3 Houston innovators to know this week

who's who

This week's roundup of Houston innovators includes Moji Karimi of Cemvita Factory, Shanna Jin of Rice University, and Trent Crow of Real Simple Energy. Courtesy photos

Editor's note: In the week's roundup of Houston innovators to know, I'm introducing you to three local innovators across industries — data science, consumer tech, and medical device innovation — recently making headlines in Houston innovation.

Moji Karimi, co-founder and CEO of Cemvita Factory

Moji Karimi joins the Houston Innovators Podcast to discuss how his technology is offering energy execs an innovative way to meat their climate change pledge goals. Photo courtesy of Cemvita

A lot of startups are working on technology that makes existing practices more efficient, cheaper, or faster — or all of the above. But Cemvita Factory, founded by siblings Moji and Tara Karimi, is doing something that's never been done before: biomimicking photosynthesis to convert carbon emissions into useful chemicals.

"There weren't biotech companies working with oil and gas companies for this use case that we have now," Moji Karimi says on this week's episode of the Houston Innovators Podcast. "We're defining this new category for application of synthetic biology in heavy industries for decarbonization."

With this uncharted territory comes unique challenges and opportunities. Click here to read more and stream the episode.

Shanna Jin, communications and marketing specialist of the Data to Knowledge Lab at Rice University

Startups and small businesses are accumulating data daily — here's how to use that to your advantage, according to this Houston expert. Photo via rice.edu

Ironically, the power of data management is almost incalculable. With the right practices and processes in place, businesses can make better decisions and grow more strategically. But, it's not something a lot of startups or small businesses look at regularly. That's where the Rice University Data To Knowledge group comes into play.

"Being able to interpret data and making data-driven decisions becomes the key to the success of a business," writes Shanna Jin in a guest column for InnovationMap. "It is not just a privilege for big companies anymore. Small businesses need it more than ever to make sustainable growth in the digital era." Click here to read more.

Trent Crow, founder and president of Real Simple Energy

Trent Crow, founder and president, and the Real Simple Energy team have moved over to Arcardia with the acquisition. Photo courtesy of Real Simple Energy

Earlier this month, a Houston startup exited to a larger tech company. Trent Crow, co-founder and CEO of Real Simply Energy, says all eight of the company's employees have moved over to Arcadia and more workers will be hired soon. The company has maintained a mix of office and remote workers. Arcadia will look for Houston office space later this year, Crow says.

"Expansion plans include doing more of what we're doing now and offering more features for customers," says Crow, who now is Arcadia's general manager of energy services in Texas. Click here to read more.

Startups and small businesses are accumulating data daily — here's how to use that to your advantage. Photo via Getty Images

Houston expert: How to use the power of data and analytics to inform small businesses

Guest column

Starting a business in a digital era brings entrepreneurs unprecedented advantages with technology and tools designed to optimize a business' operation. Whether it is a B2C or B2B, business owners can gather almost any data and metrics to improve their performance.

Being able to interpret data and making data-driven decisions becomes the key to the success of a business. It is not just a privilege for big companies anymore. Small businesses need it more than ever to make sustainable growth in the digital era.

The challenge? There are countless analytic tools and resources available that can generate data, but you need people who can extract insights from the massive amount of data.

Hire a data science team vs. outsourcing

Many companies go to campus recruitment and scout bright data science talent who also identify with their business value. Hiring people with data science and analytic skills is optimal, but for startups that are not ready to hire an in-house team or have a short-term question, outsourcing is a better option.

Data science consulting

Many online resources can help you extract data, but you are probably wondering: where do I begin? Which tool should I use? Which exact metric should I track?

The Rice University's Data Science Consulting Clinic provides free, open to the public assistance to help clients with all of those questions. It can be for various business sectors, such as research and product development, cost predictions, analytic tools, acquisition decisions, and talent management.

Here are some of the data science aspects we specialize in:

Research & Development - Obtain data to inform a decision on what products to develop.
Data analysis of who your customers are, what they are interested in, and what product to develop is crucial for B2C and B2B. A recent example of how Rice's Data Science Consulting Clinic is making a difference is a client needed assistance with market research to help inform a startup on what kind of product they should create next. The client was able to use the data resources suggested by the student and faculty consultants to gauge consumer sentiment and examples of successful products. With the data collected, the client was able to identify the features that drive customers to purchase similar products.

Cost Predictions - A case study for an energy company
Businesses need to make crucial decisions to achieve business intelligence. CEOs and managers need to base their decisions on predictions and analysis. Another client from the Data Science Consulting Clinic was interested in predicting cost and analysis of the factors contributing to the most expense for the coming year. The client's main problem was to transform the data into a statistical model that could predict the cost. With the prediction model suggested by the student consultants, the client was able to reduce the cost by controlling factors that were likely to cause higher costs.

