The new Rice Nexus is partnering with Google Public Sector and Non Sibi Ventures to support high-potential AI-focused startups. Image via Rice University.

Google Public Sector is teaming up with Rice University to drive early-stage artificial intelligence innovation and commercialization via the new Rice AI Venture Accelerator, or RAVA.

RAVA will use Google Cloud technology and work with venture capital firm Non Sibi Ventures to connect high-potential AI-focused startups with public and private sector organizations. The incubator will be led by Rice Nexus, which launched earlier this year in the Ion District as an AI-focused "innovation factory.”

“Google Public Sector is proud to partner with a leading institution like Rice University to launch the Rice AI Venture Accelerator,” Reymund Dumlao, director of state and local government and education at Google Public Sector, said in a news release. “By providing access to Google Cloud’s cutting-edge AI, secure cloud infrastructure and expertise, we’re enabling the next generation of AI pioneers to develop solutions that address critical challenges across industries and within the public sector. This unique partnership between education and industry will give participants access to cutting-edge research, leading technologists, specialized resources and a collaborative academic ecosystem, fostering an environment for rapid innovation and growth.”

Participants will have access to Google Public Sector’s AI leadership as well as experts from Rice’s Ken Kennedy Institute, which focuses on AI and computing research. It will be led by Sanjoy Paul, Rice Nexus’ inaugural executive director. Paul previously worked at Accenture LLC as a managing director of technology and is a lecturer in Rice's Department of Computer Science.

Rice Nexus will serve as the physical hub for RAVA, but the program will support AI startups from across the U.S., as part of Rice’s Momentous strategic plan, according to the university.

“This hub enables AI startups to go beyond building minimum viable products that meet industry privacy standards by utilizing the latest AI technologies from Google Cloud,” Paul said in the news release. “Our goal is to maximize the return on investment for our corporate partners, driving meaningful innovation that will have lasting impact on their industries.”

The 10,000-square-foot Rice Nexus space currently serves as home base for several startups with ties to Rice, including Solidec, BeOne Sports and others. Read more about the new incubation space here.

OpenSafe.AI, a new platform that utilizes AI, data, and hazard and resilience models to support storm response decision makers, has secured an NSF grant. Photo by Eric Turnquist

Houston-area researchers score $1.5M grant to develop storm response tech platform

fresh funding

Researchers from Rice University have secured a $1.5 million grant from the National Science Foundation to continue their work on improving safety and resiliency of coastal communities plagued by flooding and hazardous weather.

The Rice team of engineers and collaborators includes Jamie Padgett, Ben Hu, and Avantika Gori along with David Retchless at Texas A&M University at Galveston. The researchers are working in collaboration with the Severe Storm Prediction, Education and Evacuation from Disasters (SSPEED) Center and the Ken Kennedy Institute at Rice and A&M-Galveston’s Institute for a Disaster Resilient Texas.

Together, the team is developing and hopes to deploy “Open-Source Situational Awareness Framework for Equitable Multi-Hazard Impact Sensing using Responsible AI,” or OpenSafe.AI, a new platform that utilizes AI, data, and hazard and resilience models "to provide timely, reliable and equitable insights to emergency response organizations and communities before, during and after tropical cyclones and coastal storm events," reads a news release from Rice.

“Our goal with this project is to enable communities to better prepare for and navigate severe weather by providing better estimates of what is actually happening or might happen within the next hours or days,” Padgett, Rice’s Stanley C. Moore Professor in Engineering and chair of the Department of Civil and Environmental Engineering, says in the release. “OpenSafe.AI will take into account multiple hazards such as high-speed winds, storm surge and compound flooding and forecast their potential impact on the built environment such as transportation infrastructure performance or hazardous material spills triggered by severe storms.”

OpenSafe.AI platform will be developed to support decision makers before, during, and after a storm.

“By combining cutting-edge AI with a deep understanding of the needs of emergency responders, we aim to provide accurate, real-time information that will enable better decision-making in the face of disasters,” adds Hu, associate professor of computer science at Rice.

