“We received innovative proposals from our faculty proposing exciting research into various aspects of trustworthy machine learning. The response was so overwhelming that we decided to fund one more project than our original intention.”
–Salman Avestimehr, inaugural director of the USC+Amazon Center, Dean’s Professor of ECE and computer science, Amazon Scholar
Back in January, 2021, USC and Amazon announced the establishment of a new center for secure and trusted machine learning. After asking USC faculty for proposals, five research initiatives were recently announced for the upcoming year:
- “Federated Learning for Natural Language Processing” (by Xiang Ren and Mahdi Soltanolkotabi )
- “Reconciling Privacy and Fairness in Federated Learning” (by Aleksandra Korolova )
- “Federated Learning for Human-centered Experience and Perception Modeling with Biobehavioral Data” (by Shrikanth Narayanan)
- “Fast Fair Decentralized Learning” (by Keith Burghardt)
- “Efficient Federated Learning in Heterogeneous and Corrupted Environments by Secure Performance Weighting” (by Jose Luis Ambite , Muhammad Naveed , and Paul Thompson)
