Amirhossein Ershadi

HS Hydrological Sciences

The 2024 Outstanding Student and PhD candidate Presentation (OSPP) Award is awarded to Amirhossein Ershadi for the poster/PICO entitled:

Ensemble Surrogate Modeling of Advective-Dispersive Transport with IntraParticle Pore Diffusion for Column-Leaching Tests (Ershadi, A.; Finkel, M.; Liu, B.; Cirpka, O. A.; Grathwohl, P.)

Click here to download the poster/PICO file.

Amirhossein Ershadi is a PhD candidate in the Hydrogeochemistry group at the University of Tübingen, Germany. His research focuses on the application of machine learning to column leaching tests, which are crucial for assessing the environmental risks of contaminated soils and waste materials reused for various construction purposes.

At the awarded presentation, Amirhossein showcased his work on developing two innovative ensemble surrogate models to emulate the complex dynamics of solute transport and kinetic inter-phase mass transfer in column leaching tests. These models, which utilize random-forest stacking and inverse-distance weighted interpolation, significantly reduce the computational intensity required by traditional numerical models. By applying Simulation-Based Inference, the proposed ensemble surrogate models demonstrated excellent performance, accurately estimating the complete posterior parameter distribution based on copper-leaching data from different soils.