In the long term, OpenSafe.AI hopes to explore how the system can be applied to and scaled in other regions in need of equitable resilience to climate-driven hazards.

“Our goal is not only to develop a powerful tool for emergency response agencies along the coast but to ensure that all communities ⎯ especially the ones most vulnerable to storm-induced damage ⎯ can rely on this technology to better respond to and recover from the devastating effects of coastal storms,” adds Gori, assistant professor of civil and environmental engineering at Rice.

------

This article originally ran on EnergyCapital.

Angela Wilkins joins the Houston Innovators Podcast to discuss the intersection of data and health care. Photo courtesy

Houston data scientist joins medical device startup amid AI evolution in the sector

HOUSTON INNOVATORS PODCAST EPISODE 241

When most people hear about Houston startup Starling Medical, they might think about how much potential the medical device company has in the field of urinalysis diagnostics. But that's not quite where Angela Wilkins's head went.

Wilkins explains on the Houston Innovators Podcast that when she met the company's co-founders, Hannah McKenney and Drew Hendricks, she recognized them as very promising startup leaders taking action on a real health care problem. Starling's device can collect urine and run diagnostics right from a patient's toilet.

"It was one of those things where I just thought, 'They're going to get a bunch of data soon,'" Wilkins says. "The opportunity is just there, and I was really excited to come on and build their AI platform and the way they are going to look at data."

For about a year, Wilkins supported the startup as an adviser. Now, she's working more hands on as chief data officer as the company grows.



Wilkins, who serves as a mentor and adviser for several startups, has a 20-year career in Houston across all sides of the innovation equation, working first at Baylor College of Medicine before co-founding Mercury Data Science — now OmniScience. Most recently she served as executive director of the Ken Kennedy Institute at Rice University.

This variety in her resume makes her super connective — a benefit to all the startups she works with, she explains. The decision to transition to a startup team means she gets to work hands on in building a technology — while bringing in her experience from other institutions.

"I think I've really learned how to partner with those institutions," she says on the show. "I've really learned how to make those bridges, and that's a big challenge that startups face."

"When we talk about the Houston innovation ecosystem, it's something we should be doing better at because we have so many startups and so many places that would like to use better technology to solve problems," she continues.

Wilkins has data and artificial intelligence on the mind in everything she does, and she even serves on a committee at the state level to learn and provide feedback on how Texas should be regulating AI.

"At the end of the day, the mission is to put together a report and strategy on how we think Texas should think about AI," she explains. "It's beyond just using an algorithm, they need infrastructure."

Colorado is the first state to pass legislation surrounding AI, and Wilkins says all eyes are on how execution of that new law will go.

"We should have technology that can be double checked to make sure we're applying it in a way that's fair across all demographics. It's obvious that we should do that — it's just very hard," she says.

"Better and personalized healthcare through AI is still a hugely challenging problem that will take an army of scientists and engineers." Photo via UH.edu

Houston expert explains health care's inequity problem

guest column

We are currently in the midst of what some have called the "wild west" of AI. Though healthcare is one of the most heavily regulated sectors, the regulation of AI in this space is still in its infancy. The rules are being written as we speak. We are playing catch-up by learning how to reap the benefits these technologies offer while minimizing any potential harms once they've already been deployed.

AI systems in healthcare exacerbate existing inequities. We've seen this play out into real-world consequences from racial bias in the American justice system and credit scoring, to gender bias in resume screening applications. Programs that are designed to bring machine "objectivity" and ease to our systems end up reproducing and upholding biases with no means of accountability.

The algorithm itself is seldom the problem. It is often the data used to program the technology that merits concern. But this is about far more than ethics and fairness. Building AI tools that take account of the whole picture of healthcare is fundamental to creating solutions that work.

The Algorithm is Only as Good as the Data

By nature of our own human systems, datasets are almost always partial and rarely ever fair. As Linda Nordling comments in a Nature article, A fairer way forward for AI in healthcare, "this revolution hinges on the data that are available for these tools to learn from, and those data mirror the unequal health system we see today."

