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VP of AI @ Qualcomm | Gen AI · Edge AI · Agentic AI | Board Member · Speaker · Author
The most consequential AI challenge of our time isn't building smarter models - it's making them run in the real world, on real devices, at real scale. That is exactly what I do. As Vice President of AI at Qualcomm Technologies, I have the privilege of leading the strategy and commercialization of Generative AI, Agentic AI, Voice AI, and Sensing AI: Spanning the full stack from silicon architecture to enterprise deployment. My work sits at the hardest part of the AI problem: Making frontier models run efficiently on constrained edge hardware at scale. That means deep engagement across the full stack from neural network quantization, hardware-aware model optimization, MLOps/LLOps pipelines, and cross-platform AI software ecosystems spanning mobile, automotive, XR, PC, IoT and upcoming form factors. Had the opportunity to lead teams responsible for bringing the world's first on device large language models to Snapdragon platforms, enabling real time multimodal AI experiences, and building the Qualcomm AI Stack -> A unified software portfolio now used by developers and ML engineers across the industry. I hold a PhD in Electrical Engineering (Vision System Modeling) and an MBA in Strategy, Marketing & Operations. I've authored multiple peer-reviewed journal papers and two technical books, and I'm a regular speaker at AI industry forums and major industry conferences. Beyond my day job, I serve as a board member and an Industry Advisor so as to bridge the gap between academic AI research and real-world commercial deployment. If you're building in the AI space - whether as an engineer, a founder, or a researcher -> I'm always open to conversations about Edge AI, Generative AI, and the future of intelligent computing. 📩 Let's connect.
Isenberg School of Management, UMass Amherst
Master of Business Administration (MBA), Strategy, Marketing and Operations Management
N/A – Present
Washington State University
Doctor of Philosophy (PhD), Electrical Engineering (Vision System Modeling)
N/A – Present
Forbes Technology Council
Board Member - Artificial Intelligence
February 1, 2025 – Present
Qualcomm
Vice President - GEN AI | Agentic AI | Voice AI | Sensing AI
September 1, 2020 – Present
San Francisco Bay Area · On-site
California State University - East Bay
Industry Advisor Board - Artificial Intelligence
September 1, 2020 – Present
Fremont, California, United States
San Francisco State University
Industry Advisory Board - Big Data and Artificial Intelligence
August 1, 2020 – Present
San Francisco Bay Area
Intel Corporation
Head of AI Product- Strategic AI Architecture
September 1, 2014 – August 1, 2020
Santa Clara, California, United States
Lenovo
Director - Mobile Product Design and Architecture
November 1, 2012 – August 1, 2014
Santa Clara, California, United States
Aptina
Senior Manager - Mobile Vision and Imaging Product Engineering
December 1, 2003 – November 1, 2012
Santa Clara, CA
NASA
Research Engineer
January 1, 2001 – December 1, 2003
MRCI
Cultural Fit Analysis
The candidate's career trajectory is heavily focused on senior leadership, product strategy, and AI, which is a significant divergence from a hands-on FPGA Developer role. While the PhD in Electrical Engineering and early career at NASA and Aptina show a technical foundation, the last decade has been in high-level management. This profile suggests a strong fit for strategic, leadership, or advisory roles, but a potential mismatch for a dedicated, individual contributor FPGA development position. The breadth of experience is high, but direct alignment with the target role's day-to-day technical demands is low.
Soft Skills & Operational Fit
The candidate's extensive leadership and advisory roles suggest strong communication, strategic thinking, and collaboration skills. Experience at large corporations like Qualcomm and Intel indicates an ability to operate within complex organizational structures. The MBA further supports business acumen and operational understanding.