Houston-based VineSleuth created a custom algorithm to match you with new wines based on wines you've had in the past. Courtesy of VineSleuth

Amy Gross wants to find you the perfect wine. In fact, she wants it so much, she built her company, VineSleuth, around the concept that technology and machine learning could find the best wine to match individual palates.

VineSleuth's custom algorithm is backed by research from sensory scientists at Cornell University, and relies on both data collection and machine learning to determine specific wines that will match an individual customer's tastes. Flavor profiles from thousands of wines are incorporated into her database, and none of those are based on the typical wine scores you'll see in magazines or reviews of wines.

"We have a team that tastes and analyzes wines and inputs their findings. Then, we have a team that codes all of that data," she says.

VineSleuth's technology can be easily overlaid on a restaurant, grocery store, or other vendor's existing web platform or app to provide a tailor-made experience for customers.

"Take a grocery store setting for example," says Gross. "A customer logs into the store using their loyalty card, and their past wine purchases come up. Our technology can analyze those and point to different selections in the store's inventory they'll enjoy."

Think of it as using big data and machine learning to deliver big returns for wine drinkers.

Gross has been deliberate and incremental in how she's grown her company, and she just got a major boost: back in September, she won the 2018 Start Here Now competition, a combination business pitch event and incubator aimed at encouraging women entrepreneurs. She took home the $10,000 Silicon Valley Bank Grand Prize, as well as an app-design concept prize to help her improve the app she created, and a media and PR consultation.

"It was such an affirmation," she says. "To have them validate our work and my future plans."

Planting the seed
It was a slow and steady growth for Gross, who started work on VineSleuth in 2011. But her wine journey started before that.

"My now-husband asked me out on a date, and I'd just graduated college," she says. "I wanted to be sophisticated, so I ordered the house chardonnay. Well, after four or five dates, I started paying attention to what I was drinking, and I developed my palate."

She and her husband and friends of theirs enjoyed exploring wine together, and on a trip to Napa in 2009, Gross noticed something. All six of them were drinking the same wines — mostly Cabernet Sauvignons from Oakville — but they had remarkably different reactions to them.

"I thought, wouldn't it be great if there were an app that told me what I wanted, not what was 'good?'" Gross says.

While she wasn't sure then how to create such an app, she knew she needed to build up her wine knowledge. She started learning about wine in earnest and launched a wine blog. That gave her access to wine vendors and wine makers.

And then, several things happened in steps. Her brother-in-law wrote a basic algorithm that would collect taste profiles and other details from wines, but Gross needed something more. A neighbor who was an applied mathematician took that original algorithm and built on it.

"When I felt brave enough to show it, I shared it with the owners of some wineries I'd developed a business relationship with in the Finger Lakes," says Gross. "They loved the idea, and it turns out one of the winemaker's wife was a sensory scientist at Cornell. At every key place along building this business, it's been about relationships."

Still fermenting
Gross did create an app, but she admits it's not quite where she wants it to be, so she'll likely tweak it over the coming year. In the meantime, she's focused on the B2B future of VineSleuth. While she says the technology her team has created is currently being used for wine, she knows it's possible to take it and expand its capabilities to beer, chocolate, spirits and other consumables.

Building the business has been both an adventure and a learning curve for Gross, whose background is in journalism and PR. But even though she doesn't come from the technology or STEM side, she says her journalism work made her a great researcher – which is exactly what she needed to build VineSleuth. She's also a driven and detail-oriented project manager.

"My team once called me the den mother, keeping everyone on track," she laughed. "And in a way, I am. But I'm also watching the future of AI happening in front me and I really love hanging out with the brilliant people on my team. This is a blast."


Amy Gross is also working on a consumer-facing app, called Wine4Me, that helps users keep track of their favorite wines and gives recommendations for new wines. Courtesy of VineSleuth

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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.”

12 winners named at CERAWeek clean tech pitch competition in Houston

top teams

Twelve teams from around the country, including several from Houston, took home top honors at this year's Energy Venture Day and Pitch Competition at CERAWeek.

The fast-paced event, held March 25, put on by Rice Alliance, Houston Energy Transition Initiative and TEX-E, invited 36 industry startups and five Texas-based student teams focused on driving efficiency and advancements in the energy transition to present 3.5-minute pitches before investors and industry partners during CERAWeek's Agora program.

The competition is a qualifying event for the Startup World Cup, where teams compete for a $1 million investment prize.

PolyJoule won in the Track C competition and was named the overall winner of the pitch event. The Boston-based company will go on to compete in the Startup World Cup held this fall in San Francisco.

PolyJoule was spun out of MIT and is developing conductive polymer battery technology for energy storage.

Rice University's Resonant Thermal Systems won the second-place prize and $15,000 in the student track, known as TEX-E. The team's STREED solution converts high-salinity water into fresh water while recovering valuable minerals.

Teams from the University of Texas won first and second place in the TEX-E competition, bringing home $25,000 and $10,000, respectively. The student winners were:

Companies that pitched in the three industry tracts competed for non-monetary awards. Here are the companies named "most-promising" by the judges:

Track A | Industrial Efficiency & Decarbonization

Track B | Advanced Manufacturing, Materials, & Other Advanced Technologies

  • First: Licube, based in Houston
  • Second: ZettaJoule, based in Houston and Maryland
  • Third: Oleo

Track C | Innovations for Traditional Energy, Electricity, & the Grid

The teams at this year's Energy Venture Day have collectively raised $707 million in funding, according to Rice. They represent six countries and 12 states. See the full list of companies and investor groups that participated here.

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