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Houston researchers win prestigious DOE early career awards

James Shee, Naihao Chiang and Tony Geng have received the Department of Energy’s Early Career Award. Photos courtesy Rice and UH

Researchers at Rice University, the University of Houston and other Texas universities have been awarded the Department of Energy’s Early Career Award for their work in quantum science, AI and more.

Each professor who received the honor will be awarded $875,000 over five years to continue their work.

The Houston-area recipients include:

  • James Shee, assistant professor of chemistry at Rice University
  • Tony Geng, assistant professor of electrical and computer engineering at Rice
  • Naihao Chiang, assistant professor in the department of chemistry at the University of Houston

For Shee, the award will support his work to advance a “first principles platform to simulate the quantum dynamics of chemical systems of relevance to sustainable energy consumption and generation,” according to a news release from Rice.

“Support from the Department of Energy will enable my group to pursue the ambitious quantum chemistry development required to simulate the dynamics of transition metal-based molecular computing paradigms and multi-excitonic processes in a purely ab initio manner,” Shee said in the release.

Geng is developing next-generation AI for real-time digital twins for scientific systems. Geng and his team will make microchips that function as trainable electronic dynamical systems computing through natural, continuous evolution rather than digital instructions, according to the university.

Chiang’s work at UH addresses the DOE’s Quantum Information Science priority. Chiang leads a team that develops and applies “plasmonic-enhanced near-field optical techniques” to investigate fundamental light-matter interactions at the quantum limit before applying them to emerging technologies. In addition, the team will use AI to help with data acquisition and will utilize STEM workforce development.

Dr. Joshua Burby, an assistant professor in the Department of Physics at the University of Texas at Austin, and Junyeong Ahn, who is part of the University’s Texas Quantum Institute, also received early career awards for their work in superconducting and fusion technologies. See the full list of recipients from around the country here.

“The energy and creativity of early-career scientists is crucial for propelling scientific discovery forward. The Department of Energy is committed to nurturing this talent through programs like the Early Career Research Program,” Darío Gil, DOE under secretary for science, added in a release. “These awards provide essential resources and opportunities for collaboration, enabling these researchers to explore novel concepts and accelerate the development of solutions for our nation’s energy and scientific landscape.”

The DOE has also doled out funding to Houston researchers and companies in recent months through its Genesis Mission and geothermal initiatives.

Researchers from Rice, UH and Halliburton were named in July among the nearly 300 projects selected under the Trump administration's Genesis Mission, which aims to address some of the largest science and technology challenges in the country

In September, three Houston companies also received more than $45 million in funding from the DOE's Next-Generation Geothermal Field Tests and Geothermal Resource Characterization and Confirmation initiative to advance geothermal technologies and field tests. The projects were among 21 selected from around the country to receive a total of $99 million. Read more here.

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The company is known for its Orbital AI platform, which is tailored for the energy sector. Photo via solutions.kbr.com

Energy AI startup chooses Houston for first U.S. office after $20M raise

welcome to houston

London-based AI firm Applied Computing has announced a $20 million Series A round and a new office in Houston.

The new Bayou City office is Applied Computing’s first in the United States and part of its North American expansion. The company is known for its Orbital AI platform, which is tailored for energy operations.

The funding round was led by Houston-based KBR Inc., with participation from San Francisco-based Databricks Ventures. KBR’s investment was first announced in March.

KBR and Applied Computing have also entered into a multi-year agreement to deliver exclusive AI products for the energy sector. KBR already has integrated Orbital into its INSITE 3.0 platform for energy projects, and is also using the product for ammonia production.

Applied Computing’s Orbital platform combines physics-grounded intelligence with models across chemical engineering, time-series forecasting and language, according to the company. The system analyzes sensor readings and can recognize a facility’s equipment constraints and operator activity. The platform can also allow technicians to run simulations of how a change to a facility could affect the rest of its operations.

According to TechCrunch, Applied Computing will use the $20 million to further explore projects and deployments with the energy sector, hire engineering and research positions, and continue to expand internationally, potentially into the Middle East.

The company is also working on deals with a major U.S. stream operator, TechCrunch reports. And Applied Computing shared on LinkedIn that it plans to announce its first partnership with a major European oil company in the coming weeks.

