Towards Federated Learning at Scale: System Design. - Kallista A. Bonawitz; Hubert Eichner; Wolfgang Grieskamp; Dzmitry Huba; Alex Ingerman; Vladimir Ivanov; Chloé Kiddon; Jakub Konecný; Stefano Mazzocchi; Brendan McMahan; Timon Van Overveldt; David Petrou; et al. (SysML, 2019)

Federated Learning with Buffered Asynchronous Aggregation. - John Nguyen; Kshitiz Malik; Hongyuan Zhan; Ashkan Yousefpour; Mike Rabbat; Mani Malek 001; Dzmitry Huba (AISTATS, 2022)

PAPAYA: Practical, Private, and Scalable Federated Learning. - Dzmitry Huba; John Nguyen; Kshitiz Malik; Ruiyu Zhu; Mike Rabbat; Ashkan Yousefpour; Carole-Jean Wu; Hongyuan Zhan; Pavel Ustinov; Harish Srinivas; Kaikai Wang; Anthony Shoumikhin; et al. (MLSys, 2022)

FEL: High Capacity Learning for Recommendation and Ranking via Federated Ensemble Learning. - Meisam Hejazinia; Dzmitry Huba; Ilias Leontiadis; Kiwan Maeng; Mani Malek 001; Luca Melis; Ilya Mironov; Milad Nasr; Kaikai Wang; Carole-Jean Wu (CoRR, 2022)

Federated Ensemble Learning: Increasing the Capacity of Label Private Recommendation Systems. - Meisam Hejazinia; Dzmitry Huba; Ilias Leontiadis; Kiwan Maeng; Mani Malek 001; Luca Melis; Ilya Mironov; Milad Nasr; Kaikai Wang; Carole-Jean Wu (IEEE Data Eng. Bull., 2023)

Confidential Federated Computations. - Hubert Eichner; Daniel Ramage; Kallista A. Bonawitz; Dzmitry Huba; Tiziano Santoro; Brett McLarnon; Timon Van Overveldt; Nova Fallen; Peter Kairouz; Albert Cheu; Katharine Daly; Adrià Gascón; et al. (CoRR, 2024)

Federated Analytics in Practice: Engineering for Privacy, Scalability and Practicality. - Harish Srinivas; Graham Cormode; Mehrdad Honarkhah; Samuel Lurye; Jonathan Hehir; Lunwen He; George Hong; Ahmed Magdy; Dzmitry Huba; Kaikai Wang; Shen Guo; Shoubhik Bhattacharya (CoRR, 2024)

PAPAYA Federated Analytics Stack: Engineering Privacy, Scalability and Practicality. - Harish Srinivas; Graham Cormode; Mehrdad Honarkhah; Samuel Lurye; Jonathan Hehir; Lunwen He; George Hong; Ahmed Magdy; Dzmitry Huba; Kaikai Wang; Shen Guo; Shoubhik Bhattacharya (NSDI, 2025)