School of Computer Science faculty members Virginia Smith and Steven Wu have received a Meta Research Award for their project, "Private Multi-Task Learning." The nearly $100,000 award is part of Meta's Privacy-Enhancing Technologies initiative, which aims to design and deploy new solutions that minimize and secure the data the company collects, processes and shares.

Smith, an assistant professor in Carnegie Mellon University's Machine Learning Department (MLD), and Wu, an assistant professor in the Software and Societal Systems Department with appointments in MLD and the Human-Computer Interaction Institute, will investigate how personalization techniques impact utility in machine learning. Specifically, their work will analyze and evaluate a suite of novel tools for differentially private multitask learning, a machine learning personalization technique that aims to solve multiple learning tasks simultaneously across different data silos.

Smith and Wu's project joins nine others selected for funding from more than 160 proposals.

"Building and scaling privacy-enhancing technologies is a key investment for us, not only to improve our own products but also to open-source innovations for use across the industry," said Mike Clark, Meta's director of privacy and product management. "We're excited to champion these innovative scholars and look forward to their long-term impact on enhancing privacy."

For more on the awards, visit Meta's website.