Our team: Delivering your customers the best glasses for face shape
The Veero leadership team brings together design-centered, entrepreneurial problem solvers who are committed to the full ecosystem in which we operate. The satisfaction of our customers—and your customers—is paramount, as are the needs of our employees, our shareholders, and our communities.
Leadership team
Stan brings to Veero a background in product design and a deep understanding of modern AI and robotic perception technologies. His design-centric thinking, technological acumen, and entrepreneurial mindset combine to provide a unique viewpoint on how to benefit the end customer, sales channels, and the eyewear industry as a whole.
A longtime consumer in the eyewear space himself, Stan struggled with the process and subpar results associated with shopping for glasses online. His collaboration with co-founder Michael Kim led him to adapt their existing AI stack to significantly improve the customer experience in the eyewear shopping process.
Stan is highly skilled in technology application. He is continuously expanding his toolset based on a decade of leading R&D work in fields such as structure from motion, deep learning, robot perception and vision, and human-machine interfaces, among others.
As Chief Engineering Officer, Michael leverages a decade of experience applying AI technologies across a variety of environments, from austere computers onboard drones and vehicles to massive onsite and cloud-based GPU clusters. He is passionate about spearheading Veero’s rewarding and engaging engineering environment, with a particular emphasis on aggressive yet achievable results.
Michael has teamed with Stan over the past decade to explore the practical application of identified technologies to the many complexities of modern computing environments. He thrives in managing the challenges of machine learning and computer vision across heterogenous and distributed computing environments; from onboard embedded computers to mobile phones to adaptive, cloud-based CPU and GPU resources.
Michael’s career arc is based on achievements in combining highly skilled software engineering, including industry best practices in DevOps and CICD, with R&D topics focused on edge deployable deep learning architectures, structure from motion, sensor processing, and object detection and tracking.