Hello, I am అభిరామ్ ముళ్ళపూడి (Abhiram Mullapudi). I develop autonomous water systems; think self-driving cars, but for water infrastructure. These autonomous water systems will monitor and operate themselves to mitigate flash floods, ensure access to safe drinking water, and improve the efficiency of water treatment processes. I currently work at Xylem Vue as a Hydraulic Optimization and Control Engineer. At my job, I design machine learning algorithms and develop software for distilling actionable intelligence from data. In addition, I develop firmware and hardware for wireless monitoring of water networks. I have a Ph.D. in civil engineering, specializing in intelligent systems, from the University of Michigan, Ann Arbor, where I was fortunate to have been advised by Prof. Branko Kerkez. I did my bachelor's in civil engineering at Amrita Viswavidhya Peetham, Coimbatore.
I am a design nerd. I enjoy learning about urban systems, graphic design (especially fonts), and architecture. I like typesetting documents in LaTex. I also collect fountain pens and mechanical pencils. I am passionate about open source science and software; I extensively use and contribute to open-source tools. I enjoy tinkering with microcontrollers and sensors. I am obsessed with coffee and all its derivatives. I enjoy traveling, hiking, and exploring different cuisines. I love playing video games and reading fiction and occasionally non-fiction. I am currently learning French and Chess.
I am interested in optimization, real-time control, and machine learning, and their application for addressing water challenges. I also enjoy building wireless sensor networks: designing backend infrastructure, prototyping sensors, and laying out custom hardware.
In preparation, 2022
pystorms provides a curated collection of stormwater control scenarios to enable the development and quantitative comparison of stormwater control algorithms.
Urban Water Journal, 2022
Real-time control improves the nutrient capture efficiency of bioretention cells, and thus reducing the size of bioretention cells needed for nutrient removal.
Environmental Modelling and Software, 2021
StormReactor is a python package for updating pollutant concentrations in EPA-SWMM durng simulations.
Journal of Open Source Software, 2020
pyswmm is a python wrapper for interfacing with US EPA's Stormwater Management Model.
Advances in Water Resources, 2020
Reinforcement learning can be used for creating autonomous stormwater systems that can dynamically change their behavior based on the state of the watershed for achieving system scale objectives.
Journal of Open Source Software, 2019
Anomalies in the streaming data can be detected by estimating the shift in the structure of the random forest caused by the addition of a new data point.
Environmental Science: Water Research and Technology, 2017
By re-imagining physical watersheds as a network of interconnected systems, they can be dynamically reconfigured in real-time to target the removal of specific pollutants.