Rice University professor earns $550k NSF award for wearable imaging tech​

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Rice University's Lei Li has been awarded a $550,000 NSF CAREER Award to develop wearable, hospital-grade medical imaging technology. Photo by Jeff Fitlow/ Courtesy Rice University

Another Houston scientist has won one of the highly competitive National Science Foundation (NSF) CAREER Awards.

Lei Li, an assistant professor of electrical and computer engineering at Rice University, has received a $550,000, five-year grant to develop wearable, hospital-grade medical imaging technology capable of visualizing deep tissue function in real-time, according to the NSF. The CAREER grants are given to "early career faculty members who demonstrate the potential to serve as academic models and leaders in research and education."

“This is about giving people access to powerful diagnostic tools that were once confined to hospitals,” Li said in a news release from Rice. “If we can make imaging affordable, wearable and continuous, we can catch disease earlier and treat it more effectively.”

Li’s research focuses on photoacoustic imaging, which merges light and sound to produce high-resolution images of structures deep inside the body. It relies on pulses of laser light that are absorbed by tissue, leading to a rapid temperature rise. During this process, the heat causes the tissue to expand by a fraction, generating ultrasound waves that travel back to the surface and are detected and converted into an image. The process is known to yield more detailed images without dyes or contrast agents used in some traditional ultrasounds.

However, current photoacoustic systems tend to use a variety of sensors, making them bulky, expensive and impractical. Li and his team are taking a different approach.

Instead of using hundreds of separate sensors, Li and his researchers are developing a method that allows a single sensor to capture the same information via a specially designed encoder. The encoder assigns a unique spatiotemporal signature to each incoming sound wave. A reconstruction algorithm then interprets and decodes the signals.

These advances have the potential to lower the size, cost and power consumption of imaging systems. The researchers believe the device could be used in telemedicine, remote diagnostics and real-time disease monitoring. Li’s lab will also collaborate with clinicians to explore how the miniaturized technology could help monitor cancer treatment and other conditions.

“Reducing the number of detection channels from hundreds to one could shrink these devices from bench-top systems into compact, energy-efficient wearables,” Li said in the release. “That opens the door to continuous health monitoring in daily life—not just in hospitals.”

Amanda Marciel, the William Marsh Rice Trustee Chair of chemical and biomolecular engineering and an assistant professor at Rice, received an NSF CAREER Award last year. Read more here.

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The device is lighter than a Band-Aid and could be used as robot skin to track movement and health conditions. Photo via uh.edu

University of Houston professors identify super thin wearable device

Data collecting skin

Imagine a wearable device so thin it's less noticeable and lighter than a Band-Aid but can track and record important health information. According to some University of Houston researchers, you might not need to imagine it at all.

A recent paper, which ran as the cover story in Science Advances, identified a wearable human-machine interface device that is so thin a wearer might not even notice it. Cunjiang Yu, a Bill D. Cook associate professor of Mechanical Engineering at the University of Houston, was the lead author for the paper.

"Everything is very thin, just a few microns thick," says Yu, who also is a principal investigator at the Texas Center for Superconductivity at UH, in a release. "You will not be able to feel it."

The device is reported in the paper to be made of a metal oxide semiconductor on a polymer base. It could be attached to a robotic hand or prosthetic, as well as other robotic devices, that can collect and report information to the wearer.

"What if when you shook hands with a robotic hand, it was able to instantly deduce physical condition?" Yu asks in the release.

The device could also be used to help make decisions in situations that are hazardous to humans, such as chemical spills.

Current devices on the market or being developed are much slower to respond and bulkier to wear, not to mention expensive to develop.

"We report an ultrathin, mechanically imperceptible, and stretchable (human-machine interface) HMI device, which is worn on human skin to capture multiple physical data and also on a robot to offer intelligent feedback, forming a closed-loop HMI," the researchers write in the paper. "The multifunctional soft stretchy HMI device is based on a one-step formed, sol-gel-on-polymer-processed indium zinc oxide semiconductor nanomembrane electronics."

The paper's co-authors, in addition to Yu, include first author Kyoseung Sim, Zhoulyu Rao, Faheem Ershad, Jianming Lei, Anish Thukral, and Jie Chen, who are all from UH; Zhanan Zou and Jianliang Xiao of the University of Colorado; and Qing-An Huang of Southeast University in Nanjing, China.


Soft Wearable Multifunctional Human-Machine Interfaces (HMIs)www.youtube.com

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Houston researchers develop material to boost AI speed and cut energy use

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A team of researchers at the University of Houston has developed an innovative thin-film material that they believe will make AI devices faster and more energy efficient.

AI data centers consume massive amounts of electricity and use large cooling systems to operate, adding a strain on overall energy consumption.

“AI has made our energy needs explode,” Alamgir Karim, Dow Chair and Welch Foundation Professor at the William A. Brookshire Department of Chemical and Biomolecular Engineering at UH, explained in a news release. “Many AI data centers employ vast cooling systems that consume large amounts of electricity to keep the thousands of servers with integrated circuit chips running optimally at low temperatures to maintain high data processing speed, have shorter response time and extend chip lifetime.”

In a report recently published in ACS Nano, Karim and a team of researchers introduced a specialized two-dimensional thin film dielectric, or electric insulator. The film, which does not store electricity, could be used to replace traditional, heat-generating components in integrated circuit chips, which are essential hardware powering AI.

The thinner film material aims to reduce the significant energy cost and heat produced by the high-performance computing necessary for AI.

Karim and his former doctoral student, Maninderjeet Singh, used Nobel prize-winning organic framework materials to develop the film. Singh, now a postdoctoral researcher at Columbia University, developed the materials during his doctoral training at UH, along with Devin Shaffer, a UH professor of civil engineering, and doctoral student Erin Schroeder.