Acquisition Decision Making for Business Professionals
Clients from the Rice MBA program were interested in investigating the causes and effects of private equity (PE) acquisition. Specifically, the clients wanted to analyze the difference in practice habits before and after acquisitions. As a result of the consultation, the clients were able to determine what factors influenced the PE's decision to acquire new equity.

Longer term projects

It would be helpful to have a dedicated data science team who can work over a semester or year long to find the solution.

Higher education has placed a prominent focus on data science programs, especially capstone projects that provide students with real-world experience. As a business owner, you might not even think about working with an esteemed university to help you with data challenges.

The Center for Transforming Data to Knowledge, informally known as the D2K Lab at Rice University, is founded based on the mission to seek real-world data challenges for passionate data science students. Student teams have worked on over 50 sponsored data science projects with partners from a wide variety of businesses, organizations, and community partners.

Advance data science and security

The perk of working with Rice University is that it provides the most advanced data science research tools and an interdisciplinary pool of student and faculty talent who are passionate about data science. Working with Rice University also guarantees a strong data security system and a comprehensive confidentiality agreement.

A cloud-based financial company sponsored a series of capstone projects on applying deep learning to reduce documentation errors and increase efficiency for businesses.
A fintech company sponsored multiple capstone projects on building statistical models to predict costs.
In the tech-med industry, the D2K Lab has partnered with the Medical Informational Corps, and researchers from Texas Children's Hospital and Baylor College of Medicine to build algorithms to predict cardiac events.

The future of data-driven decision making

The digital era has become the norm for all businesses (large or small), and there's no way to avoid the power of transforming data into actionable insights. So start gathering data even before you build out a business and incorporate the culture of data-driven decision making into every sector of your business.

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Shanna Jin is the communications and marketing specialist of the Data to Knowledge Lab at Rice University.

The Rice D2K Lab wants to help startups and small businesses solve business concerns with data science. Photo courtesy of Rice University

Rice University's data-focused lab presents unique opportunity for startups and small businesses

data to knowlege

A data-focused lab at Rice University is training the next generation of data scientists. However, the students at the Rice D2K Lab are doing more than just learning about the significance of data, machine learning, and artificial intelligence — they're working as data scientists now.

Businesses — large and small — can come into the lab and have Rice students and faculty work on data projects in both short-term and long-term capacity. One semester, a group of students worked with 311 call data for the city of Houston so that officials can figure out what parts of town were in the most need of support, says Jennifer Sanders, program administrator at the Rice D2K lab.

"They were able to show on a Houston map the areas where most of these 311 calls were coming from," Sanders tells InnovationMap. "That allowed the city to focus on those areas."

Lately, the lab has been focused on a several COVID-19 Houston Response Projects, which addressed issues ranging from homelessness in the time of a pandemic, ventilator distribution, and more. One team even made a recommendation to the city after a data project determined that adding five ambulances to southwest neighborhoods served by the Houston Fire Department Emergency Medical Services program would optimize response times.

The lab has two avenues to help businesses: a semester-long capstone course and a clinic for one-time sessions. This upcoming semester, the capstone course has 60 students signed up to work on 10 to 12 projects from corporate sponsors. These lab members — which support the program monetarily — are selected based on their fit within the program.

The D2K Consulting Clinic also offers free one-hour sessions on campus. At the clinic, students look at the data and assess the possibilities and advise on how to use that data for business gain or growth.

"The consulting clinic can be a starting point if a business is not sure what to do with their data," says Shanna Jin, communications and marketing specialist at the D2K Lab.

The clinic also presents a special opportunity for small businesses and startups, a niche Sanders says they haven't tapped into enough yet. She says most of the companies they've worked with are larger organizations, usually in the energy industry.

"We really want to broaden the scope to smaller startups, tech companies, and nonprofits," Sanders says. "We really don't have to limit ourselves. I would really love to expand our reach."

Membership dues for companies, which provides a more structured, long-term access to data consulting, range from $25,000 to $75,000 a year. However, Sanders says the lab is willing to work with startups on a cost that's more accessible.

Ultimately, the goal of the program is to connect the dots for businesses that have data and don't know how to use it.

"To realize the potential of big data, we need people — people who can transform data to knowledge," says the lab's founder, Genevera Allen, in a promotional video. "That's what we're doing with the Rice D2K Lab."

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

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

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

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

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

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

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

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

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

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

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

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

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

jobs report

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

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

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

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

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

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

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

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

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

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