Luyao Wang, PhD student
Research Topic
Prediction of infectious disease prevalence based on wastewater surveillance using machine learning
Research Abstract
Infectious diseases caused by various pathogens are inducing severe social and economic burden worldwide. Wastewater-based epidemiology (WBE) has been proven as a potential and viable supplementary surveillance tool for monitoring the transmission of various pathogens in communities. However, the relation between wastewater data and cumulative cases is still poorly explored. Wastewater-based epidemiology associated with machine learning techniques is currently emerging as a promising method for COVID-19 prediction. For the successful implementation of WBE, more precise estimations integrating various factors are necessary. This research aims to improve the accuracy of the COVID-19 prediction based on WBE and investigate the viability of its application to other infectious diseases.
Academic Backgrounds
2011 – 2015: Bachelor of Environmental Engineering, China University of Petroleum (East China), China
2016 – 2019 & 2021-2022: Master of Environmental Technology, Technical University of Berlin, Germany
Academic Papers
- Characterization of phage vB_EcoS-EE09 infecting E. coli DSM613 isolated from wastewater treatment plant effluent and comparative proteomics of the infected and non-infected host
Jimena Barrero-Canosa, Luyao Wang, Angelah Oyugi, Simon Klaes, Pascal Fischer, Lorenz Adrian, Ulrich Szewzyk, Myriel Cooper
Microorganisms, November 2023, 11(11), 2688.
Conference Presentations
TBD
Honors
TBD