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La startup puertorriqueña XSync seleccionada para la beca de salud digital de la Universidad de Nueva York

Danilo Trinidad Pérez-Rivera, director ejecutivo y científico de XSync, representará a la empresa en el programa de verano Stern Venture Fellowship de la Universidad de Nueva York.

The digital platform uses biometric data and AI to expand access to preventive care.

A digital health platform founded by young Puerto Ricans has been selected for the Stern Venture Fellowship (SVF) at New York University, a program that supports early-stage ventures with potential for broad impact.

XSync uses biometric monitoring, predictive analytics and community-based tools to advance preventive and lifestyle medicine, with a focus on underserved populations. The platform combines artificial intelligence with applied science and emphasizes ethical data practices.

“The Stern Venture Fellowship recognizes our ability to transform the lessons of past crises into technological solutions for the present and future,” said Danilo Trinidad Pérez-Rivera, CEO and scientific director of XSync. “XSync was born from that conviction, and this support validates the path our team has taken.”

Pérez-Rivera, who is completing a doctorate in computational neuroscience, will participate in the SVF’s 10-week summer program. The fellowship provides executive mentorship, access to capital, industry workshops and strategic networking, along with a $10,000 seed fund to support XSync’s development.

Co-founder Joshua Villafañe serves as chief of operations and compliance. He previously worked on Puerto Rico’s COVID-19 public health technology response, including the development of community surveillance tools.

“This support gives us the impetus to continue strengthening our mission of integrating technologies that not only connect personal and community well-being, but also support a preventive and sustainable healthcare model,” Villafañe said.

XSync’s selection for the SVF is expected to help the company advance its goal of using biometric tools and predictive data to inform decisions that improve health outcomes.

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