Houston researcher tries to crack the code on the Fed's data to determine economic outlook

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There's no crystal ball, but this researcher from Rice University is trying to see if some metrics work for economic forecasting. Photo via Getty Images

Research by Rice Business Professor K. Ramesh shows that the Fed appears to harvest qualitative information from the accounting disclosures that all public companies must file with the Securities and Exchange Commission.

These SEC filings are typically used by creditors, investors and others to make firm-level investing and financing decisions; and while they include business leaders’ sense of economic trends, they are never intended to guide macro-level policy decisions. But in a recent paper (“Externalities of Accounting Disclosures: Evidence from the Federal Reserve”), Ramesh and his colleagues provide persuasive evidence that the Fed nonetheless uses the qualitative information in SEC filings to help forecast the growth of macroeconomic variables like GDP and unemployment.

According to Ramesh, the study was made possible thanks to a decision the SEC made several years ago. The commission stores the reports submitted by public companies in an online database called EDGAR and records the IP address of any party that accesses them. More than a decade ago, the SEC began making partially anonymized forms of those IP addresses available to the public. But researchers eventually figured out how to deanonymize the addresses, which is precisely what Ramesh and his colleagues did in this study.

"We were able to reverse engineer and identify those IP addresses that belonged to Federal Reserve staff," Ramesh says.

The team ultimately assembled a data set containing more than 169,000 filings accessed by Fed staff between 2005 and 2015. They quickly realized that the Fed was interested only in filings submitted by a select group of industry leaders and financial institutions.

But if Ramesh and his colleagues now had a better idea of precisely which bellwether firms the Fed focused on, they still had no way of knowing exactly what Fed staffers had gleaned from the material they accessed. So the team decided to employ a measure called "tone" that captures the overall sentiment of a piece of text – whether positive, negative, or neutral.

Building on previous research that had identified a set of words with negatively toned financial reports, Ramesh and his colleagues examined the tone of all the SEC filings accessed by Fed staff between one meeting of the Federal Open Markets Committee (FOMC) and the next. The FOMC sets interest rates and guides monetary policy, and its meetings provide an opportunity for Fed officials to discuss growth forecasts and announce policy decisions.

The researchers then examined the Fed's growth forecasts to see if there was a relationship between the tone of the documents that Fed staff examined in the period between FOMC meetings and the forecasts they produced in advance of those meetings.

The team found close correlations between the tone of the reports accessed by the Fed and the agency’s forecasts of GDP, unemployment, housing starts and industrial production. The more negative the filings accessed prior to an FOMC meeting, for example, the gloomier the GDP forecast; the more positive the filings, the brighter the unemployment forecast.

Ramesh and his colleagues also compared the Fed's forecasts with those of the Society of Professional Forecasters (SPF), whose members span academia and industry. Intriguingly, the researchers found that while the errors in the SPF's forecasts could be attributed to the absence of the tonal information culled from the SEC filings, the errors in the Fed’s forecasts could not. This suggests both that the Fed was collecting qualitative information that the SPF was not—and that the agency was making remarkably efficient use of it.

"They weren’t leaving anything on the table," Ramesh says.

Having solved one mystery, Ramesh would like to focus on another; namely, how does the Fed identify bellwether firms in the first place?

Unfortunately, the SEC no longer makes IP address data publicly available, which means that Ramesh and his colleagues can no longer study which companies the Fed is most interested in. Nonetheless, Ramesh hopes to use the data they have already collected to build a model that can accurately predict which firms the Fed is most likely to follow. That would allow the team to continue studying the same companies that the Fed does, and, he says, “maybe come up with a way to track those firms in order to understand how the economy is going to move.”

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This article originally ran on Rice Business Wisdom and was based on research from K. Ramesh is Herbert S. Autrey Professor of Accounting at Jones Graduate School of Business at Rice University.

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Equity options can act as an alternative to credit default swaps for detecting a company’s credit risk. Photo via Getty Images

Rice research explains a new way to measure default risk for investors

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Up until the 2007-2009 financial crisis, credit default swaps (CDS) were a predominant method for predicting the probability of corporate default. CDS function like insurance for loan assets — if an asset defaults, the bank who purchased the CDS would recoup their loss. Higher-risk assets usually have higher premiums, and in this way the price of a CDS indicates the probability of default.

