Scientific Machine Learning is an approach that integrates machine learning methods with scientific models, simulations, and domain knowledge to analyze and predict complex physical, biological, or engineered systems. It combines data-driven techniques with governing equations and constraints to improve accuracy, interpretability, and generalization. Scientific machine learning is used in applications such as climate modeling, fluid dynamics, materials science, and computational biology to accelerate discovery and optimize system performance.
Designing drug molecules is no longer just about generation, but control. NEC Laboratories America introduces MolDiffdAE, a diffusion-based framework that enables precise, multi-objective tuning of 3D molecular properties. By learning a semantic space, researchers can efficiently guide design, accelerating drug discovery and exploration of chemical space.
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NEC Laboratories America, Inc. (NEC Labs) is the US-based center for NEC Corporation’s global network of corporate research laboratories. Our diverse research groups collaborate with industry, academia and governments to provide disruptive solutions to complex problems. A leader in the integration of IT and network technologies with more than 100 years of expertise, NEC provides a combination of products and solutions that cross-utilize the company’s experience and global resources to meet the complex and ever-changing needs of its customers.