My research uses machine learning to sense and predict both building- and occupant-related information to understand human response as well as VR or AR to explore human-building interactions and construction safety while working on robot-assisted sites.
My group’s research uses probabilistic modeling and computational stochastic mechanics, quantitative models for the propagation of uncertainty in physical systems and probabilistic multi-scale modeling.
My group’s research uses computing to develop frameworks, and algorithms, that support the acquisition, modeling, management, and analysis of construction/infrastructure management data.
My research uses computing to run models which analyze climate, air pollution, hydrology, and electricity consumption to predict and gain insight into the impact of human energy systems.
My group’s research focuses on developing technologies for measuring the physico-chemical characteristics of air pollutants, with an emphasis on particulate matter (PM) and determining their toxic properties.
My group’s research uses computational methods to address water quality challenges related to chemical and ultraviolet disinfection of wastewater and drinking water.
My research focuses on investigating chemical exposures to people through food and water and how communities and socioeconomics interplay with these exposures.
Dr. Childress
My group’s research uses computing to evaluate the energy, recovery, and water quality advantages of advanced systems to reduce energy consumption in clean water production, to reuse water during energy production, and to leverage uncommon sources to produce energy.
My research uses computing to develop theoretical models to study and predict how the binding forces in cement may be affected by changes in its electrochemistry.
My group’s research uses computational methods to study transportation networks and infrastructure through control and dynamical systems, optimization, stochastics, networks, game theory, learning, and experiments.
My group’s research uses regression analysis to develop and validate models focused on estimating site response in sedimentary basins and surrounding non-basin locations.
My group’s research developed the computational suite of codes MOST (Method of Splitting Tsunami) and uses numerical and analytical modeling to study tsunami behavior.
My group’s research uses numerical-based multi-scale wave modeling, hybrid and parallel numerical computing, investigations into tsunami breaking, and extraction of energy from nearshore wind waves.
My research uses computational methods to determine risk reduction and reliability enhancement of complex technological systems, including nuclear power, aviation, petrochemical, and transportation industries.