About Me

Bio Statement

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
  • Sustainability
  • Environmental justice

Research Overview


  • I work with Branko Kerkez in the Real-Time Water Systems Lab.
  • In the era of the self-driving car, my goal is to bring the same technologies to water and environmental conservation. Specifically, I am focused on reducing stormwater pollution, which is recognized as one of our greatest environmental and social challenges. My research combines domain knowledge from environmental engineering, computing, data science, signal processing, and control theory to enable the next generation of autonomous water systems and move society towards a more just and sustainable future.

Intellectual Merit

  • 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.

Research Objectives

  1. 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)
  2. 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)
  3. Although autonomous control can mitigate flooding and particulate pollutants, it has not yet been evaluated for other water quality parameters. Unfortunately, the application of control theory for water quality is not yet feasible due to the nonlinearities inherent in most stormwater models. To address this limitation, I am formulating a water quality control model for the system-level control of stormwater networks. (Underway)

Broader Impacts

  • 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.