Calvin Chen

Multi-objective drug design with a scaffold-aware variational autoencoder† Designing molecules with multiple properties of interest is a fundamental challenge in drug development. To tackle this, we have developed ScafVAE, an innovative scaffold-aware variational autoencoder designed for the in silico graph-based generation of multi-objective drug candidates.

Abstract Advances in Artificial Intelligence envision a promising future, where the personalized Internet of Things can be revolutionized with the ability to continuously improve system efficiency and service quality.

Abstract In modern computational materials, machine learning has shown the capability to predict interatomic potentials, thereby supporting and accelerating conventional molecular dynamics (MD) simulations. However, existing models typically sacrifice either accuracy or efficiency. Moreover, efficient models are highly demanded for offering simulating systems on a considerably larger scale at reduced computational costs.