The natural protein universe is vast, and yet, going beyond and designing new proteins not observed in nature can yield new ...

Understanding and predicting complex physical systems remain significant challenges in scientific research and engineering. Machine learning models, while powerful, often fail to follow the ...

Machine learning (ML) with approximation and numerical simulations plays an important role in aircraft design. ML techniques, such as deep learning and reinforcement learning, are increasingly being ...

The SMART-FIT Lab will train students in smart manufacturing skills and machine optimization ...

In this work, we demonstrate the machine learning-driven optimization of a photoredox tertiary amine synthesis with six continuous variables (e.g., concentration, temperature, residence time) and ...

Then, by combining the multi-objective optimization strategy Artificial Rabbit Optimization (ARO) with the Light Gradient Boosting Machine (LightGBM) model, a new intelligent lithology identification ...

This course teaches an overview of modern mathematical optimization methods, for applications in machine learning and data science. In particular, scalability of algorithms to large datasets will be ...

This study employed multi-objective Bayesian optimization (MOBO) machine learning (ML) to simultaneously optimize multiple electrical objectives, aiming to achieve high mobility and a near-zero ...