When the housing market crashed in 2007, the CDS market crashed along with it when banks had to pay out more than they had expected. The CDS market is not expected to ever return to its previous high, leaving a void in market-driven estimates for determining an asset’s default probability.

To fill that void, a team of researchers including Rice Business Professor Robert Dittmar created an alternative method for measuring default risk: equity options data. The team found that equity options not only correlate with CDS data in terms of accurate prediction of default but also provide additional insights on what types of assets are more likely to default, and when they will default.

There are two types of options, a call option, which is essentially a bet that a stock’s price will be higher than a contracted value (the strike price) and a put option, which is a bet that a stock’s price will be less than a contracted value.

A put is often viewed as an insurance contract — if you hold a stock, but also a put option on it, you limit your loss on the stock if the stock price falls.

“What we are looking at is essentially how expensive put options get,” says Dittmar. “If the market thinks a company is likely to default, it expects that its stock value will fall (almost to zero). As a result, put options, which represent insurance against this loss become more expensive. We are looking at how these option prices change to see if they inform us about the probabilities of default.”

According to Dittmar and his team, this approach has several advantages. 1) There are more stocks with options than CDS. 2) The CDS market is drying up whereas the option market remains liquid. And 3) Because of the nature of an option contract, and the fact that in principle equity holders have the lowest claim on a company’s assets, this approach may allow investors to predict losses in case of default.

The team looked at CDS quotes on 276 firms between 2002 and 2017, focusing attention on entities that had quote data available on one-year credit default swaps. The 15-year sample enabled the researchers to analyze the money lost through defaults over a longer period of time, including the 2007-2009 financial crisis.

Using equity options data as a predictor of default led to some interesting insights. First, there are two components that investors in corporate bonds think about when weighing default risk — the probability of default and (should there be a default) how much of the bond’s principal they will get back (i.e., recovery rate). “What we see is that credit ratings imply different levels of default thresholds, which may mean that investors believe that there are differences in the amount that debt holders will lose in the case of default,” says Dittmar.

Second, option-implied default probabilities correlate to historical changes in the economy. Default probabilities are higher in bad economic times and for firms with poorer credit ratings and financial positions. Default spikes are more likely during times of economic turbulence, such as the financial crisis of 2007-2009, which correlated with the decline of the CDS market after an onslaught of debt defaults during the recession. Assets are less likely to default during times of economic expansion. Over the period of 2013-2017, forecasted losses through defaults hovered around 15%.

The research sample ends in 2017, and the paper was published in 2020, about a month after the start of the coronavirus pandemic. Since then, there have been unprecedented changes in the economy, and some economists are anticipating another recession in 2023. With such instability in the market, multiple methods of predicting losses should be especially relevant. This research suggests that the equity options market may provide additional ways of finding the probability of these losses.

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This article originally ran on Rice Business Wisdom and was based on research from Robert Dittmar, professor of finance at the Jones Graduate School of Business at Rice University.

Earnings report delays generally lead to drops in stock prices. Disclosure can soften this market reaction. Photo via Getty Images

Houston research: Is no news always bad news in market reports?

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Investors eagerly wait for the news in their earnings reports. When these reports don't appear on the expected date, investors worry — and stock prices often fall as a result. But what if managers could present late reports in a way that spared their companies?

Research by K. Ramesh, a professor at Rice Business, shows that managers' approach to late earnings reports can profoundly affect market reaction. When firms put off filing a report, it's up to managers to decide whether to speak up or stay quiet. Those who choose to talk about a postponement then must decide how, what and how much to say.

All earnings delays, whether they're attended by a statement or not, prompt negative market reaction, prior research suggests. But in his research, Ramesh, Herbert S. Autrey Professor of Accounting, wanted to learn more about the exact consequences of these late reports, and how managers can lessen the blowback.

To do this, Ramesh and a team of coauthors first looked at the incidence, timing and contents of a comprehensive sample of press releases announcing an earnings delay. Then they studied what those delays did to market value.

Conventional wisdom in the business press already suggested that investors viewed any announcement of a delayed earnings report as bad news. But finance theorists tell a more complicated story, one in which the market response might be partially shaped by managerial behavior. Subtle factors, they found, such as whether the impending delay is discussed or treated with silence, really can make a difference.