Take, for example, the finding that Black people in US emergency rooms are 40 percent less likely to receive pain medication than are white people, and Hispanic patients are 25 percent less likely. Now, imagine the dataset these findings are based on is used to train an algorithm for an AI tool that would be used to help nurses determine if they should administer pain relief medication. These racial disparities would be reproduced and the implicit biases that uphold them would remain unquestioned, and worse, become automated.

We can attempt to improve these biases by removing the data we believe causes the bias in training, but there will still be hidden patterns that correlate with demographic data. An algorithm cannot take in the nuances of the full picture, it can only learn from patterns in the data it is presented with.

Bias Creep

Data bias creeps into healthcare in unexpected ways. Consider the fact that animal models used in laboratories across the world to discover and test new pain medications are almost entirely male. As a result, many medications, including pain medication, are not optimized for females. So, it makes sense that even common pain medications like ibuprofen and naproxen have been proven to be more effective in men than women and that women tend to experience worse side effects from pain medication than men do.

In reality, male rodents aren't perfect test subjects either. Studies have also shown that both female and male rodents' responses to pain levels differ depending on the sex of the human researcher present. The stress response elicited in rodents to the olfactory presence of a sole male researcher is enough to alter their responses to pain.

While this example may seem to be a departure from AI, it is in fact deeply connected — the current treatment choices we have access to were implicitly biased before the treatments ever made it to clinical trials. The challenge of AI equity is not a purely technical problem, but a very human one that begins with the choices that we make as scientists.

Unequal Data Leads to Unequal Benefits

In order for all of society to enjoy the many benefits that AI systems can bring to healthcare, all of society must be equally represented in the data used to train these systems. While this may sound straightforward, it's a tall order to fill.

Data from some populations don't always make it into training datasets. This can happen for a number of reasons. Some data may not be as accessible or it may not even be collected at all due to existing systemic challenges, such as a lack of access to digital technology or simply being deemed unimportant. Predictive models are created by categorizing data in a meaningful way. But because there's generally less of it, "minority" data tends to be an outlier in datasets and is often wiped out as spurious in order to create a cleaner model.

Data source matters because this detail unquestionably affects the outcome and interpretation of healthcare models. In sub-Saharan Africa, young women are diagnosed with breast cancer at a significantly higher rate. This reveals the need for AI tools and healthcare models tailored to this demographic group, as opposed to AI tools used to detect breast cancer that are only trained on mammograms from the Global North. Likewise, a growing body of work suggests that algorithms used to detect skin cancer tend to be less accurate for Black patients because they are trained mostly on images of light-skinned patients. The list goes on.

We are creating tools and systems that have the potential to revolutionize the healthcare sector, but the benefits of these developments will only reach those represented in the data.

So, what can be done?

Part of the challenge in getting bias out of data is that high volume, diverse and representative datasets are not easy to access. Training datasets that are publicly available tend to be extremely narrow, low-volume, and homogenous—they only capture a partial picture of society. At the same time, a wealth of diverse health data is captured every day in many healthcare settings, but data privacy laws make accessing these more voluminous and diverse datasets difficult.

Data protection is of course vital. Big Tech and governments do not have the best track record when it comes to the responsible use of data. However, if transparency, education, and consent for the sharing of medical data was more purposefully regulated, far more diverse and high-volume data sets could contribute to fairer representation across AI systems and result in better, more accurate results for AI-driven healthcare tools.

But data sharing and access is not a complete fix to healthcare's AI problem. Better and personalized healthcare through AI is still a hugely challenging problem that will take an army of scientists and engineers. At the end of the day, we want to teach our algorithms to make good choices but we are still figuring out what good choices should look like for ourselves.

AI presents the opportunity to bring greater personalization to healthcare, but it equally presents the risk of entrenching existing inequalities. We have the opportunity in front of us to take a considered approach to data collection, regulation, and use that will provide a fuller and fairer picture and enable the next steps for AI in healthcare.

