Fatemeh Zarinjouei

Graduate Research Assistant in Applied Cryptography

Education

M.S. Computer Science | Sharif University of Technology, Tehran, Iran | 2023–2025 (expected)
GPA: 19.61 / 20 — Thesis: Zero-Knowledge Machine Learning (ZKML)
B.S. Computer Science | University of Isfahan, Isfahan, Iran | 2019–2023
GPA: 17.87 / 20 — Ranked 1st in the Computer Science Department
Diploma in Mathematics and Physics | NODET (National Organization for Development of Exceptional Talents)
GPA: 19.64 / 20

Research Interests

I am broadly interested in applied cryptography and its use in building systems that protect users’ privacy in the real world. Recently, I have become focused on proof systems and their potential to make machine learning more trustworthy and auditable. My research explores cryptographic approaches to trustworthy machine learning, including the design of zero-knowledge proofs for neural networks that enable verifiable inference without exposing sensitive model parameters. More broadly, I aim to develop privacy-preserving machine learning pipelines that not only safeguard users’ data but also provide auditable guarantees of compliance, combining secure multi-party computation and zero-knowledge proofs to create systems that can be transparently trusted in deployment.

Research Experience

Graduate Research Assistant — ZKRNN: Zero-Knowledge Proofs for Recurrent Neural Networks (2024–Present)
University of Sheffield & Sharif University of Technology

Designing cryptographic protocols to generate succinct zero-knowledge proofs for RNN inference using Incrementally Verifiable Computation (IVC).
Currently developing and preparing a manuscript for publication.

Research Intern — Secure E-Voting with Everlasting Privacy (2025–Present)
École Polytechnique Fédérale de Lausanne (EPFL)

Extending the TRIP framework to achieve post-quantum everlasting privacy guarantees in e-voting.
Exploring cryptographic primitives and protocol designs for long-term security against quantum adversaries.

Research Intern — Proof-of-Personhood Usability Study for Digital Democracy (2025–Present)
École Polytechnique Fédérale de Lausanne (EPFL)

Developed a mobile-friendly web application for Proof-of-Personhood (PoP) to support usability evaluation.
Conducted a pilot study and preparing for HR-approved user study.

Graduate Research Assistant — Privacy-Preserving Federated Learning (2023–2024)
Sharif University of Technology

Investigated secure aggregation and MPC-based techniques to enhance privacy in federated learning.
Focused on challenges in security and privacy for distributed machine learning systems.

Undergraduate Researcher — Automated Quality Control System using YOLO (2022–2023)
University of Isfahan

Built an image-processing system using YOLO to detect missing components on electronic boards.
Deployed on Raspberry Pi for industrial quality control use.

Teaching Experience

Introduction to Cryptography (Graduate) Sharif University of Technology (2024)
Foundation of Blockchains (Graduate) University of Minnesota, Twin Cities (2023)
Mathematical Database University of Isfahan (2023)
Data Structures and Algorithms University of Isfahan (2022)

Relevant Courses

• Theory of Distributed Systems (20/20) • Design and Analysis of Algorithms (20/20) • Introduction to Cryptography (20/20) • Machine Learning Theory (20/20) • Matrix Computation (20/20)
• Advanced Programming (20/20) • Linear Optimization (20/20) • Principles of Operating Systems (20/20)

Course Projects

Computer Vision Project — Intro to Machine Learning, SUT
Face Recognition using Eigenfaces and PCA — Matrix Computations, SUT
Cracking a Classic Encryption Scheme — Cryptography Project, University of Isfahan
RSA Encryption and Decryption System — Advanced Programming, University of Isfahan

Technical Skills

Programming: Python, C++, SQL, JavaScript, Solidity, RISC-V
Machine Learning: PyTorch, Scikit-Learn, Pandas, NumPy, Matplotlib, YOLO
Tools: LaTeX, Git, PyQt5

Beyond Research

🥾 Hiking and spending time in nature
🚴‍♀️ Biking on trails and in the city
🎨 Painting
🎥 Watching and reviewing films