Speaker Profile
Biography
Currently, Vahram Mouradian focuses on pioneering AI-driven integrated ecosystems for a new generation of wearable medical devices at KehaAI, Inc. His work uniquely converges electronic integrated biosensors with fundamental clinical research to drive digital transformation in healthcare technology.
With a career spanning over 30 years, he brings extensive expertise in semiconductor technology, clinical research, and multi-vital human physiology modeling. Throughout his career, he has achieved clinical relevance in wearables by bridging the gap between hard science and practical application.
Previously, Vahram held key leadership positions where he specialized in translating fundamental research into innovative technologies and scaling high-growth teams. Known for a collaborative approach, he is passionate about applying cutting-edge science to solve complex physiological challenges. Based in Plano, Texas, he focuses on leading strategic initiatives that seamlessly integrate technical execution with measurable business impact.
Talk
Enabling calibration-free clinical-grade Blood Pressure (BP) wearable ring
We present kRing, the first medical grade wearable ring being developed to enable calibration free, continuous blood pressure monitoring for patients and caregivers. This breakthrough integrates artificial intelligence with clinically proven sensing to transform hypertension management and remote patient monitoring.
AI and Data Sciences Showcase:
KehaAI, Inc.
Medical technology company focused on developing advanced, non-invasive sensing technologies. By combining clinical rigor with innovative AI, KehaAI is dedicated to creating wearable solutions that empower individuals and healthcare providers in the proactive management of chronic conditions.
Session Abstract – PMWC 2026 Silicon Valley
The PMWC 2026 AI Company Showcase will provide a 15-30 minute time slot for selected AI companies to present their latest technologies to an audience of leading investors, potential clients, and partners. We will hear from companies building technologies that expedite the pre-clinical and clinical drug discovery and development process, accelerate patient diagnosis and treatment, or develop scalable systems framework to make AI and deep/machine learning a reality.




