Houston researcher scores prestigious NSF award for machine learning, power grid tech

grant funding

The UH team is developing ways to use machine learning to ensure that power systems can continue to run efficiently when pulling their energy from wind and solar sources. Photo via Getty Images

An associate professor at the University of Houston received the highly competitive National Science Foundation CAREER Award earlier this month for a proposal focused on integrating renewable resources to improve power grids.

The award grants more than $500,000 to Xingpeng Li, assistant professor of electrical and computer engineering and leader of the Renewable Power Grid Lab at UH, to continue his work on developing ways to use machine learning to ensure that power systems can continue to run efficiently when pulling their energy from wind and solar sources, according to a statement from UH. This work has applications in the events of large disturbances to the grid.

Li explains that currently, power grids run off of converted, stored kinetic energy during grid disturbances.

"For example, when the grid experiences sudden large generation losses or increased electrical loads, the stored kinetic energy immediately converted to electrical energy and addressed the temporary shortfall in generation,” Li said in a statement. “However, as the proportion of wind and solar power increases in the grid, we want to maximize their use since their marginal costs are zero and they provide clean energy. Since we reduce the use of those traditional generators, we also reduce the power system inertia (or stored kinetic energy) substantially.”

Li plans to use machine learning to create more streamlined models that can be implemented into day-ahead scheduling applications that grid operators currently use.

“With the proposed new modeling and computational approaches, we can better manage grids and ensure it can supply continuous quality power to all the consumers," he said.

In addition to supporting Li's research and model creations, the funds will also go toward Li and his team's creation of a free, open-source tool for students from kindergarten up through their graduate studies. They are also developing an “Applied Machine Learning in Power Systems” course. Li says the course will help meet workforce needs.

The CAREER Award recognizes early-career faculty members who “have the potential to serve as academic role models in research and education and to lead advances in the mission of their department or organization,” according to the NSF. It's given to about 500 researchers each year.

Earlier this year, Rice assistant professor Amanda Marciel was also granted an NSF CAREER Award to continue her research in designing branch elastomers that return to their original shape after being stretched. The research has applications in stretchable electronics and biomimetic tissues.

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This article originally ran on EnergyCapital.

Houston professor earns Google Scholar award for quantum computing research

recent recognition

A Rice University quantum computer scientist was one of 78 global professors to be presented with a 2023 Google Scholar award, the university announced this month.

Nai-Hui Chia, an assistant professor of computer science at Rice, was recognized for his research on Hamiltonian simulations, a method for representing the motion of moving particles. Chia aims to understand if quantum computers or machines can simulate a "Hamiltonian matrix" with a shorter evolution time.

"We call this fast-forwarding for a Hamiltonian simulation,” Chia says in a statement.

Chia aims to use the funds from Google to discover Hamiltonians that can be fast-forwarded using parallelism or classical computation, according to Rice. He will present his current work on Hamiltonians and their connection to cryptology in July at the 2023 Computational Complexity Conference in Warwick, UK.

The Google Research Scholar program grants funds of up to $60,000 to support professors' research around the world. This year's cohort works in fields ranging from algorithms and optimization to natural language processing to health research.

Three other Texas researchers were awarded funds in the 2023 cohort.

The University of Texas at Austin's Jon Tamir was awarded for his work in applied sciences. Atlas Wang, also from UT, was awarded in the machine learning and data mining category. Shenglong Xu, from Texas A&M University, joined Chia in the quantum computing category.

Tech behemoth Google has awarded funds to several Houston innovators in recent years.

Last summer the company named AnswerBite, Boxes and Ease to its inaugural cohort of the Google for Startups Latino Founders Fund. Selected companies received an equity-free $100,000 investment, as well as programming and support from Google.

In September 2022, ChurchSpace and Enrichly were named part of the Google for Startups Black Founders Fund. The companies also received $100,000 non-dilutive awards along with mentoring and support.

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Rice student startup lands $1.85M to launch medical drone network

critical cargo

Students at Rice University have developed a medical cargo drone transport system to help deliver sensitive medical supplies and improve mobile healthcare efforts.

Haast Autonomous is the brainchild of graduating seniors Ege Halac, Jason Chen and Santiago Brent, who got their venture idea off the ground with help from the Liu Idea Lab for Innovation and Entrepreneurship (Lilie) Summer Venture Studio. The founders have developed the prototype at Rice’s Oshman Engineering Design Kitchen (OEDK) with fellow Rice researchers Felix Hasson, Ethan Javedan, Kenna Sanders and Caden Schmidt.

The startup has raised $1.85 million in pre-seed funding, according to Rice. The founders plan to focus on Haast full-time following graduation. They said they aim to launch pilot trials in 2027 and head to market later that year.

“We need better alternatives for a fast, safe and on-demand system of transport for life-critical cargo,” Halac said in a news release from Rice.

The Haast team has developed a custom aircraft with software that manages dispatch, routes, and chain of custody to assist in how materials move between sites in centralized medical systems. Generally, the transportation of medical supplies and materials between facilities and points of care relies on ground shipping or expensive air transport.

Haast Autonomous’ aircraft can take off and land vertically, and is designed around a mission profile of 50 to 62 miles. It can carry a payload of at least 5 pounds, with future versions intended to scale up in size. It also includes a built-in payload bay that regulates temperature, pressure, vibration and tilt to protect sensitive contents such as patient samples, antivenom or poisoning kits and radioligands or other therapies, according to Rice.

