Concrete ML: Privacy Preserving ML framework using Fully Homomorphic Encryption (FHE), built on top of Concrete, with bindings to traditional ML frameworks.
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Curl: Private LLMs through Wavelet-Encoded Look-Up Tables
Samples of multi-class text classification with Differential Privacy Tensorflow 2.0
Sisyphus: A Cautionary Tale of Using Polynomial Activations in Privacy-Preserving Deep Learning
Hands-on part of the Federated Learning and Privacy-Preserving ML tutorial given at VISUM 2022
Comparative analysis of Structural Gravity Estimators (PPML vs. Polyads) on sparse international trade data (CEPII BACI). A replication and benchmarking project based on Resende, Lecué et al. (2026).
Thesis and replication pipeline using realized US customs data to test whether the 2025 Liberation Day tariffs lowered trade or mainly shifted imports from China toward other foreign suppliers.
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