“Yesterday we showed Orbital live in deployments at our demo day at the Energy Institute in London,” Callum Adamson, CEO and co-founder of Applied Computing, posted on LinkedIn on July 16. “Today, we're announcing the capital to scale it globally as well as the launch of our new offices in Houston and Bangalore. In the weeks following, there will be more announcements on our progress, partnerships and deployments.”

The company opened its Bangalore offices in December.

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This article originally appeared on our sister site, InnovationMap.com.

Scotty Nyquist discuss the growth in AI data centers and the strain on the system. Photo via HARC report

Houston energy expert asks: Who pays when AI outruns the power grid?

Guets Column

For most of the past 20 years, U.S. electricity policy relied on predictable trends in demand. Electricity use, in most regions, increased gradually, forecasts were stable, and utilities adjusted the system in small steps. Power plants, transmission lines, and substations were generally added to reflect shifts in load, rather than growth, and costs were recovered through modest adjustments to customer bills.

Growth in AI data centers has disrupted this model. A single facility can add as much electricity demand as a small town. That demand comes all at once, runs continuously, and has little tolerance for outages. If electricity service drops even briefly, computation stops, and services shut down. Ironically, data centers need reliable service, a point that their emergence is driving concern around for the rest of the grid.

What the numbers say

The International Energy Agency projects global electricity consumption from data centers to double by 2030, reaching roughly 945 TWh, nearly 3 percent of global electricity demand, with consumption growing about 15 percent per year this decade. McKinsey projects that U.S. data center demand alone could grow 20–25 percent per year, with global capacity demand more than tripling by 2030.

After years of roughly 0.5 percent annual demand growth, many forecasts now place total U.S. electricity demand growth closer to 2–3 percent per year through the mid-2030s, with much higher growth in specific regions. In Texas, some forecasters are saying electricity demand could double over the next five years, a staggering 10 percent per year growth rate. What sounds incremental on paper translates into a major challenge on the ground. Meeting this pace of growth is estimated to require $250–$300 billion per year in grid investment, about double what the system has been absorbing.

Where the system starts to strain

The strain appears first in the interconnection queue. It shows up as long waits, backlogs, and delays for connecting new loads and new generation.

Before new generators or large load customers can be connected, a study is required to assess their impact on the grid, whether it can physically handle the added load, and whether upgrades are required. With AI-driven data centers, utilities face far more connection requests than they can realistically support. In ERCOT, large-load interconnection requests exceed 200 gigawatts, most tied to data centers. That amount exceeds historical norms, and it is several times larger than what can be practically studied or built in the near term.

To be clear, public utility commissions are required to study these requests because they must manage system capabilities to ensure minimal disruption. This means engineers spend time evaluating projects that may never be built, while other more commercially viable projects may wait longer for approvals. This extends timelines and makes infrastructure planning less reliable.

Why policymakers are rethinking the rules

Utilities and their regulators must decide how much generation, transmission, and substation capacity to build years before it comes online. Those decisions are based on expected demand at the time projects are approved. When it comes to data centers, by the time infrastructure is completed, they may end up deploying newer, more efficient chips that use less power than originally assumed. This can result in grid infrastructure built for a higher load than what actually materializes, leaving excess capacity that still must be paid for through system-wide rates.

That’s the central dilemma. If utilities build too little capacity, the system operates with less reserve margin. During periods of grid stress, operators have fewer options, increasing the likelihood of curtailments or outages. However, if utilities build too much, customers may be asked to pay for infrastructure that is not fully used.

In response, policymakers are adjusting the rules. In some regions, regulators are moving toward bring-your-own-power approaches that require large data centers to supply or fund part of the capacity needed to serve them or reduce demand during system stress. At the federal level, permitting reforms tied to datacenter infrastructure increasingly treat electricity as a strategic economic input.

As Ken Medlock, senior director at the Baker Institute Center for Energy Studies (CES), explains:

“Many of the planned data centers are now also adding behind-the-meter options to their development plans because they do not anticipate being able to manage their needs solely from the grid, and they certainly cannot do so with only intermittent power sources.”

