There are many LiDAR companies on the market, but AEye’s technology and its process of leveraging the existing automotive supply chain and Tier 1 suppliers to go-to-market got me very excited and interested in joining the company.
For me, artificial intelligence became perception, and that was the first problem that had to be solved. I decided at that point that I would start a company, and my mission would be to create a perception engine that was as good or better than human perception.
I'm a big believer in LiDAR as a market opportunity. There's a huge need for this technology, and LiDAR will be able to go everywhere, ultimately.
The bottom line is: anything that you design has to meet all the reliability and quality standards, and should be manufacturable at the lowest possible cost - especially in automotive. There’s no way you can win the market without reliability, quality, and cost efficiency.
The startup opportunity intrigued me, as I saw it as an opportunity to have a different kind of impact, to change the world through changing the kinds of products that are available. I was involved with some of the early investments in autonomy and LiDAR through DARPA, and like many others amongst my peers I was drawn to the autonomous vehicle commercial market as a result of the DARPA Grand Challenge.
We have built an active, intelligent, software-definable sensing platform – which we call iDAR – that can be used in a variety of different markets, and we're enabling our systems integrator and Tier 1 partners to take iDAR and customize it to the unique needs of each of these markets. These partnerships are a win-win for everybody: for the customer, the partner, and for us because everyone gets something better out of the equation.
It is in AEye’s DNA to innovate; I have been very lucky in my career to work on many cutting edge projects and products, but the technical innovation here at AEye, under Luis’ leadership, is second to none.
I head up our corporate development, partnerships and strategy, which means that I define our strategic initiatives, cultivate our sales channel partners, and drive fundraising processes. Our business model is predicated on enabling partners to be successful, and our technology design and automotive grade supply chain are a catalyst for the manufacturing, sales and integration partners for automotive, trucking, industrial, and more.
When I became an advisor with AEye, I was deeply impressed with the technology know-how in the team, and since then I have been further impressed with the business side of the company. At this point in my career, I'd rather be a contributor to a strong team rather than trying to do something like this solely on my own, so I took the opportunity to join the team at AEye about four years ago.
It is exciting to be involved and fully engaged in so many areas of the company and to have the unique opportunity to set up processes and establish rules to help make it succeed. AEye has a very inspiring environment with brilliant minds and experts in their fields.
I decided to join the automotive industry because I wanted to learn more about it. I had heard a lot of great things about what vehicles will be like in the future, and working hands-on in the industry is a great way to learn about the future of automotive!
LiDAR is the final sensor modality that is needed to make ADAS systems (and eventually full autonomy) work effectively in all conditions. LiDAR is more deterministic by nature, as it can detect and measure the distance to all objects. And with an agile LiDAR, such as AEye’s iDAR, this can be done incredibly fast with the added ability to classify objects and determine their velocity.
An NPI Engineer is responsible for bringing a product from the engineering sample phase to mass production. At the end of the day, my goal is to deliver a safe, reliable, and cost-efficient product at volume.
I was part of the microprocessor design team at Intel in the early 2000s. For the second Grand Challenge, Stanford University teamed up with Intel and VW to build the winning car: Stanley. I got involved in the project and, ultimately, in AVs, because I felt that the Grand Challenge was cool and interesting, and a clever and effective way to develop AV technology.
AEye has a perspective that we hope the industry will adopt more widely, which is to use biomimicry to focus energy on things that matter.
Autonomous vehicles will spark a radical shift in our society. Not only will it make safer and more efficient public transportation accessible to the masses, it will allow us to have the time to accomplish meaningful tasks which would otherwise be lost to a long commute. Engineers are the leaders in bringing about this societal change.
For the better part of 25 years, I have worked at the intersection of transportation and technology. Starting as a powertrain engineer at Ford Motor Company, and through executive tenures at Flexcar, Zipcar and Silvercar, I have seen the industry begin the most profound, tectonic shift in its 120 year history.
I was fortunate enough to work for Intel from the mid 70’s to the mid 90’s – and participated in the advent of desktop and mobile computing...we now have the advanced computing tools that allow companies to apply Artificial Intelligence (AI) within their decision making and take advantage of big data. These trends converge around the auto industry and its next inflection points — EVs and autonomy.
As a professional athlete, I have always been fascinated and amazed by human perception and the role it plays in athletic performance... I have been curious about how these capabilities might be replicated with technology and artificial intelligence.
I was formerly the Vice President and General Manager of the Transportation Solutions Division at Intel. In that role, I had a front row seat as autonomous driving went from research to a race to commercialism.