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Accelerating biotech workflows by combining metabolic modeling (CarveMe/COBRApy) with SMAC3 Bayesian optimization to simulate and discover ideal fungal growth environments.

Celebrating the prestigious Best Paper Award at GECCO 2025 for pioneering insights into Reinforcement Learning and Dynamic Algorithm Configuration.

How integrating 2D molecular graphs with ensembles of 3D conformers via an efficient, geometry-aware barycenter pooling mechanism yields state-of-the-art molecular property prediction.

How combining a dynamic two-stage uncertainty frame with a localization-heavy Emphasis loss breaks the data-hungry bottleneck of deep object detectors.