Speaker Profile
M.D., Chief Quality & Innovation Officer, MEDNAX
Biography
Ingrid Vasiliu Feltes is a healthcare futurist who has extensive experience in the healthcare industry as a founder, executive, consultant or speaker. She currently is serving as the Chief Quality and Innovation Officer at MEDNAX Healthcare Solutions. In this capacity, she provides oversight for all quality and innovation initiatives across the enterprise,. Additionally, she provides leadership to the MEDNAX Innovation Center & the Center for Research, Education, Quality and Safety. Prior to her current role, she held several leadership positions within the academic, corporate and not-for-profit healthcare arena. After completing her post-graduate residency and fellowship training at Columbia University College of Physicians and Surgeons in 2003, she earned her Executive Masters of Business Administration degree in 2011 from the University of Miami Herbert Business School. During her academic tenure, she taught several courses within the Medical School, as well as the combined MD/PhD and MD/MPH programs. She was a highly active member or chair of several committees and professional organizations. She holds several professional executive certifications from Harvard, MIT and Stanford.
AI and Data Sciences Showcase:
MEDNAX
MEDNAX- Healthcare Solutions Partner
Empowering Precision Medicine via AI & Blockchain
The field of precision medicine has witnessed exponential advances over the past decade and if powered by technologies like AI & Blockchain can be a catalyst for innovative solutions that can change the paradigm in healthcare from " sick care " to " preventative care", as well as serve as the foundation for global population health models.
Session Abstract – PMWC 2020 Silicon Valley
The PMWC 2020 AI Company Showcase will provide a 15-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.
