ZS’s legacy in academic innovation and life sciences consulting began at Northwestern University, where our two cofounders met as professors. Over our 40-year history, ZS has earned recognition for solving complex commercial challenges in life sciences. As ZS has grown, so has its expertise in healthcare, research and development (R&D)—bridging scientific research and healthcare analytics to improve life and how we live it.

Championing data privacy in healthcare through AI innovation

ZS recently won a U.S. and U.K. prize challenge in privacy-enhancing technologies (PETs) at the second Summit for Democracy, cohosted by the White House and the United Kingdom. The challenge spotlighted innovations that use AI and data privacy solutions to support public health without compromising personal information.

Principal Qin Ye, a physician-turned-consultant, led a cross-functional team of ZSers to design a privacy-preserving artificial intelligence (AI) model that forecasts individual pandemic infection risk while safeguarding personal data. The win highlights ZS’s capabilities in AI, data security and privacy technology for real-world healthcare applications.

Where passion changes lives

Qin has been with ZS for seven years, now leading integrated evidence strategy within the firm’s R&D consulting work. “ZS is full of problem-solvers who care about patient outcomes and healthcare transformation,” he says.

When Qin’s team brought him the privacy-enhancing technologies challenge, he was drawn to the complex question: How can healthcare teams unlock insights from patient data while protecting individual privacy?

The solution required developing a federated learning model—a form of AI that enables privacy-preserving collaboration across datasets. Qin brought together a global team of experts, including Sagar Madgi, Mayank Shah, Shaishav Jain, Md. Umar Faraque, Parika Vyas, Kapil Jain and Pranava Goundan, to develop an innovative approach.

Designing privacy-preserving AI for public health

The technical brief challenged teams to build federated learning solutions that combine input and output privacy techniques to predict infection risk. Participants were given access to a synthetic healthcare dataset created by the University of Virginia’s Biocomplexity Institute, which simulated population-level dynamics.

“We collaborated and competed with world-class teams from MIT, Harvard, Carnegie Mellon and others,” Qin recalls. “Though the competition was virtual, it was clear we were part of a global community of experts pushing the limits of what healthcare AI can do.”

Scalable AI solutions for pandemic forecasting and beyond

ZS’s winning entry was an AI-powered privacy-preserving risk prediction tool.

“This model is just the beginning,” says Qin. “It opens new possibilities for privacy-first, data-driven healthcare innovation.”

Recognition on the global stage

ZS was honored at a ceremony hosted at the Royal Society House in London, where representatives from the U.S. and U.K. governments celebrated the winners of the PETs Prize Challenge. ZS is proud to stand alongside global leaders in privacy, security and AI innovation for public health.

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