Behind-the-meter (BTM) refers to power that a consumer controls on its side of the utility meter, such as on-site gas generation or a dedicated power plant. These resources allow data centers to keep operating during grid-related service. Most facilities remain connected to the grid, but the backup BTM generation serves as insurance for operating their core business.

This shifts responsibility. Utilities traditionally manage reliability across all customers by maintaining an operating reserve margin, or spare capacity. Increasingly, large-load customers manage part of their own electricity reliability needs, which changes how infrastructure is planned and how risk is distributed.

Bottom line

AI-driven load growth is arriving faster and in more concentrated places than the power system was built to accommodate. Utilities and regulators are being forced to make decisions sooner than planned about where to build, how fast to build, and which customers get priority when capacity is limited. The effects extend beyond data centers, showing up in system costs, reliability margins, competition for grid access, and pressure on communities and industries that depend on affordable and dependable power. The issue is not whether electricity can be generated, but how the costs and risks of rapid demand growth are distributed as the system tries to keep up. How regulators balance these decisions will determine who pays as AI demand outruns the power grid.

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Scott Nyquist is a senior advisor at McKinsey & Company and vice chairman, Houston Energy Transition Initiative of the Greater Houston Partnership. The views expressed herein are Nyquist's own and not those of McKinsey & Company or of the Greater Houston Partnership. This article originally appeared on LinkedIn.

Collide has rolled out RIGGS, a large language model for energy professionals. Photo via Getty Images

Houston AI startup rolls out platform to reshape oil and gas workflows

AI for energy

Houston-based Collide is looking to solve AI issues in the energy industry from within.

Co-founded by former oil roughneck Collin McLelland, the company has developed AI software for operators and field teams, shaped by firsthand oilfield experience. Its AI-native platform “retrieves and synthesizes data from authoritative sources to deliver accurate, cited, and energy-focused insights to oil and gas professionals,” according to the company.

“Oil and gas has a graveyard full of technology that was technically impressive and operationally useless,” McLelland tells Energy Capital. “The reason is almost always the same: the people who built it didn't understand what they were actually solving for. When you're an outsider, you see workflows and try to automate them. When you're an insider, you understand why those workflows exist—the regulatory constraints, the physical realities, the liability concerns, the trust dynamics between operators and service companies.”

Collide’s large language model, known as RIGGS, performed well in recent benchmarking results when taking a standardized petroleum engineering (SPE) exam, the company reports. The exam assesses understanding from conceptual terminology to complex mathematical problem-solving.

According to Collide, RIGGS achieved a score of 67.5 percent on a 40-question subset of the SPE petroleum engineering exam, outperforming other large language models like Grok 4 (62.5 percent), Claude Sonnet 4.5 (52.5 percent) and GPT 5.1 (4 percent).

RIGGS completed the test in 15 minutes, while Grok took two hours. Collide hopes over the next few months, RIGGS will receive a score between 75 percent to 80 percent accuracy.

The software could potentially help oil and gas companies produce accurate outputs and automate trivial workflows, which can open up valuable time for engineers and teams to work on other pressing matters, according to McLelland.

“Collide exists because we sat in those seats — we were the engineers, the operators, the field guys,” he says. ”RIGGS scoring higher on the PE exam versus the frontier labs isn't a party trick. It's evidence that the model understands petroleum engineering the way a petroleum engineer does, because it was built by people who do.”

RIGGS was trained on Collide’s Spindletop hardware and is supported by a vast library of information, as well as a reasoning engine and validation layer that uses logic to solve problems.

“Longer term, we see RIGGS as the intelligence layer that sits underneath every operator's workflow — not a chatbot you open in a browser, but something embedded in the tools engineers already use,” McLelland says. “The goal is to give every engineer the knowledge and pattern recognition of a 30-year veteran, on demand."

According to McLelland, Collide is already building toward reservoir analysis and production optimization, automated regulatory compliance (Railroad Commission filings, W-10s, G-10s), workover report generation, and engineering decision support in the field for near-term use cases. In March, Collide and Texas-based oil and gas operator Winn Resources announced a collaboration to automate the time-intensive process of filing monthly W-10 and G-10 forms with the Texas Railroad Commission, completing what’s normally a multi-hour task in under 30 minutes. Collide reports that Winn’s infrastructure now automates regulatory filings and provides real-time visibility into data gaps, which has reduced processing time by over 95 percent.

