Bayesian Optimization (BO) has emerged as a powerful tool to improve model performance, but its integration with ML for bond strength prediction remains underutilized. Key research directions include ...

Explore new calibration methods for automated material handling systems. Click to see how it transforms smart factories.

In this work, we propose a novel approach called AutoCIL-FMOBO (AutoCIL via Few-shot Multi-Objective Bayesian Optimization). Specifically, we design meta-learned deep kernel Gaussian process ...

To manage increasingly complex manufacturing systems, involving material flows across numerous transporters, machines, and ...

Digital twins for automated material handling systems (AMHSs) of semiconductor and display fabrication industries suffer from parameter uncertainty and discrepancy. This leads to inaccurate ...

Accurate forecasting of agricultural commodity prices is critical for economic stability and strategic decision-making, yet remains challenging owing to nonlinear dynamics and multifactorial ...

Be it in the frequentist or the Bayesian world, the meta-analytic approach is a well accepted method of validation. However, the full joint bivariate models suffer computational issues. And there is a ...

The many stages of a bioprocess offer endless opportunities for optimization. Improving a process starts with process design (PD) and never really ends. In late 2024, Jun Luo, PhD, Genentech’s ...