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Alexander Viand

I am a postdoctoral researcher in the Cambridge Compiler Lab at the University of Cambridge in addition to my work at Belfort Labs. I develop compilers, tools and systems that make privacy-preserving computation more practical and accessible. My research spans fully homomorphic encryption, secure multi-party computation and zero-knowledge proofs, with a focus on abstractions and automation that help non-experts use these technologies. I am also interested in usable security and privacy, and how these technologies interact with society.

I received my PhD from ETH Zürich in May 2023, where I was a doctoral student and research assistant in the Applied Cryptography Group and a member of the Privacy Preserving Systems Lab. I also received my MSc and BSc in Computer Science from ETH Zürich. During my PhD, I visited Tobias Grosser at the University of Edinburgh and Dawn Song at UC Berkeley. Before my current roles, I was a research scientist in the Privacy Technologies Research group at Intel Labs from 2023 to 2025.

Selected Publications:

Thumbnail of HEIR: A Universal Compiler for Homomorphic Encryption

Asra Ali, Jaeho Choi, Bryant Gipson, Shruthi Gorantala, Jeremy Kun, Wouter Legiest, Lawrence Lim, Alexander Viand, Meron Zerihun Demissie, Hongren Zheng

Preprint, arXiv:2508.11095

Thumbnail of vFHE: Verifiable Fully Homomorphic Encryption

Christian Knabenhans*, Alexander Viand*, Antonio Merino-Gallardo, Anwar Hithnawi

Workshop on Encrypted Computing & Applied Homomorphic Cryptography (WAHC '24)

Thumbnail of Pyfhel: PYthon For Homomorphic Encryption Libraries

Alberto Ibarrondo, Alexander Viand

Workshop on Encrypted Computing & Applied Homomorphic Cryptography (WAHC '21).

Thumbnail of Private Outsourced Translation for Medical Data.

Travis Morrison, Bijeeta Pal, Sarah Scheffler, Alexander Viand

In "Protecting Privacy through Homomorphic Encryption" K. Lauter, W. Dai, and K. Laine, editors. Springer, 2021.

Thumbnail of Robust Secure Aggregation for Privacy-Preserving Federated Learning with Adversaries

Lukas Burkhalter, Alexander Viand, Matthias Lei, Hossein Shafagh, Anwar Hithnawi

Privacy Preserving Machine Learning Workshop (PPML), 2019.

Thumbnail of Marble: Making Fully Homomorphic Encryption Accessible to All.

Alexander Viand, Hossein Shafagh

Workshop on Encrypted Computing & Applied Homomorphic Cryptography (WAHC '18). Toronto, Canada,

Talks:

FHE Development Ecosystem: Tools, Compilers & Challenges.

HECO: Automatic Code Optimizations for Efficient Fully Homomorphic Encryption.

Building an End-to-End Toolchain for Fully Homomorphic Encryption with MLIR.

Usable FHE: Opportunities & Challenges.

Service

Program committees

  • IEEE Symposium on Security and Privacy (S&P): 2026, 2027
  • USENIX Security Symposium: 2026, 2027
  • IEEE European Symposium on Security and Privacy (EuroS&P): 2024
  • The Web Conference (WWW): 2020

Conference reviewing

  • ACM Conference on Fairness, Accountability, and Transparency (FAccT): 2027
  • ACM SIGPLAN Symposium on Principles of Programming Languages (POPL): 2026 (external reviewer)
  • International Conference on Compiler Construction (CC): 2026 (external reviewer)
  • ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI): 2023 (external reviewer)
  • ACM SIGPLAN Conference on Object-Oriented Programming, Systems, Languages, and Applications (OOPSLA): 2022 (external reviewer)
  • IEEE Symposium on Security and Privacy (S&P): 2022 (external reviewer)

Journal reviewing

  • Journal of Cryptology: 2022–2025

Departmental service

  • Treasurer, ETH Zürich Scientific Staff Association: 2019–2022
  • President, Computer Science Scientific Staff Association, ETH Zürich: 2018–2021
  • Faculty Hiring Committee, Department of Computer Science, ETH Zürich: 2020
  • Chair, Teaching Commission, Department of Computer Science, ETH Zürich: 2018–2019