Biography
Dr. Yao has led Univfy from founding through stages of technology invention and commercialization. She is now leading the team to scale Univfy’s business. Dr. Yao has over 20 years of experience in clinical and scientific research in reproductive medicine. Prior to founding Univfy, she was on the faculty at Stanford University, where she led NIH-funded fertility and embryo genetics research and developed the Univfy technology with the academic founding team. Dr. Yao graduated from medical school at the University of Toronto and completed her obstetrics and gynecology residency training at McGill University. She received her clinical subspecialty training in reproductive endocrinology and infertility at Brigham and Women’s Hospital at Harvard University. Dr. Yao received multiple research awards for her fertility research work, including pre-implantation embryo development, the role of stem cell genes in the embryo, and uterine receptivity at implantation.
Clinical Dx Showcase:
Univfy
Univfy is dedicated to helping individuals and couples realize their dream of becoming parents. We are IVF and fertility analytics experts passionate about providing you with the tools to choose IVF with greater confidence, success, and cost-success transparency.
An AI Platform to Improve IVF Access and Patients’ Experience Across Diverse Demographics
Univfy is dedicated to helping individuals and couples realize their dream of becoming parents. We are IVF and AI experts passionate about providing you with the tools to choose IVF with greater confidence, success, and cost-success transparency.
The PMWC 2020 Data Applications in Clinical Diagnostics Showcase will provide a 15-minute time slot for selected organizations, including commercial companies, clinical testing labs, and medical research institutions, to present their latest advancements, insights, applications, and technologies to an audience of clinicians, leading investigators, academic institutions, pharma and biotech, investors, and potential clients. We will learn about new technologies and findings that promise expedited, cost-effective, and accurate clinical diagnosis for early disease detection, treatment decisions, and disease prevention.