At first, the company envisioned the mission to be centered around transplants, but saw the product being best suited for a variety of operations.

“What we realized is that the platform we are building is suited for medicine, but it really underlies a much larger problem of mission-critical transport across industries,” Brent added in the news release. “We are building the fastest, most secure logistics chain for the world’s most sensitive cargo.”

Haast Autonomous was recognized at the 2026 Oshman Engineering Design Showcase and Competition, where it won Best Aerospace or Transportation Technology. It also performed well in the 2026 Napier Rice Launch Challenge.

In the future, Haast Autonomous plans to deploy a fleet of aircraft. The software will be designed to assist hospitals in requesting flights and tracking deliveries in real time.

“The drone is only part of the solution,” Chen also added in the release. “What matters is moving something from point A to point B in a way that fits into how hospitals already operate.”

Houston scientist wins prestigious Pew Scholar award for brain cancer research

standout scholar

Christina Tringides, an assistant professor of materials science and nanoengineering at Rice University, is one of 21 scientists to win a prestigious Pew Biomedical Scholar award.

She is the first faculty member from Rice to win the distinction, which provides $300,000 over four years for advances in biomedicine, according to the university. The awards are granted to researchers who are in the first few years at the assistant professor level.

In Tringides’ case, the funding will support her innovative new method of modeling glioblastoma, a common and extremely aggressive form of brain cancer. Thanks to producing its own blood supply, glioblastoma spreads quickly, weaving tendrils of blighted tissue throughout the brain. Because of this, surgery is difficult and conventional therapies ineffective.

Understanding the way glioblastoma spreads is crucial to the search for a cure. Tringides is using hydrogels that mimic the brain’s extracellular matrix. Using cultures and a microscopic labyrinth, her team can see how the cancer spreads, bonds with neurons and changes cell wall activity. Essentially, Tringides has devised an intelligence test for tumors in hopes of learning how to outsmart them.

“As cancer crawls through the maze, we can look at how it is interacting with the neurons more and more, and measure how electrical activity is changing as a result,” she said in a news release from Rice.

Examining how cancer cells grow can reveal which conditional changes slow them down. Finding ways to alter the structure of brain matter in a way that makes it inhospitable to the cancer could lead to therapies that would impede growth or even reverse it. Using her custom-made ersatz brain maze makes it easier to observe changes than it would be in a patient’s brain.

“Imaging synapses is time-intensive ⎯ it can involve large data files that are hard to visualize, but if we know that the only place where we might have a synapse is this tiny 1-by-4-by-10 micron channel, it makes it much faster and reliable to image them,” Tringides said.

Born in Ames, Iowa, Tringides received her doctorate in biophysics from Harvard before joining Rice in 2024 through a Cancer Prevention and Research Institute of Texas (CPRIT) recruitment award.

Her research was also one of the first four projects to receive research awards through the Rice Brain Institute and TMC Neuro Collaboration Seed Grant Program.

Texas residents earn 11th highest income in U.S., says 2026 study

Money Matters

A new WalletHub study comparing income disparities across America has ranked Texas residents No. 11 on the list of states with the highest earning residents in the nation.

The report, "States Where People Have the Highest Income (2026)," analyzed U.S. Census Bureau income data in all 50 states and the District of Columbia. The report evaluated the average annual income of the top five percent, the median annual household income, and the average annual income of the bottom 20 percent of residents in every state, all adjusted for the cost of living.

The report's data revealed the top five percent of Texans, the highest earners, make $520,378 on average yearly after adjusting for the cost of living. That's the seventh-highest income among the top five percent of earners nationwide.

Meanwhile, the median annual income of a Texas household is just under $76,000. The bottom 20 percent of Texas residents make $17,651 a year, the report found.

For additional context, the latest data from the Federal Reserve shows an American household's median yearly income is about $83,700. WalletHub analyst Chip Lupo also found that the highest earning 10 percent of individuals in the U.S. earn over 12 times more than those in the lowest-earning 10 percent, based on the latest Census data.

"By measuring the income of various percentiles against a state's median income, we can better identify where income disparities are more prevalent, which could help us better understand why residents of certain states struggle more to make ends meet," said Lupo.

Virginia is the state where residents earn the highest income in the U.S., WalletHub said. Based on the report's findings, the top five percent of Virginians make $545,097 on average per year after adjusting for the cost of living. The median annual income of a Virginia household comes out to $95,339, and the bottom 20 percent of residents make $19,671 annually on average.

Conversely, West Virginia is the state where people have the lowest income in the U.S. A West Virginia household makes a median annual income of $56,610, the third-lowest nationally, and the bottom 20 percent of residents make $13,260 on average per year, which is the fifth-lowest in the nation. The top five percent of West Virginians make $372,218 on average per year.

The top 10 states where residents have the highest income are:

No. 1 – Virginia
No. 2 – New York
No. 3 – New Jersey
No. 4 – Washington
No. 5 – Connecticut
No. 6 – Utah
No. 7 – Colorado
No. 8 – Minnesota
No. 9 – Illinois
No. 10 – Massachusetts

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This article originally appeared on CultureMap.com.

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