In the view of some theorists, merely announcing a delay can sometimes avert a drop in stock prices. Others argue that this isn’t necessarily the case, especially if the company discloses that the delay stemmed from legal concerns. The better approach: making it clear up front that reports aren't being postponed to hide disastrous information. But what if the information is indeed disastrous?

That may be the one case where disclosure won’t change much, Ramesh and his team found.

“Those companies that are in fact concealing disastrous results will experience no benefits (in the form of higher stock price) from revealing their true situation,” the research team wrote, “because the market will infer the worst from the manager’s decision not to announce the delay.” For this reason, they added, delayed earnings without a stated explanation prompt the most negative market reaction. As in so many areas of public relations, without a narrative, investors will infer a negative one of their own.

To better understand the impact of late reports, Ramesh and his coauthors built a comprehensive sample of 545 delay announcements by using a keyword search of the Dow Jones Factiva database between January 1, 1995, and December 31, 2009.

As conventional wisdom suggested, the study showed that announcements of late earnings reports led to negative market reactions. (Earlier studies have shown smaller firms are hit hardest by this dynamic, perhaps because investors assume large companies have more finely tuned financial reporting systems, so are less worried by their earnings delays).

Consistent with the anecdotal evidence, the average one-day abnormal stock return for the sample was -6.29 percent, while the median return was -2.27 percent. Both figures are economically and statistically significant.

The researchers next classified the announcements according to stated reason, dividing the delays into “Accounting” and “Non-Accounting” categories. “Accounting” explanations were subdivided into “Accounting Issue,” “Accounting Process” and “Rule Change.”

Meanwhile, “Non-Accounting” explanations were divided into “Business,” which linked the delay to some event such as divestitures or regulatory proceedings, and “Other,” which ranged from earthquakes to power outages. Finally, there were delays for no stated reason at all.

About two-thirds of the late announcements, the team found, were linked to accounting. When firms named a specific accounting issue as the cause for delay, the average abnormal return reached a statistically significant -8.15 percent. When managers explained that the accounting process was not complete, the average abnormal return was slightly lower, at -7.04 percent.

After accounting issues, business events drove most earnings delays. In theory, these events could have been either good or bad news. But the average abnormal return for the subsample was a statistically significant -3.74 percent — a reflection of the fact that most business events linked to late earnings reports tend to be negative.

Curiously, the average abnormal return for the grouping classified as “Other” was almost nil — at 0.53 percent. This suggests that the market does not penalize managers for events outside of their control that have little, if any, relevance to firm performance.

“No Reason,” the researchers found, was the most damaging explanation of all. Seven percent of the sample, or 37 out of 545 delays, came without a stated reason. The average abnormal return for these was a significant -10.41 percent, a greater negative number than the returns for any of the other reasons.

So what should managers do when a deadline is going to be busted? Bite the bullet and disclose the reasons, Ramesh suggests. For one thing, it helps limit legal exposure and preserve credibility. When the reason for the late report is innocuous, explaining to investors can also mitigate the market's displeasure. A caveat: While informing investors that a power outage caused earnings delay will calm jitters, disclosure may not make a difference if the company just can’t balance its books.

It's human nature, apparently, to read no news as bad news. Relaying something—anything—about the cause of a late report seems to soothe investors' nerves by preventing them from filling the silence themselves.

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This article originally ran on Rice Business Wisdom and was based on research from K. Ramesh, Tiago Duarte-Silva, Huijing Fu and Christopher F. Noe. K. Ramesh is the Herbert S. Autrey Professor of Accounting at Jones Graduate School of Business at Rice University.

Research shows that some corporate executives skew earnings to influence the market and inflate share price. Photo via Pexels

Rice University research finds market outliers at risk of misreporting

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Say a company called CoolConsumerGoodsCo has just released its quarterly earnings report, revealing significantly higher profits than its consumer goods industry counterparts.

That result might spur analysts to slap a buy rating on the stock and investors to snap up shares. In an ideal world, the market wouldn't have to consider the possibility that the numbers aren't legit — but then again, it's not an ideal world. (Enron, anyone?)

Rice Business professors Brian R. Rountree and Shiva Sivaramakrishnan, along with Andrew B. Jackson at UNSW in Australia, studied what makes business leaders more likely to engage in fraudulent earnings reporting. Specifically, they focused on the relationship between this kind of misrepresentation and the degree to which a company's earnings are in line with the rest of its industry — a variable the researchers term "co-movements."

