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Greentown Labs calls for applicants from Texas universities for climatetech bootcamp

Greentown Labs opened applications for their TEX-E climatetech bootcamp. Photo courtesy of Greentown Labs

Greentown Labs is calling for student entrepreneurs, faculty, and staff from Texas universities to enroll in their climatetech bootcamp.

The course is part of the Texas Entrepreneurship Exchange for Energy (TEX-E) program, a collaboration between The University of Texas at Austin, Texas A&M University, University of Houston, Rice University, and Prairie View A&M University—powered by Greentown Labs and MIT’s Martin Trust Center for Entrepreneurship. The free bootcamp will run from Sept. 22-24 at Greentown Labs and the deadline to apply is Aug. 27.

Participants will learn from faculty from several Texas universities and instructors from the Climate & Energy Ventures Course at MIT.

“Throughout the weekend, participants will learn from leading academic minds in the field of energy innovation, and they will work together on collaborative projects that could be the genesis of a new enterprise. They will leave the program with enhanced readiness to tackle one of the biggest problems humanity has ever faced,” reads a statement about the program.

TEX-E is seeking participants with interest in one or more areas within the intersection of energy and entrepreneurship:

  • Mobility and Transport
  • Energy
  • Food, Agriculture, and Land Use
  • Industry Manufacturing, and Resource Management
  • Built Environment
  • Financial Services
  • Climate Change Management and Reporting
  • GHG Capture, Removal, and Storage

Once the bootcamp is over, participants will join the TEX-E network and be eligible for follow-up opportunities, including: networking events, job postings, cross-learning with MIT, career fairs, on-campus events, and pitch competitions.

TEX-E previously sponsored a multi-round startup competition for Texas students who are creating companies focused on moving the energy transition forward. The winners were collectively awarded $50,000 in prizes.

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A View From HETI

Researchers have secured $3.3 million in funding to develop an AI-powered subsurface sensing system aimed at improving the safety and efficiency of underground power line installation. Photo via Getty Images

Researchers from the University of Houston — along with a Hawaiian company — have received $3.3 million in funding to explore artificial intelligence-backed subsurface sensing system for safe and efficient underground power line installation.

Houston's power lines are above ground, but studies show underground power is more reliable. Installing underground power lines is costly and disruptive, but the U.S. Department of Energy, in an effort to find a solution, has put $34 million into its new GOPHURRS program, which stands for Grid Overhaul with Proactive, High-speed Undergrounding for Reliability, Resilience, and Security. The funding has been distributed across 12 projects in 11 states.

“Modernizing our nation’s power grid is essential to building a clean energy future that lowers energy costs for working Americans and strengthens our national security,” U.S. Secretary of Energy Jennifer M. Granholm says in a DOE press release.

UH and Hawaii-based Oceanit are behind one of the funded projects, entitled “Artificial Intelligence and Unmanned Aerial Vehicle Real-Time Advanced Look-Ahead Subsurface Sensor.”

The researchers are looking a developing a subsurface sensing system for underground power line installation, potentially using machine learning, electromagnetic resistivity well logging, and drone technology to predict and sense obstacles to installation.

Jiefu Chen, associate professor of electrical and computer engineering at UH, is a key collaborator on the project, focused on electromagnetic antennas installed on UAV and HDD drilling string. He's working with Yueqin Huang, assistant professor of information science technology, who leads the geophysical signal processing and Xuqing Wu, associate professor of computer information systems, responsible for integrating machine learning.

“Advanced subsurface sensing and characterization technologies are essential for the undergrounding of power lines,” says Chen in the release. “This initiative can enhance the grid's resilience against natural hazards such as wildfires and hurricanes.”

“If proven successful, our proposed look-ahead subsurface sensing system could significantly reduce the costs of horizontal directional drilling for installing underground utilities,” Chen continues. “Promoting HDD offers environmental advantages over traditional trenching methods and enhances the power grid’s resilience.”

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