“Before Collide, I'd spend hours manually keying in filings,” Buck Crum, director of operations, said in a news release. “(In March), we had 50 wells to file and I was done in 20 minutes. It does the majority of the heavy lifting while keeping me in control. That human-in-the-loop approach saves meaningful time and gives us greater confidence in our compliance and reporting.”

Collide was originally launched by Houston media organization Digital Wildcatters as “a professional network and digital community for technical discussions and knowledge sharing.” After raising $5 million in seed funding led by Houston’s Mercury Fund last year, the company said it would shift its focus to rolling out its enterprise-level, AI-enabled solution.
Hadi Ghasemi, a University of Houston professor, has uncovered a method to release heat from data centers and electronics at record performance. Photo courtesy UH.

Houston researcher develops efficient method to cool AI data centers

cool findings

A University of Houston professor has developed a new cooling method that can remove heat at least three times more effectively from AI data centers than current technologies.

Hadi Ghasemi, a distinguished professor of Mechanical & Aerospace Engineering at UH, published his findings in two articles in the International Journal of Heat and Mass Transfer. The findings solve a critical issue in the growing AI sector, according to UH.

High-powered AI data centers generate huge amounts of heat due to the GPU and operating systems they use with extreme power densities, which introduce complex thermal challenges. Traditionally, cooling methods, like microchannels, which use flow and spray cooling, have had limitations when exposed to extreme heat flux, according to UH.

Ghasemi’s research, however, found a more effective way to design thin-film evaporation structures to release heat from data centers and electronics at record performance.

Ghasem’s solution coupled topology optimization and AI modeling to determine the best shapes for thin film efficiency, ultimately landing on a branch-like structure—resembling a tree.

The model found that the “branches” needed to be about 50 percent solid and 50 percent empty space for optimum efficiency, and that they could sustain high heat fluxes with minimal thermal resistance.

“These structures could achieve high critical heat flux at much lower superheat compared to traditionally studied structures,” Ghasemi said in a news release. “The new structures can remove heat without having to get as hot as previous removal systems.

Ghasemi’s doctoral candidates, Amirmohammad Jahanbakhsh and Saber Badkoobeh Hezave, also worked on the project. The team believes their results show the impact of a physics-aware, AI design and can help ensure reliability, longevity and stability of AI data centers.

“Beyond achieving record performance, these new findings provide fundamental insight into the governing heat-transfer physics and establishes a rational pathway toward even higher thermal dissipation capacities,” Ghasemi added in the release

Merab Momen, founder of AI CTO Services. Courtesy Photo

How this Houston expert helps startups turn AI hype into real impact

now streaming

Artificial intelligence is now everywhere. It is mentioned in every startup pitch deck, and every corporate roadmap claims to use it. However, many early-stage businesses struggle with the simple question, “What does AI actually mean for my business?”

In a recent podcast episode of EnergyTech Startups, Merab Momen, founder of AI CTO Services and a long time AI practitioner, explains why most founders misunderstand AI, how startups can practically apply it and why Houston is quietly becoming a serious hub for AI-driven innovation.

Filling the AI Leadership Gap

Merab’s career has spanned decades of technology transitions. He worked on neutral networks in the 1990s, constructed computer vision systems long before they were common, and helped install AI solutions inside huge industrial companies. However, he noticed a huge problem when generative AI started to explode into the mainstream-The requirement of a real partner by the founders for AI integration but inability to rely on a full-time CTO and project-based consultants.

“I really needed something which is much more engaging where I can give that partner-level advice to the founders,” he said. By giving firms on-demand access to high-level AI knowledge and expertise, his methodology enables them to analyse tools, steer clear of cost blunders and eventually transition to a permanent technology leader when the time is right.

AI is Older than Most People Think

Despite its recent rise in popularity, AI is nothing new. AI actually began in the 1950s. Merab in his conversation explained how he worked on his first AI project back in the year 1996 that worked perfectly, but the processing power wasn’t just there to make it practical. He continued how he utilized the swarm intelligence models to optimize supply chains, now referred to as MLPOs and data engineering.

