Data science startup based in Houston focus on neuroscience software nabs $3.78M grant

brain game

A Houston-based software startup received a multimillion-dollar grant from the National Institutes of Health for its work within neurophysiology. Getty Images

Armed with a nearly $3.8 million federal grant, a Houston startup aims to boost neuroscience research around the world.

Vathes LLC, a developer of data management software that collaborates with neuroscience research labs in North America and Europe, recently received the $3.78 million grant from the Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative at the National Institutes of Health (NIH). That initiative is part of the National Institute of Neurological Disorders and Stroke.

Vathes says the NIH funding will enable the startup to ramp up its DataJoint Pipelines for Neurophysiology project. The project aims to make open-source software for data science and engineering available to researchers who specialize in neurophysiology, a branch of neuroscience that looks at how the nervous system functions. The pipeline project holds the promise of benefiting research in areas like autism, Alzheimer's disease, and amyotrophic lateral sclerosis (ALS, or Lou Gehrig's disease).

The project's principal investigator is Dimitri Yatsenko, vice president of research and development at Vathes. Technologically speaking, neuroscientists are playing catch-up with their counterparts in fields like astrophysics, genomics, and bioinformatics, according to Yatsenko.

Neuroscience "is undergoing a fast transformation in terms of moving toward much more data-centric, data-intensive, computation-intensive, and collaborative projects," Yatsenko says. This means that neuroscientists are "now finding themselves having to quickly adapt to an environment," he adds, "where they have to share big data and computations with their collaborators in very dynamic settings and perform them in a very fluid way."

Yatsenko says the NIH-funded project will help smaller research groups tap into the technical expertise of larger research labs.

Vathes' DataJoint Neuro platform and services, which help create so-called DataJoint pipelines, enable neuroscientists to streamline, analyze, and visualize complex data. Among its customers are Princeton University's Neuroscience Institute and Columbia University's Zuckerman Institute. The federally funded project will empower smaller labs to capitalize on existing DataJoint pipelines as ready-to-go turnkey packages, Yatsenko says.

In essence, Vathes' technology acts as a translator. Big research labs collect data in databases that can vary by computer language and platform. Through the Vathes setup, that data can be incorporated by a lab of any size into algorithmic, machine learning, and artificial intelligence mechanisms, regardless of the computer language or platform.

Edgar Walker, CEO of Vathes, says this simplifies the construction and use of databases, giving scientists "more room to focus on the logic of their data pipeline rather than on the physical implementation of it."

Founded in 2016, Vathes is housed at the Texas Medical Center's Innovation Institute. It employs 10 people. The startup previously received a $100,000 grant from the U.S. Defense Advanced Research Projects Agency (DARPA).

Yatsenko says the project backed by the $3.78 million NIH grant will propel the startup's growth, as it "gives us a big window of opportunity" to provide tools and services that support the startup's open-source software.

"As the NIH and other funding agencies are shifting a lot of their focus to collaborative projects that are distributed among multiple institutions," Walker says, "we've established a reputation as the company that can facilitate such research, be efficient, and actually be cost-effective as well, and make the projects very smooth."

"We expect to continue to grow this business at the same exponential rate," he adds. "We'll keep our fingers crossed and see how things go."


CEO Edgar Walker (left) and Dimitri Yatsenko, vice president of research and development, lead Houston-based Vathes. Photos courtesy of Vathes

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Houston unicorn closes $421M to fuel first phase of flagship energy project

Heating Up

Houston geothermal unicorn Fervo Energy has closed $421 million in non-recourse debt financing for the first phase of its flagship Cape Station project in Beaver County, Utah.

Fervo believes Cape Station can meet the needs of surging power demand from data centers, domestic manufacturing and an energy market aiming to use clean and reliable power. According to the company, Cape Station will begin delivering its first power to the grid this year and is expected to reach approximately 100 megwatts of operating capacity by early 2027. Fervo added that it plans to scale to 500 megawatts.

The $421 million financing package includes a $309 million construction-to-term loan, a $61 million tax credit bridge loan, and a $51 million letter of credit facility. The facilities will fund the remaining construction costs for the first phase of Cape Station, and will also support the project’s counterparty credit support requirements.

Coordinating lead arrangers include Barclays, BBVA, HSBC, MUFG, RBC and Société Générale, with additional participation from Bank of America, J.P. Morgan and Sumitomo Mitsui Trust Bank, Limited, New York Branch.

“As demand for firm, clean, affordable power accelerates, EGS (Enhanced Geothermal Systems) is set to become a core energy asset class for infrastructure lenders,” Sean Pollock, managing director, project Finance at RBC Capital Markets, said in a news release. “Fervo is pioneering this step change with Cape Station, a vital contribution to American energy security that RBC is proud to support.”