Their study shows that dielectrics with high permittivity (high-k) store more electrical energy and dissipate more energy as heat than those with low-k materials. Karim focused on low-k materials made from light elements, like carbon, that would allow chips to run cooler and faster.

The team then created new materials with carbon and other light elements, forming covalently bonded sheetlike films with highly porous crystalline structures using a process known as synthetic interfacial polymerization. Then they studied their electronic properties and applications in devices.

According to the report, the film was suitable for high-voltage, high-power devices while maintaining thermal stability at elevated operating temperatures.

“These next-generation materials are expected to boost the performance of AI and conventional electronics devices significantly,” Singh added in the release.

Houston to become 'global leader in brain health' and more innovation news

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Editor's note: The most-read Houston innovation news this month is centered around brain health, from the launch of Project Metis to Rice''s new Amyloid Mechanism and Disease Center. Here are the five most popular InnovationMap stories from December 1-15, 2025:

1. Houston institutions launch Project Metis to position region as global leader in brain health

The Rice Brain Institute, UTMB's Moody Brain Health Institute and Memorial Hermann’s comprehensive neurology care department will lead Project Metis. Photo via Unsplash.

Leaders in Houston's health care and innovation sectors have joined the Center for Houston’s Future to launch an initiative that aims to make the Greater Houston Area "the global leader of brain health." The multi-year Project Metis, named after the Greek goddess of wisdom and deep thought, will be led by the newly formed Rice Brain Institute, The University of Texas Medical Branch's Moody Brain Health Institute and Memorial Hermann’s comprehensive neurology care department. The initiative comes on the heels of Texas voters overwhelmingly approving a ballot measure to launch the $3 billion, state-funded Dementia Prevention and Research Institute of Texas (DPRIT). Continue reading.

2.Rice University researchers unveil new model that could sharpen MRI scans

New findings from a team of Rice University researchers could enhance MRI clarity. Photo via Unsplash.

Researchers at Rice University, in collaboration with Oak Ridge National Laboratory, have developed a new model that could lead to sharper imaging and safer diagnostics using magnetic resonance imaging, or MRI. In a study published in The Journal of Chemical Physics, the team of researchers showed how they used the Fokker-Planck equation to better understand how water molecules respond to contrast agents in a process known as “relaxation.” Continue reading.

3. Rice University launches new center to study roots of Alzheimer’s and Parkinson’s

The new Amyloid Mechanism and Disease Center will serve as the neuroscience branch of Rice’s Brain Institute. Photo via Unsplash.

Rice University has launched its new Amyloid Mechanism and Disease Center, which aims to uncover the molecular origins of Alzheimer’s, Parkinson’s and other amyloid-related diseases. The center will bring together Rice faculty in chemistry, biophysics, cell biology and biochemistry to study how protein aggregates called amyloids form, spread and harm brain cells. It will serve as the neuroscience branch of the Rice Brain Institute, which was also recently established. Continue reading.

4. Baylor center receives $10M NIH grant to continue rare disease research

BCM's Center for Precision Medicine Models has received funding that will allow it to study more complex diseases. Photo via Getty Images

Baylor College of Medicine’s Center for Precision Medicine Models has received a $10 million, five-year grant from the National Institutes of Health that will allow it to continue its work studying rare genetic diseases. The Center for Precision Medicine Models creates customized cell, fly and mouse models that mimic specific genetic variations found in patients, helping scientists to better understand how genetic changes cause disease and explore potential treatments. Continue reading.

5. Luxury transportation startup connects Houston with Austin and San Antonio

Shutto is a new option for Houston commuters. Photo courtesy of Shutto

Houston business and leisure travelers have a luxe new way to hop between Texas cities. Transportation startup Shutto has launched luxury van service connecting San Antonio, Austin, and Houston, offering travelers a comfortable alternative to flying or long-haul rideshare. Continue reading.

Texas falls to bottom of national list for AI-related job openings

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For all the hoopla over AI in the American workforce, Texas’ share of AI-related job openings falls short of every state except Pennsylvania and Florida.

A study by Unit4, a provider of cloud-based enterprise resource planning (ERP) software for businesses, puts Texas at No. 49 among the states with the highest share of AI-focused jobs. Just 9.39 percent of Texas job postings examined by Unit4 mentioned AI.

Behind Texas are No. 49 Pennsylvania (9.24 percent of jobs related to AI) and No. 50 Florida (9.04 percent). One spot ahead of Texas, at No. 47, is California (9.56 percent).

Unit4 notes that Texas’ and Florida’s low rankings show “AI hiring concentration isn’t necessarily tied to population size or GDP.”

“For years, California, Texas, and New York dominated tech hiring, but that’s changing fast. High living costs, remote work culture, and the democratization of AI tools mean smaller states can now compete,” Unit4 spokesperson Mark Baars said in a release.

The No. 1 state is Wyoming, where 20.38 percent of job openings were related to AI. The Cowboy State was followed by Vermont at No. 2 (20.34 percent) and Rhode Island at No. 3 (19.74 percent).

“A company in Wyoming can hire an AI engineer from anywhere, and startups in Vermont can build powerful AI systems without being based in Silicon Valley,” Baars added.

The study analyzed LinkedIn job postings across all 50 states to determine which ones were leading in AI employment. Unit4 came up with percentages by dividing the total number of job postings in a state by the total number of AI-related job postings.

Experts suggest that while states like Texas, California and Florida “have a vast number of total job postings, the sheer volume of non-AI jobs dilutes their AI concentration ratio,” according to Unit4. “Moreover, many major tech firms headquartered in California are outsourcing AI roles to smaller, more affordable markets, creating a redistribution of AI employment opportunities.”

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