Metal-organic frameworks (MOFs) are porous materials that can be applied to modern technologies in energy storage, gas separation, carbon dioxide capture, catalysis, and many other areas. There are an ...

In the rapidly evolving landscape of modern manufacturing and engineering, a new technology is emerging as a crucial enabler-Data-Model Fusion (DMF). A recent review paper published in Engineering ...

Researchers have discovered a new way to drive chemical reactions that could generate a wide variety of azetidines -- four-membered nitrogen heterocycles that have desirable pharmaceutical properties.

A deep learning framework combines convolutional and bidirectional recurrent networks to improve protein function prediction from genomic sequences. By automating feature extraction and capturing long ...

Abhijeet Sudhakar develops efficient Mamba model training for machine learning, improving sequence modelling and ...

A new computational model of the brain based closely on its biology and physiology not only learned a simple visual category learning task exactly as well as lab animals, but even enabled the ...

The traditional approach to artificial intelligence development relies on discrete training cycles. Engineers feed models vast datasets, let them learn, then freeze the parameters and deploy the ...

Faculty opportunities in Computational Modeling, Simulation, and Energy Sustainability. Conduct pioneering research in reservoir simulation, optimization, and decarbonization. Collaborate with ...

Electro- and photocatalytic materials are central to enabling sustainable energy conversion processes such as water splitting, CO 2 reduction, oxygen reduction, and ammonia synthesis. These reactions ...

Train professional engineers in advanced methods of engineering analysis and modeling for exploration, simulation and optimization of mechanical engineering systems. Develop theoretical understanding ...