From Language Models to Physical World

Much of the public conversation about AI revolves around chatbots and text generation. But Merab sees far greater potential in AI’s interaction with the physical world, especially in industrial settings. He emphasized edge computing and vision language models (VLMs) as significant advances in manufacturing and energy. This physical shift is opening doors for new opportunities for robotics, automated inspections, and industrial safety applications. Merab added that Houston is uniquely positioned for this transition.

Why Houston has an AI Advantage

Silicon Valley may dominate the AI headlines, but Merab believes Houston’s advantage lies beneath the surface. The city doesn’t lag in AI utilization; it just operates in industries where results show differently.

Machine learning isn’t new to Houston’s core industries. Energy companies, manufacturers, logistics providers, and healthcare systems have been using advanced analytics for decades. The difference lies in them innovating in industrial sectors rather than consumer technology.

What’s Next

With the AI CTO Services growing, Merab is working with startups across industries to deploy AI in practical, business-first ways.

He is more interested in assisting founders in finding answers to critical issues than following new trends.

For Houston’s energy and climate tech community, it needs to transform AI enthusiasm into real-world impact.

Listen to the full conversation with Mehrab Momin on the Energy Tech Startups Podcast to learn more.

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Energy Tech Startups Podcast is hosted by Jason Ethier and Nada Ahmed. It delves into Houston's pivotal role in the energy transition, spotlighting entrepreneurs and industry leaders shaping a low-carbon future.


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Houston’s Fervo Energy amasses $12B backlog of orders

q3 results

Houston-based geothermal power company Fervo Energy saw a 65 percent spike in purchase orders during the third quarter.

During Fervo’s third-quarter earnings call, Tim Latimer, co-founder, chair, president and CEO, said the company had a $11.9 billion backlog of orders, up from $7.2 billion in the previous quarter.

Those numbers didn’t translate to robust financial results in the third quarter, though. It closed the quarter with an operating loss of $43 million on revenue of just $116,000.

Beyond the billions of dollars in signed purchase agreements, Fervo is in talks with prospective customers in the utility, industrial data-center sectors, Latimer said. About half the potential customers are in the data-center sector, 35 percent in the utility sector and 15 percent in the industrial sector.

Latimer said the broad-based demand reflected by the backlog and the discussions with potential customers reinforces the critical need for reliable, readily available power.

“Our approach to power delivery will continue to blend front-of-the-meter and behind-the-meter development,” he said. “Grid-connected assets remain the foundation, though behind-the-meter gives customers a faster path to power when transmission time lines lag their need.”

Front-of-the-meter refers to power plants, utility-scale solar and wind farms, large grid batteries, and transmission and distribution infrastructure. Behind-the-meter assets sit on the customer side of the meter, such as backup generators and EV chargers at homes, businesses, factories and other everyday places.

The order backlog isn’t Fervo’s only recent milestone. In late September, the company’s Cape Station geothermal plant in Utah started delivering its first utility-scale geothermal power to the grid. The plant is producing about 33 megawatts of power.

Earlier in September, Fervo signed a 15-year deal to supply about 396 megawatts of power for Google data centers. The power will be delivered in four 99-megawatt batches. The company filed its $1.89 billion IPO this spring.

3 Houston incubators supporting hard tech, energy transition, and beyond

Meet The Finalists

It takes a village to launch a business. That's where Houston's network of incubators and accelerators can step in, providing the resources, mentorship and community needed to push a fledgling company forward.

As part of InnovationMap's 2026 Houston Innovation Awards, the Incubator/Accelerator of the Year category honors a local organization that is championing and fueling the growth of Houston startups.

Three incubators and accelerators have been named finalists for the 2026 award. They support startups ranging from hard tech companies to food and youth concepts.

Read more about these organizations below. The 2026 winners will be announced on InnovationMap.com in mid-November.

Activate

Hard tech incubator Activate supports scientists in "the outset of their entrepreneurial journey." The Houston hub was introduced in 2024, and joins others in Boston, New York, and Berkley, California—where Activate is headquartered. It named its third Houston cohort this summer.

