Lawrence-based Ainstein predicts radar tech will push self-driving automotive advances

By: Elyssa Bezner, Reporter


November 15, 2018

From Kansas, Ainstein’s radar technology can have a profound impact on industries across the globe, said Zongbo Wang.

“We wanted to design radar that can be very affordable and play different roles in the industry,” said Wang, CEO of the radar tech firm. “Over the past three years, we’ve experienced a time of tremendous growth.”

That upward trajectory is, in part, because of the increase in interest surrounding autonomous vehicles, including cars and drones, he said.

Click here to read how Ainstein’s tech literally took flight earlier in 2018 with the founder of Jetpack Aviation at Red Bull’s Air Race World Championship.

The Lawrence-based firm currently serves 200 clients worldwide that range from Fortune 500 companies to small businesses, said Wang, noting the frequency of work keeps Ainstein’s team of 55 — across the U.S. and China — busy.

“I expect the size of our team is going to be doubled in the coming 12 to 18 months and our business is going to be growing quickly based on the contracts we already have and the clients we already have,” he said. “I [predict] that we’re going to be more recognized in branding and name in the automotive industry than any other industry.”

“We’re very glad to be a company based in Kansas, and I see that as our advantage in growing our company,” he added.

Wang moved to Lawrence from China in 2013 to work as a research professor for the University of Kansas, he said, noting that living previously in locales across the globe — the Netherlands and Singapore for a time — made the transition to stateside life easier.

Research in the radar field spurred the start of Aerotenna, the tech firm powering Ainstein, which in 2016, snagged first prize at the Unmanned Traffic Management Preliminary Drone Sense & Avoid technology competition, the $12,000 award providing pathways for global distribution.

“[I had a] mission and a vision that radar could not only be used for statistical applications or homeland security applications, but also for commercial applications,” said Wang.

Wang’s early business models were technology driven, he said, thinking that a good business was just about a good product.

“I made a lot of mistakes in the beginning, and even still now, but the only way that I see is recognizing those mistakes — it means you can improve — and continue to mature as a founder, and mature your team and your product,” he added.