Scholar
Jonathan Passerat-Palmbach
Google Scholar ID: EElOUT8AAAAJ
Imperial College London, Flashbots
Privacy Enhancing Technologies
Federated Learning
AI & Privacy
Privacy-Preserving Machine
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Homepage
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Citations & Impact
All-time
Citations
3,564
H-index
20
i10-index
32
Publications
20
Co-authors
5
list available
Contact
Email
j.passerat-palmbach@imperial.ac.uk
CV
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GitHub
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LinkedIn
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Publications
7 items
The MICCAI Federated Tumor Segmentation (FeTS) Challenge 2024: Efficient and Robust Aggregation Methods for Federated Learning
2025
Cited
0
Biologically-Informed Hybrid Membership Inference Attacks on Generative Genomic Models
2025
Cited
0
Proof of Cloud: Data Center Execution Assurance for Confidential VMs
2025
Cited
0
Differentially Private aggregate hints in mev-share
2025
Cited
0
FedCLAM: Client Adaptive Momentum with Foreground Intensity Matching for Federated Medical Image Segmentation
2025
Cited
0
Narrowing the Gap between TEEs Threat Model and Deployment Strategies
2025
Cited
0
Addressing Data Heterogeneity in Federated Learning with Adaptive Normalization-Free Feature Recalibration
arXiv.org · 2024
Cited
0
Resume (English only)
Academic Achievements
Published multiple papers in privacy-preserving and federated learning, including:
“A generic framework for privacy preserving deep learning” (PPML @NeurIPS)
“ARIA: On the interaction between Architectures, Aggregation methods and Initializations in federated visual classification” (ISBI’24)
“Cooperative AI via Decentralized Commitment Devices” (MASEC @NeurIPS’23)
“Zen and the art of model adaptation: Low-utility-cost attack mitigations in collaborative machine learning” (PoPETS 2022)
“2CP: Decentralized Protocols to Transparently Evaluate Contributivity in Blockchain Federated Learning Environments”
“A blockchain-orchestrated Federated Learning architecture for healthcare consortia”
“End-to-end privacy preserving deep learning on multi-institutional medical imaging”
“Split HE: Fast Secure Inference Combining Split Learning and Homomorphic Encryption”
Full publication list available at ORCID: https://orcid.org/0000-0003-3178-9502
Co-authors
5 total
Daniel Rueckert
Technical University of Munich and Imperial College London
Co-author 2
Andrew Trask
University of Oxford and OpenMined
Co-author 4
Dmitrii Usynin
Imperial College London, TU Munich
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