The two-year program graduated its first class of Houston fellows in 2026 and saw its first alumni IPO from Houston-based Fervo Energy, which previously participated in a Berkley cohort. Nationally, it has supported 346 fellows and 276 companies since 2015. Those companies have raised more than $6 billion in follow-on funding, according to Activate. In Houston, it has supported Houston startups like energy transition leaders Solidec and FlowCellutions. Activate Houston is led by managing director Jeremy Pitts, who co-founded Greentown Labs in Boston. It is based out of the Ion.

Impact Hub Houston

Impact Hub Houston supports early-stage ventures at various stages of development through innovative programs that address pressing societal issues. The nonprofit organization supports social impact startups through mentorship, connections and training opportunities.

There are more than 110 Impact Hubs globally with members spanning 72 countries. Launched in 2018, Impact Hub Houston says its membership tripled by the beginning of 2026. This year brought major milestones for the community, including the launch of its Ideas to Impact Accelerator, which supported 11 founders across the health, education, food systems, civic technology and workforce development sectors. It also received funding from more than 20 international Impact Hubs to develop SYNC, a collaboration platform that 25 Impact Hubs across five continents have committed to pilot. The organization has worked with local startups including Myoviva Health, The Change Lab and INNERVERSE Inc.

MarMo Innovation

Galveston-based business incubator MarMo Innovation is focused on removing barriers to entrepreneurship. It aims to provide affordable space, education, mentorship, market access, connections and real-world opportunities that help entrepreneurs move from idea to launch to sustainable growth. The "industry-agnostic" incubator was founded in 2022 and is led by Executive Director Erica Delgadillo.

This year, the organization moved from primarily serving as a coworking and community space into a more comprehensive entrepreneurial incubator by expanding its MarMo Market, MarMo Market Jr. and Lunch LineUp programs. A major focus for MarMo is food entrepreneurship. It is developing an Incubator Kitchen, which MarMo says will support programs like its Cottage to Commercial Bootcamp and Food Biz 101. The organization also expanded its board this year and says it is diversifying its revenue through memberships, events, markets, equipment and space rentals, sponsorships, grants and new entrepreneurial programming.

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This article first appeared on InnovationMap.com.

Sage Geosystems taps Halliburton to advance Nevada geothermal project

power partnership

Houston-based Sage Geosystems has selected oil and gas powerhouse Halliburton to provide cementing and stimulation services at its enhanced geothermal project in Nevada known as Project Vector.

“Our technology and experience will support Sage as it advances its geopressured geothermal technology,” Shawn Skobel, vice president at Halliburton, said in a news release.

Halliburton will provide Sage with technical modeling, engineering design, and field execution support as part of its specialized cementing and stimulation services at Project Vector at Ormat Technologies' Blue Mountain geothermal power plant. Sage announced the location of the geothermal project in September.

At the time, Sage said it expected to begin drilling the first well at Project Vector this year, with the first electricity to be generated in 2027 and full-scale production to start in 2028.

The project will use Sage’s enhanced geothermal systems (EGS) method in a two-well system to convert geothermal heat into electricity. The project aims to help meet industrial and residential demand, especially as data centers strain energy grids.

Founded in 2020, Sage has raised $159 million across three funding rounds. Its technology aims to reach Earth’s natural heat source deep underground for more consistent power generation and utilizes engineered subsurface reservoirs to minimize water and energy losses and increase net power output. Through the process, Sage says it can enable reliable, 24/7 power generation.

“One of the keys to scaling next-generation geothermal is combining innovative subsurface technology with the proven capabilities and execution of the oil and gas industry,” Jason Peart, Chief Operating Officer of Sage Geosystems, added in the news release. “Halliburton brings decades of experience in well integrity and reservoir stimulation, two critical components of our development approach. By selecting an established industry leader, we are strengthening our ability to execute Project Vector and demonstrate that Sage’s technology can be replicated and deployed commercially across a broad range of geologies.”

Sage is building off prior success of its South Texas SMECI facility, which began operations in August. Project Vector supports Sage’s growing commercial pipeline, which includes a 150-megawatt geothermal power agreement with Meta.

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