------

Angela Wilkins is the executive director of the Ken Kennedy Institute at Rice University.

Ad Placement 300x100
Ad Placement 300x600

CultureMap Emails are Awesome

Trailblazing Houston entrepreneur brings big ideas to new Yahoo Finance show

tune in

Elizabeth Gore, co-founder and president of Houston's Hello Alice, debuted the first episode of her new video podcast series with Yahoo Finance on Thursday, April 24.

The weekly series, known as "The Big Idea with Elizabeth Gore," will focus on providing information and resources to small business owners and sharing stories of entrepreneurship, according to a news release from Yahoo Finance.

“Entrepreneurs and small business owners drive our country’s economy forward. With a record number of small businesses launching in our communities, my goal is to help every citizen live the American Dream. On the Big Idea, we will break down barriers for entrepreneurs and lift up opportunities for every person wanting to be their own boss,” Gore said in the release.

“By hosting the 'Big Idea' on Yahoo Finance, I’m looking forward to elevating business owners’ stories and providing actionable insights to small business owners at a scale like never before. I am blown away to be joining the number one finance news source that is already trusted by so many.”

Gore was joined by Hello Alice co-founder and CEO Carolyn Rodz in the premiere episode, titled "Got a big idea for a small business? Here's your first step," to discuss the steps they took when launching the business.

Gore and Rodz founded Hello Alice in 2017. The fintech platform supports over 1.5 million small businesses across the nation. It has helped owners access affordable capital and credit and distributed over $57 million in grants to businesses across various industries. The company raised a series C round backed by Mastercard last year for an undisclosed amount and reported that the funding brought the company's valuation up to $130 million at the time.

According to Yahoo Finance, Gore's experience and expertise build on its "mission to be the trusted guide of financial information to all investors, and democratize access to quality content."

“Over the past year, we invested in expanding our programming lineup with the launch of new shows and podcasts, and welcomed new financial creators and influencers into our newsroom,” Anthony Galloway, head of content at Yahoo Finance, added the release. “By diversifying our programming and talent roster, Yahoo Finance is introducing unique points-of-view that make financial topics more engaging, actionable, and personalized. Small business owners are a vital part of our audience, so we’re excited to welcome Elizabeth Gore from Hello Alice, whose insights and expertise will help us serve and connect with this important cohort in meaningful ways.”

The show is available on Spotify, Apple Podcasts, iHeart, Pandora, and Amazon Music for listening. Streamers can view it on yahoofinance.com, Amazon Prime Video, Samsung TV, Fire TV, Vizio, Haystack, DirectTV and other streaming platforms. Watch the premiere here:

7 top Houston researchers join Rice innovation cohort for 2025

top of class

The Liu Idea Lab for Innovation and Entrepreneurship (Lilie) has announced its 2025 Rice Innovation Fellows cohort, which includes students developing cutting-edge thermal management solutions for artificial intelligence, biomaterial cell therapy for treating lymphedema, and other innovative projects.

The program aims to support Rice Ph.D. students and postdocs in turning their research into real-world solutions and startups.

“Our fourth cohort of fellows spans multiple industries addressing the most pressing challenges of humanity,” Kyle Judah, Lilie’s executive director, said in a news release. “We see seven Innovation Fellows and their professors with the passion and a path to change the world.”

The seven 2025 Innovation Fellows are:

Chen-Yang Lin, Materials Science and Nanoengineering, Ph.D. 2025

Professor Jun Lou’s Laboratory

Lin is a co-founder of HEXAspec, a startup that focuses on creating thermal management solutions for artificial intelligence chips and high-performance semiconductor devices. The startup won the prestigious H. Albert Napier Rice Launch Challenge (NRLC) competition last year and also won this year's Energy Venture Day and Pitch Competition during CERAWeek in the TEX-E student track.

Sarah Jimenez, Bioengineering, Ph.D. 2027

Professor Camila Hochman-Mendez Laboratory

Jimenez is working to make transplantable hearts out of decellularized animal heart scaffolds in the lab and the creating an automated cell delivery system to “re-cellularize” hearts with patient-derived stem cells.

