Livia: Data-Centric Computing Throughout the Memory Hierarchy. - Elliot Lockerman; Axel Feldmann; Mohammad Bakhshalipour; Alexandru Stanescu; Shashwat Gupta; Daniel Sánchez 003; Nathan Beckmann (ASPLOS, 2020)

F1: A Fast and Programmable Accelerator for Fully Homomorphic Encryption. - Nikola Samardzic; Axel Feldmann; Aleksandar Krastev; Srinivas Devadas; Ronald G. Dreslinski; Christopher Peikert; Daniel Sánchez 003 (MICRO, 2021)

F1: A Fast and Programmable Accelerator for Fully Homomorphic Encryption (Extended Version). - Axel Feldmann; Nikola Samardzic; Aleksandar Krastev; Srini Devadas; Ronald G. Dreslinski; Karim Eldefrawy; Nicholas Genise; Chris Peikert; Daniel Sánchez 003 (CoRR, 2021)

CraterLake: a hardware accelerator for efficient unbounded computation on encrypted data. - Nikola Samardzic; Axel Feldmann; Aleksandar Krastev; Nathan Manohar; Nicholas Genise; Srinivas Devadas; Karim Eldefrawy; Chris Peikert; Daniel Sánchez 003 (ISCA, 2022)

An Architecture to Accelerate Computation on Encrypted Data. - Axel Feldmann; Nikola Samardzic; Aleksandar Krastev; Srinivas Devadas; Ronald G. Dreslinski; Chris Peikert; Daniel Sánchez 003 (IEEE Micro, 2022)

Spatula: A Hardware Accelerator for Sparse Matrix Factorization. - Axel Feldmann; Daniel Sánchez 003 (MICRO, 2023)

FeatUp: A Model-Agnostic Framework for Features at Any Resolution. - Stephanie Fu; Mark Hamilton; Laura E. Brandt; Axel Feldmann; Zhoutong Zhang; William T. Freeman (ICLR, 2024)

DsDm: Model-Aware Dataset Selection with Datamodels. - Logan Engstrom; Axel Feldmann; Aleksander Madry (ICML, 2024)

Azul: An Accelerator for Sparse Iterative Solvers Leveraging Distributed On-Chip Memory. - Axel Feldmann; Courtney Golden; Yifan Yang; Joel S. Emer; Daniel Sánchez 003 (MICRO, 2024)

I-Con: A Unifying Framework for Representation Learning. - Shaden Naif Alshammari; John R. Hershey; Axel Feldmann; William T. Freeman; Mark Hamilton (ICLR, 2025)

MiniFold: Simple, Fast, and Accurate Protein Structure Prediction. - Jeremy Wohlwend; Mateo Reveiz; Matt McPartlon; Axel Feldmann; Wengong Jin; Regina Barzilay (Trans. Mach. Learn. Res., 2025)

Optimizing ML Training with Metagradient Descent. - Logan Engstrom; Andrew Ilyas; Benjamin Chen; Axel Feldmann; William Moses; Aleksander Madry (CoRR, 2025)