Ahmed Abokifa

Assistant Professor

University of Chicago

United States

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Ahmed Abokifa is an Assistant Professor at the University of Illinois at Chicago. His research focuses on water quality and distribution systems, with recent articles exploring topics such as Bayesian optimization for contamination response, PFAS adsorption, and machine learning applications in water demand forecasting. His work contributes to the development of advanced methods for improving water safety and management.

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2020

Collaborators (5)

Marcio Giacomoni

Full Professor

University of Texas at San Antonio

UNITED STATES

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Mohammadreza Moeini

University of Illinois Chicago (UIC)

UNITED STATES

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Juneseok Lee

Associate Professor

Manhattan College

UNITED STATES

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Brian P. Chaplin

University of Chicago

UNITED STATES

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Baranidharan Raman

Professor

Washington University in St. Louis

UNITED STATES

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Ahmed Abokifa

Research Interests

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About

Articles (20)

Operational response to contamination in water distribution systems: a multi-objective Bayesian optimization approach

Heuristic Space Reduction Method for Source Localization in Water Distribution Networks

Screening of transition metals for PFAS adsorption: A comparative DFT investigation

Chlorine dosage management in drinking water systems: comparing Bayesian optimization to evolutionary algorithms

Ab Initio Investigation of Per- and Poly-fluoroalkyl Substance (PFAS) Adsorption on Zerovalent Iron (Fe0)

Disinfectant control in drinking water networks: Integrating advection–dispersion–reaction models and byproduct constraints

Graph neural networks-based dynamic water quality state estimation in water distribution networks

Sensor Placement Optimization in Sewer Networks: Machine Learning–Based Source Identification Approach

A Multivariate LSTM Model for Short-Term Water Demand Forecasting

Optimal Sensor Placement in Water Distribution Networks Using Dynamic Prediction Graph Neural Networks

Bayesian Optimization of Booster Disinfection Scheduling in Water Distribution Networks

Machine Learning–Based Source Identification in Sewer Networks

Crumpled graphene oxide for enhanced room temperature gas sensing: understanding the critical roles of surface morphology and functionalization

Water and Wastewater Systems and Utilities: Challenges and Opportunities during the COVID-19 Pandemic

Revisiting the Water Quality Sensor Placement Problem: Optimizing Network Observability and State Estimation Metrics

Room temperature gas sensing mechanism of SnO<inf>2</inf> towards chloroform: Comparing first principles calculations with sensing experiments

Spatiotemporal trends of recovery from lead contamination in Flint, MI as revealed by crowdsourced water sampling

WUDESIM: a toolkit for simulating water quality in the dead-end branches of drinking water distribution networks

Framework for Evaluating the Impact of Water Chemistry Changes in Full-Scale Drinking Water Distribution Networks on Lead Concentrations at the Tap

Investigating the impacts of water conservation on water quality in distribution networks using an advection-dispersion transport model

Collaborators (5)

Marcio Giacomoni

Mohammadreza Moeini

Juneseok Lee

Brian P. Chaplin

Baranidharan Raman

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