activity
20242026
most citedA KAN-based Interpretable Framework for Process-Informed Prediction of Global Warming Potential

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

q-bio.QM2026

PyOMES: an open-source framework for biochemical process modelling

Ethan Errington, Tom Vinestock, Jaewook Lee +1

PyOMES is a Python-based, Open-source Modelling Environment for (bio)chemical process Simulation that aims to simplify the modelling of dynamic (including steady state) processes.…

cs.LG2026

Transfer Learning Architectures for Scalable Multi-Fidelity Bayesian Optimization

Jaewook Lee, Ethan Errington, Christian D. Lorenz +1

Self-driving laboratories increasingly rely on multi-fidelity Bayesian optimization (MFBO) to balance cheap, approximate evaluations against scarce, expensive ones, with a predicti…

q-bio.QM2025

Temporal Dynamics of Microbial Communities in Anaerobic Digestion: Influence of Temperature and Feedstock Composition on Reactor Performance and Stability

Ellen Piercy, Xinyang Sun, Peter R Ellis +2

Anaerobic digestion (AD) offers a sustainable biotechnology to recover resources from carbon-rich wastewater, such as food-processing wastewater. Despite crude wastewater character…

cs.LG2024★ 1 cited

A KAN-based Interpretable Framework for Process-Informed Prediction of Global Warming Potential

Jaewook Lee, Xinyang Sun, Ethan Errington +1

Accurate prediction of Global Warming Potential (GWP) is essential for assessing the environmental impact of chemical processes and materials. Traditional GWP prediction models rel…

physics.bio-ph2024

High Throughput Parameter Estimation and Uncertainty Analysis Applied to the Production of Mycoprotein from Synthetic Lignocellulosic Hydrolysates

Mason Banks, Mark Taylor, Miao Guo

The current global food system produces substantial waste and carbon emissions while exacerbating the effects of global hunger and protein deficiency. This study aims to address th…