Many people are familiar with a similar variable, calculated using stock returns often referred to as a company's beta. The authors adapted the stock return beta to corporate earnings to see how a company's earnings move with earnings at the industry level.

The researchers hypothesized that the less in sync a company's earnings are with its industry, the higher the chance a company's leaders will manipulate earnings reports. They started with the well-accepted premise that corporations try to skew earnings reports to influence the market. The primary motive is typically to raise the company's stock price, as when an executive tries to "choose a level of bias" that balances potential fallout of getting caught against the benefits of a higher stock price.
 
To test their prediction, the professors analyzed a sample of enforcement actions taken by the U.S. Securities and Exchange Commission against companies for problematic financial reporting from 1970 to 2011 — although they noted that given the SEC's limited resources, the number of enforcement actions probably underestimates the actual amount of earnings manipulation in the market.

Their analysis revealed that firms with low earnings co-movements (meaning their earnings were out of sync with industry peers) were more likely to be accused by the SEC of reporting misdeeds. They concluded that the degree of earnings co-movement determines the probability of earnings manipulation. Put another way, earnings co-movements are a "causal factor" in the chances of earnings manipulations — and to a significant degree. The researchers found that firms who don't co-move with the market are more than 50 percent more likely to face an SEC enforcement action, compared with firms who are perfectly aligned with the market.

The researchers drilled deeper into the data to study whether the odds changed depending on the industry, since past research has indicated that the amount of competition in an industry works to constrain misreporting. That premise seems to hold true, the researchers concluded. In industries with more competitive markets, the impact of low co-movement on earnings manipulation is moderated.

They also studied whether the age of a firm played a part in the likelihood of earnings manipulation. Newer firms often rely more on stock compensation, which could be a motive for manipulating earnings reporting to drive up share price. Indeed, younger firms were more susceptible to misreporting when their earnings were out of whack with the rest of the marketplace.

Every firm faces some risk of misreporting, however. Even for public companies under analyst scrutiny, low co-movement proved to be a driver of earnings manipulation. But companies known for conservative reporting tend to be less likely to exaggerate their earnings, in general; these firms typically recognize losses in a more timely manner, the professors found.

These findings suggest a number of future lines of research. For example: When do executives underreport earnings? And can analyzing patterns related to cash flow reporting help better isolate earnings manipulation?

In the meantime, if you come across a company like CoolConsumerGoodsCo with an earnings report that's widely out of sync with the rest of its industry, you might think twice before rushing to buy in.
 

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This article originally ran on Rice Business Wisdom and is based on research from Brian R. Rountree, an associate professor of accounting at the Jones Graduate School of Business at Rice University, and Shiva Sivaramakrishnan is the Henry Gardiner Symonds Professor of Accounting at Rice Business.

John Berger, CEO of Houston-based Sunnova, is this week's Houston Innovators Podcast guest. Courtesy of Sunnova

Houston solar energy exec shines light on company growth and IPO

HOUSTON INNOVATORS PODCAST EPISODE 15

It was all about the timing for John Berger, founder and CEO of Sunnova, a Houston-based residential solar energy company.

When he founded his company in 2012 in Houston, solar energy wasn't the trendy sustainability option it is today, but Berger saw the potential for technology within the industry. So, with a lot of perseverance and the right team behind him, he scaled Sunnova through nationwide expansion, billions of money raised, and a debut on the stock market last July — something that also happened with great timing.

About 72 hours after Sunnova went public last July, the Federal Reserve System announced it was going to cut rates. Additionally, Sunnova's IPO occurred ahead of WeWork's failed IPO.

"We went public in a market that still isn't back open again, I think, for IPOs," Berger says on this week's episode of the Houston Innovators Podcast. "We had pretty good timing when we went out the door."

However great the timing was, Sunnova's success is built on the hard work and skills of the company's employees, Berger explains on the podcast, and now running a public company requires a dynamic leader.

"I really look at myself and how I can change myself," Berger says. "I'm a different CEO today than I was 12 months ago, and hopefully I'll be a different CEO in 12 months, because the company demands it."

In the episode, Berger lifts the curtain on Sunnova's IPO, explains where he sees the solar energy industry headed, how battery storage technology has evolved, and why he's not worried about who ends up in the White House. Listen to the full episode below — or wherever you get your podcasts — and subscribe for weekly episodes.


