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Houston university launches latest micro-credential course focused on AI, robotics for the energy industry

The new course will provide participants with insights on how to use robotics to enhance efficiency in data collection, AI data analysis tools for industry, risk management with AI, and more. Photo courtesy of UH

The University of Houston will launch its latest micro-credential course next month that focuses on how AI and robotics can be used in inspection processes for the energy industry.

Running from March 22 through April 22, the course is open to "engineers, technicians and industry professionals with advanced knowledge in the dynamic fields of robotics and AI," according to a statement from UH. It will combine weekly online lectures and in-person hands-on demonstrations and provide participants with insights on how to use robotics to enhance efficiency in data collection, AI data analysis tools for industry, risk management with AI, and more.

“By blending theoretical knowledge with practical applications and hands-on experience, the course aims to empower participants with the skills needed to evaluate and adopt these advanced technologies to address real-world challenges in asset management,” Vedhus Hoskere, assistant professor at the UH Cullen College of Engineering, said in a statement. “We hope that upskilling and knowledge gained from this course will help accelerate the adoption of AI and robotics and contribute to the advancement of safer and more resource-efficient energy infrastructure systems.”

Hoskere will teach the course module titled “Computer Vision and Deep Learning for Inspections.” He also recently received a $500,000 grant from the Texas Department of Transportation (TxDOT) to look at how to use drones, cameras, sensors and AI to support Texas' bridge maintenance programs.

Other leaders of the UH Energy course will include:

  • Kimberley Hayes, founder of Valkim Technologies: Lead speaker who will provide an overview and introduction of AI applications, standards and certification
  • Gangbing Song, Moores Professor of Mechanical Engineering at UH: Machine learning hands-on exercises
  • Pete Peterson, head of product management and marketing with XaaS Lab: Computer vision technology in the oil and gas industry
  • Matthew Alberts, head of project management with Future Technologies Venture Venture LLC: Use cases, workflow and optimizing inspections with AI and drones
  • Suchet Bargoti, chief technology officer at Abyss Solutions: AI and robots for integrity management.

Registration accepted up to the first day of the course and can be completed online.

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A View From HETI

Researchers from Rice University say their recent findings could revolutionize power grids, making energy transmission more efficient. Image via Getty Images.

A new study from researchers at Rice University, published in Nature Communications, could lead to future advances in superconductors with the potential to transform energy use.

The study revealed that electrons in strange metals, which exhibit unusual resistance to electricity and behave strangely at low temperatures, become more entangled at a specific tipping point, shedding new light on these materials.

A team led by Rice’s Qimiao Si, the Harry C. and Olga K. Wiess Professor of Physics and Astronomy, used quantum Fisher information (QFI), a concept from quantum metrology, to measure how electron interactions evolve under extreme conditions. The research team also included Rice’s Yuan Fang, Yiming Wang, Mounica Mahankali and Lei Chen along with Haoyu Hu of the Donostia International Physics Center and Silke Paschen of the Vienna University of Technology. Their work showed that the quantum phenomenon of electron entanglement peaks at a quantum critical point, which is the transition between two states of matter.

“Our findings reveal that strange metals exhibit a unique entanglement pattern, which offers a new lens to understand their exotic behavior,” Si said in a news release. “By leveraging quantum information theory, we are uncovering deep quantum correlations that were previously inaccessible.”

The researchers examined a theoretical framework known as the Kondo lattice, which explains how magnetic moments interact with surrounding electrons. At a critical transition point, these interactions intensify to the extent that the quasiparticles—key to understanding electrical behavior—disappear. Using QFI, the team traced this loss of quasiparticles to the growing entanglement of electron spins, which peaks precisely at the quantum critical point.

In terms of future use, the materials share a close connection with high-temperature superconductors, which have the potential to transmit electricity without energy loss, according to the researchers. By unblocking their properties, researchers believe this could revolutionize power grids and make energy transmission more efficient.

The team also found that quantum information tools can be applied to other “exotic materials” and quantum technologies.

“By integrating quantum information science with condensed matter physics, we are pivoting in a new direction in materials research,” Si said in the release.

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