Digital Twin Lab

At the heart of our initiative is the ambition to significantly mitigate the risks encountered by professionals working on offshore wind turbines. By leveraging the sophisticated capabilities of metahuman models enhanced with biomechanical simulations, we aim to create a safer working environment for these individuals. The potential of this technology to revolutionize workplace safety is vast, and we are eager to delve into the research and development process.

Big data analytics in crop management are increasingly becoming a central topic of research. A recent NSF report stated, “The growing availability of data presents an opportunity to improve the resilience and efficiency of food and agriculture production on a scale unimaginable even one decade ago”. The National Institute of Food and Agriculture (NIFA) recognized these tendencies and initiated research on big data analytics, machine learning, artificial intelligence, and predictive technologies to develop digital agriculture tools and keep US agriculture competitive.

Meeting the net-zero emission paradigm will require a realignment of hydrocarbon production strategies with other forms of energy production. Carbon Capture Storage and Sequestration (CCS) and Compressed Hydrogen (H2) energy storage along with Geothermal energy production will contribute tremendously to achieving a sustainable form of cleaner energy production in the future.

This project aims to build a digital-twin-enabled testbed with state-of-the-art user interface/user experience technologies and advanced simulation models to provide a photorealistic virtual reality environment for first responders and emergency managers to engage, experience, and explore the latest sensing and communication technologies.

The Smart Communities, Smart Responders – AI for IoT Information (AI3) Prize Competition calls participants to utilize data from multiple IoT devices to deliver an AI system to help first responders leverage the data coming from IoT devices, smart buildings, and other public data streams. Texas A&M University, Texas A&M Engineering Extension Service, and US Ignite will run this new program with $1.2 million in funding provided by NIST’s Public Safety Innovation Accelerator Program – Artificial Intelligence for IoT Information (PSAIP – AI3) cooperative agreement.

The objective of the project is to revolutionize the treatment of respiratory and digestive diseases through the development of a new generation of biologic therapeutics through AI-assisted engineering of proteins. This initiative marks a significant departure from traditional systemic administration methods, such as intravenous, intramuscular, or subcutaneous injections, by exploring alternative routes that could vastly improve treatment outcomes for diseases affecting the lung and gastrointestinal (GI) tract.