About me

I am a research engineer at Meta AI Research, working with Ilya Mironov and Mike Rabbat. I graduated with a Masters from UC Davis in 2019, where I worked with Prem Devanbu and Vincent Hellendoorn. My research interests include federated learning and differential privacy.

Publications (see all)

Preprints

Toward Fair Federated Recommendation Learning: Characterizing the Inter-Dependence of System and Data Heterogeneity.

  • Kiwan Maeng, Haiyu Lu, Luca Melis, John Nguyen, Mike Rabbat, Carole-Jean Wu.

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, Jesik Min, Mani Malek.

  • Conference on Machine Learning and Systems (MLSys), 2022.

Federated Learning with Buffered Asynchronous Aggregation

  • John Nguyen, Kshitiz Malik, Hongyuan Zhan, Ashkan Yousefpour, Mike Rabbat, Mani Malek, Dzmitry Huba.

  • International Conference on Artificial Intelligence and Statistics (AISTATS), 2022.

2021

Opacus: User-Friendly Differential Privacy Library in PyTorch

  • Ashkan Yousefpour*, Igor Shilov*, Alexandre Sablayrolles*, Davide Testuggine, Karthik Prasad, Mani Malek, John Nguyen, Sayan Ghosh, Akash Bharadwaj, Jessica Zhao, Graham Cormode, Ilya Mironov. ∗Equal contribution.

  • Privacy in Machine Learning (PriML) workshop, NeurIPS 2021