Tim Scheibe

This paper models microbial regulatory feedback in organic matter decomposition, finding copiotrophic traits drive positive priming effects.

The paper uses AI to iteratively improve environmental predictions by combining field sampling with machine learning, significantly enhancing sediment oxygen consumption forecasts across the U.S.

The paper develops an ANN-based reduced-order model to accelerate FBA integration with RTMs, enabling efficient simulation of microbial metabolic switching in Shewanella oneidensis.

This paper introduces a new biogeochemical modeling approach that explicitly represents organic matter thermodynamics to improve predictions of microbial degradation processes and their environmental impacts.