data-driven policy
- Diversity in STEM/engineering
- I work with Branko Kerkez in the Real-Time Water Systems Lab.
- My research seeks to manage stormwater including its pollutants without exponential costs and to hedge impacts from climate change, 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 machine learning.
- There is a demonstrated need to accurately model water quality processes and real-time control at the system scale. To that end, I built an open-source Python package which integrates the EPA’s Stormwater Management Model’s water balance engine with a new water quality module. (Completed)
- In order to develop a watershed-scale control strategy, we must first understand the treatment performance of the watershed’s building blocks, series and parallel infrastructure assets. Through the investigation of these building blocks, I expect to uncover fundamental insights into how flows should be routed through watersheds to maximize pollutant treatment. (Underway)
- Based on the data derived from the previous two tasks, I will investigate a systems framework to control water quality in real-time at the watershed scale. (Future Work)
- 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.