Supervision

PhD Students

Current:

  • Giulio Segalini (TU Delft, since 2024), Order fairness for blockchains
  • Manon Sourisseau (INRIA Rennes, since 2024), Byzantine Resilient Systems for the Metaverse
  • Bart Cox (TU Delft, since Dec 2021)
  • Rowdy Chotkan (TU Delft, since Oct 2021)

Graduated:

  • Wassim Yahaoui (Uni. Luxembourg, 2020–2025) - Fast, Fair, and Secure Hierarchical Consensus and Dissemination for Blockchain Resilience despite Data-Center Disasters [link]
  • Douglas Simoes Silva (Uni. Luxembourg, 2020–2023) - Resilient Threat-Adaptive Consensus [link]
  • Túlio Pascoal (Uni. Luxembourg) - Secure, privacy-preserving and practical collaborative Genome-Wide Association Studies [link]
  • Tong Cao (Uni. Luxembourg, 2018-2022, co-supervised) - Analyzing the Privacy and Security of Proof-of-Work Cryptocurrencies [link]
  • Maria Fernandes (Uni. Luxembourg, 2016-2020, co-supervised) - Reconciling data privacy with sharing in next-generation genomic workflows [link]
  • Gowher Parry (Uni. Luxembourg, 2017-2019, interrupted) - Network communication in autonomous vehicular networks

MSc Theses

Graduated:

  • Nektarios Evangelou (TU Delft, 2024) - Taming double-spending in offline payments [link]
  • Nikolay Blagoev (TU Delft, 2024) - Robust decentralized training of Large Language Models
  • Nils van den Honert (TU Delft, 2024) - Rollback protection in Damysus [link]
  • Andrea Einarsdóttir (TU Delft, 2024) - Enabling parallel voting in streamlined consensus protocols [link]
  • Nakib Ibrahimi (TU Delft, 2024) - Applying a modular execution environment with MoveVM in a Blockchain-agnostic context: a case study on IOTA
  • Gefei Zhu (TU Delft, 2024) - Tackling data non-iidness in multi-server asynchronous FL [link]
  • Xingyi Luo (TU Delft, 2024) - Adaptive model poisoning Attack
  • Mohamed Rashad (TU Delft, 2023, co-supervised) - Vertical Federated Learning [link]
  • Yuncong Zuo (TU Delft, 2023) - Asynchronous Federated Learning [link]
  • Abele Mălan (TU Delft, 2023, co-supervised) - Federated Learning for Probabilistic Models
  • Aditya Shankar (TU Delft, 2023, co-supervised) - Federated Continual Learning
  • Yanzhuo Zhou (TU Delft, 2023, co-supervised) - Twins-based testing of Byzantine consensus [link]
  • Jin Xu (TU Delft, 2022, co-supervised) - Approximate Gradient Inversion Attack in Federated Learning [link]
  • Christoph Lambert (Uni. Luxembourg, 2017) - Privacy preserving alignment of masked reads in the cloud

Master Level Projects

  • Parallel and Grid Computing project (2019) - Privacy attacks on aggregate genomic data (1 month project)

BSc Projects

  • Rafael Braga Medeiros Mota Borges (Honours project, 2022-2023) - Robust Asynchronous Federated Learning
  • Giulio Segalini (Honours project, 2021-2022) - Memory oblivious algorithms for privacy-preserving release of statistics
  • CSE3000 - Research project (1 or 2 groups of 5 students in 2021, 2022, 2023, 2024)
  • CSE2000 - Software project (2021, 2022, 2024)