Nexar Adds Former Uber Executive Jen Vescio to Board as Physical AI Expands in Mobility

Apr 24, 2026
Nexar has appointed Jen Vescio, former Uber Chief Business Development Officer, to its Board of Directors as it scales its physical AI platform across commercial mobility operations.

Nexar announced in a press release the appointment of Jen Vescio to its Board of Directors as the company expands physical AI into commercial mobility operations. The move comes as Nexar focuses on distributing predictive safety and real world intelligence across rideshare, delivery, and fleet systems.

Vescio brings more than twenty years of experience in mobility and technology. She most recently served as Chief Business Development Officer at Uber, where she led global partnerships and commercial expansion across mobility, delivery, and autonomous business lines. Her earlier roles include senior positions at Verizon, Disney, CBS, Yahoo, and eBay.

Nexar said Vescio’s appointment supports its goal of scaling physical AI in production environments used by rideshare networks, commercial fleets, insurers, and public agencies. The company recently released BADAS 2.0, its collision anticipation model with 99.4 percent average precision, used by enterprise clients including Waymo, Lyft, IBM, and NVIDIA.

Vescio joins a board that also includes AI researcher Yann LeCun and former Miami Mayor Francis Suarez, aligning expertise from research, government, and commercial operations to guide Nexar’s physical AI deployment.

We hope you enjoyed this article

Consider subscribing to one of our newsletters like Enterprise AI Brief or Daily AI Brief.

Also, consider following us on social media:

Free newsletter

Enterprise AI Brief

Weekly report on AI business applications, enterprise software releases, automation tools, and industry implementations.

Whitepaper

Tensordyne Napier: What If One Rack Could Do the Work of Nine?

Tensordyne

This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.

Read more
Free, six days a week

Daily AI Brief: the AI news that matters, in your inbox.