Alexander Lathem, Applied Physics and Chemistry, Ph.D. 2026

Professor James M. Tour Laboratory

Lathem’s research is focused on bringing laser-induced graphene technology from “academia into industry,” according to the university.

Dilrasbonu Vohidova is a Bioengineering, Ph.D. 2027

Professor Omid Veiseh Laboratory

Vohidova’s research focuses on engineering therapeutic cells to secrete immunomodulators, aiming to prevent the onset of autoimmunity in Type 1 diabetes.

Alexandria Carter, Bioengineering, Ph.D. 2027

Professor Michael King Laboratory

Carter is developing a device that offers personalized patient disease diagnostics by using 3D culturing and superhydrophobicity.

Alvaro Moreno Lozano, Bioengineering, Ph.D. 2027

Professor Omid Veiseh Lab

Lozano is using novel biomaterials and cell engineering to develop new technologies for patients with Type 1 Diabetes. The work aims to fabricate a bioartificial pancreas that can control blood glucose levels.

Lucas Eddy, Applied Physics and Chemistry, Ph.D. 2025

Professor James M. Tour Laboratory

Eddy specializes in building and using electrothermal reaction systems for nanomaterial synthesis, waste material upcycling and per- and polyfluoroalkyl substances (PFAS) destruction.

This year, the Liu Lab also introduced its first cohort of five commercialization fellows. See the full list here.

The Rice Innovation Fellows program assists doctoral students and postdoctoral researchers with training and support to turn their ideas into ventures. Alumni have raised over $20 million in funding and grants, according to Lilie. Last year's group included 10 doctoral and postdoctoral students working in fields such as computer science, mechanical engineering and materials science.

“The Innovation Fellows program helps scientist-led startups accelerate growth by leveraging campus resources — from One Small Step grants to the Summer Venture Studio accelerator — before launching into hubs like Greentown Labs, Helix Park and Rice’s new Nexus at The Ion,” Yael Hochberg, head of the Rice Entrepreneurship Initiative and the Ralph S. O’Connor Professor in Entrepreneurship, said in the release. “These ventures are shaping Houston’s next generation of pillar companies, keeping our city, state and country at the forefront of innovation in mission critical industries.”

Houston startup Collide secures $5M to grow energy-focused AI platform

Fresh Funds

Houston-based Collide, a provider of generative artificial intelligence for the energy sector, has raised $5 million in seed funding led by Houston’s Mercury Fund.

Other investors in the seed round include Bryan Sheffield, founder of Austin-based Parsley Energy, which was acquired by Dallas-based Pioneer Natural Resources in 2021; Billy Quinn, founder and managing partner of Dallas-based private equity firm Pearl Energy Investments; and David Albin, co-founder and former managing partner of Dallas-based private equity firm NGP Capital Partners.

“(Collide) co-founders Collin McLelland and Chuck Yates bring a unique understanding of the oil and gas industry,” Blair Garrou, managing partner at Mercury, said in a news release. “Their backgrounds, combined with Collide’s proprietary knowledge base, create a significant and strategic moat for the platform.”

Collide, founded in 2022, says the funding will enable the company to accelerate the development of its GenAI platform. GenAI creates digital content such as images, videos, text, and music.

Originally launched by Houston media organization Digital Wildcatters as “a professional network and digital community for technical discussions and knowledge sharing,” the company says it will now shift its focus to rolling out its enterprise-level, AI-enabled solution.

Collide explains that its platform gathers and synthesizes data from trusted sources to deliver industry insights for oil and gas professionals. Unlike platforms such as OpenAI, Perplexity, and Microsoft Copilot, Collide’s platform “uniquely accesses a comprehensive, industry-specific knowledge base, including technical papers, internal processes, and a curated Q&A database tailored to energy professionals,” the company said.

Collide says its approximately 6,000 platform users span 122 countries.

---

This story originally appeared on our sister site, EnergyCapitalHTX.com.