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Texas cybersecurity co. expands unique train-to-hire model to Houston

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It’s increasingly more difficult to ensure the confidentiality, integrity, and availability of proprietary data and information in the ever-changing, ever-evolving digital world.

Cyberattacks, including malware, phishing, and ransomware, are becoming increasingly common and sophisticated, posing a consistent threat to a company’s sustainability and bottom line.

To combat that trend, Nukudo, a San Antonio-based cybersecurity workforce development company, is expanding its initiative to bridge the global cybersecurity talent gap through immersive training and job placement to Houston.

“We saw that there was a need in the market because there's a shortage of skilled manpower within the cybersecurity industry and other digital domains,” says Dean Gefen, CEO of NukuDo. “So, our initial goal was to take a large pool of people and then make them to be fully operational in cybersecurity in the shortest amount of time.”

The company refers to the plan as the “training-to-employment model,” which focuses on providing structured training to select individuals who then acquire the skills and knowledge necessary to secure and maintain fruitful careers.

The company identifies potential associates through its proprietary aptitude test, which recognizes individuals who possess the innate technical acumen and potential for success in various cybersecurity roles, regardless of their level of education.

“We take in people from all walks of life, meaning the program is purely based on the associate’s potential,” Gefen says. “We have people who were previously aircraft engineers, teachers, graphic designers, lawyers, insurance agents and so forth.”

Once selected, associates are trained by cybersecurity experts while gaining hands-on experience through scenario-based learning, enabling them to be deployed immediately as fully operational cybersecurity professionals.

The program training lasts just six months—all paid—followed by three years of guaranteed employment with NukuDo.

While in training, associates are paid $ 4,000 per month; then, they’re compensated by nearly double that amount over the next three years, ultimately pushing their salaries to well into the six figures after completing the entire commitment.

In addition to fostering a diverse talent pipeline in the cybersecurity field, NukuDo is creating a comprehensive solution to address the growing shortage of technical talent in the global workforce.

And arming people with new marketable skills has a litany of benefits, both professional and personal, Gefen says.

“Sometimes, we have associates who go on to make five times their previous salary,” says Gefen. “Add to that fact that we had someone that had a very difficult life beforehand and we were able to put him on a different path. That really hits home for us that we are making a difference.

Nulkudo currently has partnerships with companies such as Accenture Singapore and Singapore Airlines. Gefen says he and his team plans to have a new class of associates begin training every month by next year and take the model to the Texas Triangle (Houston, Austin and Dallas)—then possibly nationwide.

“The great thing about our program is that we train people above the level of possible threat of replacement by artificial intelligence,” Gefen says. “But what we are also doing, and this is due to requirements that we have received from clients that are already hiring our cyber professionals, is that we are now starting to deliver AI engineers and data scientists in other domains.”

“That means that we have added more programs to our cybersecurity program. So, we're also training people in data science and machine learning,” he continues.

All interested candidates for the program should be aware that a college degree is not required. NukuDo is genuinely interested in talented individuals, regardless of their background.

“The minimum that we are asking for is high school graduates,” Gefen says. “They don't need to have a college degree; they just need to have aptitude. And, of course, they need to be hungry to make this change.”

2 Houston universities declared among world’s best in 2026 rankings

Declaring the Best

Two Houston universities are in a class of their own, earning top spots on a new global ranking of the world's best universities.

Rice University and University of Houston are among the top 1,200 schools included in the QS World University Rankings 2026. Ten more schools across Texas make the list.

QS (Quacquarelli Symonds), a London-based provider of higher education data and analytics, compiles the prestigious list each year; the 2026 edition includes more than 1,500 universities from around the world. Factors used to rank the schools include academic reputation; employer reputation; faculty-student ratio; faculty research; and international research, students, and faculty.

In Texas, University of Texas at Austin lands at No. 1 in the state, No. 20 in the U.S., and No. 68 globally.

Houston's Rice University is close behind as Texas' No. 2 school. It ranks 29th in the U.S. and No. 119 in the world. Unlike UT, which fell two spots globally this year (from No. 66 to 68), Rice climbed up the charts, moving from 141st last year to No. 119.

University of Houston impresses as Texas' 4th highest-ranked school. It lands at No. 80 in the U.S. and No. 556 globally, also climbing about 100 spots up the chart.

Rice and UH are on a roll in regional, national, and international rankings this year.