The oversubscribed financing marks Cape Station’s shift from early-stage and bridge funding to a long-term, non-recourse capital structure, according to the news release.

“Non-recourse financing has historically been considered out of reach for first-of-a-kind projects,” David Ulrey, CFO of Fervo Energy, said in a news release. “Cape Station disrupts that narrative. With proven oil and gas technology paired with AI-enabled drilling and exploration, robust commercial offtake, operational consistency, and an unrelenting focus on health and safety, we have shown that EGS is a highly bankable asset class.”

Fervo continues to be one of the top-funded startups in the Houston area. The company has raised about $1.5 billion prior to the latest $421 million. It also closed a $462 million Series E in December.

According to Axios Pro, Fervo filed for an IPO that would value the company between $2 billion and $3 billion in January.

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This article first appeared on EnergyCapitalHTX.com.

Houston food giant Sysco to acquire competitor in $29 billion deal

Mergers & Acquisitions

Sysco, the nation's largest food distributor, will acquire supplier Restaurant Depot in a deal worth more than $29 billion.

The acquisition would create a closer link between Sysco and its customers that right now turn to Restaurant Depot for supplies needed quickly in an industry segment known as “cash-and-carry wholesale.”

Sysco, based in Houston, serves more than 700,000 restaurants, hospitals, schools, and hotels, supplying them with everything from butter and eggs to napkins. Those goods are typically acquired ahead of time based on how much traffic that restaurants typically see.

Restaurant Depot offers memberships to mom-and-pop restaurants and other businesses, giving them access to warehouses stocked with supplies for when they run short of what they've purchased from suppliers like Sysco.

It is a fast growing and high-margin segment that will likely mean thousands of restaurants will rely increasingly on Sysco for day-to-day needs.

Restaurant Depot shareholders will receive $21.6 billion in cash and 91.5 million Sysco shares. Based on Sysco’s closing share price of $81.80 as of March 27, 2026, the deal has an enterprise value of about $29.1 billion.

Restaurant Depot was founded in Brooklyn in 1976. The family-run business then known as Jetro Restaurant Depot, has become the nation's largest cash-and-carry wholesaler.

The boards of both companies have approved the acquisition, but it would still need regulatory approval.

Shares of Sysco Corp. tumbled 13% Monday to $71.26, an initial decline some industry analysts expected given the cost of the deal.

Houston researcher builds radar to make self-driving cars safer

eyes on the road

A Rice University researcher is giving autonomous vehicles an “extra set of eyes.”

Current autonomous vehicles (AVs) can have an incomplete view of their surroundings, and challenges like pedestrian movement, low-light conditions and adverse weather only compound these visibility limitations.

Kun Woo Cho, a postdoctoral researcher in the lab of Rice professor of electrical and computer engineering Ashutosh Sabharwal, has developed EyeDAR to help address such issues and enhance the vehicles’ sensing accuracy. Her research was supported in part by the National Science Foundation.

The EyeDAR is an orange-sized, low-power, millimeter-wave radar that could be placed at streetlights and intersections. Its design was inspired by that of the human eye. Researchers envision that the low-cost sensors could help ensure that AVs always pick up on emergent obstacles, even when the vehicles are not within proper range for their onboard sensors and when visibility is limited.

“Current automotive sensor systems like cameras and lidar struggle with poor visibility such as you would encounter due to rain or fog or in low-lighting conditions,” Cho said in a news release. “Radar, on the other hand, operates reliably in all weather and lighting conditions and can even see through obstacles.”

Signals from a typical radar system scatter when they encounter an obstacle. Some of the signal is reflected back to the source, but most of it is often lost. In the case of AVs, this means that "pedestrians emerging from behind large vehicles, cars creeping forward at intersections or cyclists approaching at odd angles can easily go unnoticed," according to Rice.

EyeDAR, however, works to capture lost radar reflections, determine their direction and report them back to the AV in a sequence of 0s and 1s.

“Like blinking Morse code,” Cho added. “EyeDAR is a talking sensor⎯it is a first instance of integrating radar sensing and communication functionality in a single design.”

After testing, EyeDAR was able to resolve target directions 200 times faster than conventional radar designs.

While EyeDAR currently targets risks associated with AVs, particularly in high-traffic urban areas, researchers also believe the technology behind it could complement artificial intelligence efforts and be integrated into robots, drones and wearable platforms.

“EyeDAR is an example of what I like to call ‘analog computing,’” Cho added in the release. “Over the past two decades, people have been focusing on the digital and software side of computation, and the analog, hardware side has been lagging behind. I want to explore this overlooked analog design space.”

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