In this webinar, participants will learn how Qeexo’s AutoML machine learning platform transforms the embedded Artificial Intelligence (e‑AI) development process without users having to code. Qeexo AutoML is a fully‑automated, end‑to‑end machine learning platform that builds lightweight machine learning solutions (tinyML) running locally on constrained environments such as a Cortex Arm M4 MCU. It augments the user experience and applicability of products like the RA Family of MCUs, adding intelligence with AI for many applications including Wearables, Industrial, Mobile, Smart Home/Appliance and other IoT markets.
Sr Bus Dev Manager
Jay's career in semiconductors spans several decades from sales at Texas Instruments to leading numerous product marketing teams and sales organizations at Intel, Atmel, and AMD with embedded processor technology. In his current role as Senior Business Development Manager in the Infrastructure and IoT Business Unit at Renesas, he works with key customers and ecosystem partners to offer complete solutions and enable new markets in consumer, industrial, and IoT. Jay has a BSEET degree from Kansas State University and an MBA, and lives in Silicon Valley.
Director Product Marketing
Tina is a Senior Product Marketing Manager at Qeexo. In that role, she helps businesses apply Qeexo AutoML to build innovative solutions using sensor data. She has a passion for building and launching cutting‑edge machine learning technologies and has launched many successful machine learning products during her five years at Qeexo. Tina is an advocate for running machine learning at the Edge, and actively contributes to the tinyML community. Tina holds an MBA from Columbia University and a BS degree in EECS from UC Berkeley. Before Qeexo, she was a software consultant and facilitated the end‑to‑end integration of business processes.