California: USC and Amazon today announced they are creating a joint research center focused on development of new approaches to machine learning (ML) privacy, security, and trustworthiness. The Center for Secure and Trusted Machine Learning, which will be housed at the University of Southern California’s Viterbi School of Engineering, will support USC and Amazon researchers in the development of novel approaches to privacy-preserving ML solutions.
The expectation is that the center will unleash a new line of fundamental research on privacy and security aspects of machine learning – a timely and critical effort given the proliferation of artificial intelligence across all aspects of society from education to finance, transportation, healthcare, and many others.
Each year, the center will provide support for research projects focused on the development of new methodologies for secure and privacy-preserving machine learning solutions that can scale to support billions of users. In addition, the center will provide annual fellowships to talented doctoral students working in this research area, enabling them to advance research frontiers. Fellowship recipients will be named as Amazon ML Fellows in recognition of their promise and achievements. These fellowships will give students greater understanding of industry and solution-driven research.
“Developing solutions to protect our data requires cutting edge advances. I am pleased the USC-Amazon center will build a platform based on a shared commitment to advancing understanding and developing solutions,” said USC Provost Charles F. Zukoski. “The center reflects the important role that our university has in society, as a leading research institution, in promoting the advancement of scholarship and technology.”
“At Amazon, our mission is to be Earth’s most customer-centric company,” said Prem Natarajan, Alexa AI vice president of Natural Understanding. “For us, customer trust is of paramount importance. And that means maintaining the highest possible standards of security and privacy when handling customer data. We are delighted to bring together top talent at Amazon and USC in a joint mission to drive ground-breaking advances in privacy and security preserving machine learning – advances that enable us to continue to safely and securely deliver experiences that enrich and delight our customers worldwide.”
In addition to funded research projects and annual fellowships for doctoral students, the collaborators will host an annual joint public research symposium to share their knowledge with the machine learning and AI communities. Amazon and USC will also host annual workshops, and training and recruiting events for university and high school students.
“We are delighted to partner with Amazon in establishing the Center for Secure and Trusted Machine Learning at the USC Viterbi School of Engineering. Creating such mutually beneficial partnerships between academia and industry will help guide the development of a field as important and as rapidly changing as machine learning and artificial intelligence. Enhancing the security and trustworthiness of these powerful technologies is a necessity and a grand challenge-type problem. We eagerly anticipate the results of this new collaboration,” said Yannis C. Yortsos, dean of the USC Viterbi School of Engineering.
Salman Avestimehr, professor and director of the Information Theory and Machine Learning research lab at USC Viterbi and an Amazon Scholar, will be the inaugural director of the center.
“The USC-Amazon center provides an exciting opportunity, through close university-industry collaboration, to study trust and security. Through the center’s Amazon ML Fellows program, we can also recognize our exceptional PhD students and further the impact of their research through collaborations with Amazon,” says Avestimehr.
The new center is expected to leverage talent and scholarship across Amazon and USC Viterbi, particularly the Ming Hsieh Department of Electrical and Computer Engineering, the Department of Computer Science, and the school’s leading research institutes, such as the Information Sciences Institute.