Rice earned top-15 national rankings by both Niche.com and Forbes last fall. Rice claimed No. 1 and UH ranked No. 8 in Texas in U.S. News & World Report's 2025 rankings. Rice also topped WalletHub's 2025 list of the best colleges and universities in Texas for 2025.

More recently, in April, both UH and Rice made U.S. News' 2025 list of top grad schools.

In all, 192 U.S. universities made the 2026 QS World University Rankings — the most of any country. Topping the global list is the Massachusetts Institute of Technology (MIT).

“The results show that while U.S. higher education remains the global leader, its dominance is increasingly challenged by fast-rising emerging systems,” says the QS World University Rankings report. “A decade ago, 32 American universities [were] featured in the world’s top 100; today, that number has dropped to 26, and only 11 of these institutions have improved their position this year."

The 12 Texas universities that appear in the QS World University Rankings 2026 list are:

  • University of Texas at Austin, No. 20 in the U.S. and No. 68 in the world (down from No. 66 last year).
  • Rice University, No. 29 in the U.S. and No. 119 in the world (up from No. 141 last year).
  • Texas A&M University, No. 32 in the U.S. and No. 144 in the world (up from No. 154 last year).
  • University of Houston, No. 80 in the U.S. and No. 556 in the world (up from 651-660 last year).
  • University of Texas at Dallas, No. 85 in the U.S. and No. 597 in the world (down from 596 last year).
  • Texas Tech University, No. 104 in the U.S. and No. 731-740 in the world (unchanged from last year).
  • University of North Texas, No. 123 in the U.S. and No. 901-950 in the world (up from 1,001-1,200 last year)
  • Baylor University, tied for No. 136 in the U.S. and at No. 1,001-1,200 in the world (unchanged from last year).
  • Southern Methodist University, tied for No. 136 in the U.S. and at 1,001-1,200 in the world (unchanged from last year).
  • University of Texas Arlington, tied for No. 136 in the U.S. and at 1,001-1,200 in the world (unchanged from last year).
  • University of Texas at San Antonio, tied for No. 136 in the U.S. and at 1,001-1,200 in the world (unchanged from last year).
  • University of Texas at El Paso, No. 172 in the U.S. and at 1,201-1,400 in the world (down from 1,001-1,200 last year).
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This article originally appeared on CultureMap.com.

Houston students develop new device to prepare astronauts for outer space

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Rice University students from the George R. Brown School of Engineering and Computing designed a space exercise harness that is comfortable, responsive, and adaptable and has the potential to assist with complex and demanding spacewalks.

A group of students—Emily Yao, Nikhil Ashri, Jose Noriega, Ben Bridges and graduate student Jack Kalicak—mentored by assistant professor of mechanical engineering Vanessa Sanchez, modernized harnesses that astronauts use to perform rigorous exercises. The harnesses are particularly important in preparing astronauts for a reduced-gravity space environment, where human muscles and bones atrophy faster than they do on Earth. However, traditional versions of the harnesses had many limitations that included chafing and bruising.

The new harnesses include sensors for astronauts to customize their workouts by using real-time data and feedback. An additional two sensors measure astronauts’ comfort and exercise performance based on temperature and humidity changes during exercise and load distribution at common pressure points.

“Our student-led team addressed this issue by adding pneumatic padding that offers a customized fit, distributes pressure over a large surface area to reduce discomfort or injuries and also seamlessly adapts to load shifts — all of which together improved astronauts’ performance,” Sanchez said in a news release. “It was very fulfilling to watch these young engineers work together to find innovative and tangible solutions to real-world problems … This innovative adjustable exercise harness transforms how astronauts exercise in space and will significantly improve their health and safety during spaceflights.”

The project was developed in response to a challenge posted by the HumanWorks Lab and Life Science Labs at NASA and NASA Johnson Space Center for the 2025 Technology Collaboration Center’s (TCC) Wearables Workshop and University Challenge, where teams worked to solve problems for industry leaders.

Rice’s adaptive harness won the Best Challenge Response Award. It was funded by the National Science Foundation and Rice’s Office of Undergraduate Research and Inquiry.

“This challenge gave us the freedom to innovate and explore possibilities beyond the current harness technology,” Yao added in the release. “I’m especially proud of how our team worked together to build a working prototype that not only has real-world impact but also provides a foundation that NASA and space companies can build and iterate upon.”

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