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Staff Profile

Dr Aydin Abadi

Lecturer in Cybersecurity

Background

Aydin Abadi is a Lecturer (Assistant Professor) in the School of Computing, at Newcastle University. Aydin is a researcher and expert in the field of computer science, security, privacy, and cryptography, particularly known for his work in privacy-enhancing technologies. His main research interests include:

  • Privacy-Preserving Machine Learning and AI, such as
  • Privacy-Preserving Federated Learning
  • Developing other Privacy Enhancing Technologies (PETs), such as
  • Private Set Intersection (PSI)
  • Secure Multi-party Computation (MPC)
  • Time-lock Encryptions/Puzzles
  • Oblivious Transfers
  • Post-quantum Cryptography, such as
  • Post-quantum Oblivious Transfer
  • Financial Technology (FinTech)
  • Developing provably secure online payment systems
  • Dealing with online payment fraud (including traditional banking and decentralized payment frameworks)
  • Cryptanalysis of online payment systems
  • Cryptanalysis
  • Identifying security of state-of-the-art security mechanisms
  • Blockchain, Smart Contracts, and their Applications
  • Verifiable Computation
  • Cloud Computing Security

Join the Team

Dr. Abadi welcomes PhD students with a strong interest in:

  • Theoretical or Applied Cryptography
  • Privacy-Preserving Machine Learning
  • Secure Multi-Party Computation
  • Blockchain and Decentralized Systems
  • Secure Payment Protocols

Prospective students will have the opportunity to work on cutting-edge research projects, contribute to open-source implementations, and collaborate with leading experts in the field.

Professional Contributions and Recognitions:

One of the hallmark achievements of Aydin Abadi's career (so far) is his involvement in the STARLIT project. This initiative, developed in collaboration with the company Privitar, aims to advance privacy-enhancing technologies, a critical area in today's digital landscape where data security and privacy are of paramount importance. The project's success was recognized at an international level when it was awarded the joint first prize in the UK-US Privacy Enhancing Technology Prize Challenge in 2023. This prestigious competition seeks to encourage and reward innovative solutions that protect privacy while allowing for the responsible use of data. The STARLIT project and its recognition have further amplified Aydin Abadi's impact, with recognition from high-profile institutions such as the White House and the UK Government reflecting the project's importance and relevance in the global conversation on data privacy. During his PhD studies at the University of Strathclyde, Aydin earned the Euan Minto Prize in 2015, awarded for the best paper authored by a research student in the Computer Science Department.

Academic Background:

Before Joining Newcastle University, he worked as a (a) Senior Research Fellow at UCL, (b) Lecturer at the University of Gloucestershire, and (c) Research Associate in Blockchain Lab, at the University of Edinburgh. Aydin completed his (i) PhD, in Secure Multi-Party Computation (i.e., PSI) at the University of Strathclyde, Glasgow, (ii) MSc, in Computer Science, at the University of Leeds, (iiI) BSc, Software Engineering, University of Lahijan, Iran, and (iv) Diploma, Mathematics and Physics, Iran.

Other Profiles:

  • His "Google Scholar'' can be found here.
  • His ''DBLP Profile'' can be found here.
  • His ''GitHub profile'' can be found here, which contains the codes of the open-source software and decentralized apps (Dapps) he has developed.


Research

Research Overview:

Dr. Aydin Abadi is an Assistant Professor in Cybersecurity at Newcastle University's School of Computing. His research lies at the intersection of:

  • Secure AI and Machine Learning
  • Cryptography
  • Financial Technology
  • Blockchain Technology and Smart Contracts
  • Secure Systems
  • Privacy-Enhancing Technologies (PETs)

He focuses on designing scalable, provably secure (cryptographic) protocols that translate rigorous theoretical constructs into effective, real-world solutions; particularly, in the contexts of federated learning, secure payments, cryptography, and decentralized infrastructures. His work is driven by the challenge of enabling data utility while ensuring strong privacy guarantees in highly adversarial and data-intensive environments.


Join the Team:

Dr. Abadi is actively recruiting PhD students with a strong interest in cryptography, privacy-preserving federated learning, secure AI, secure multi-party computation, blockchain technologies, and secure payment systems. Students will have the opportunity to work on cutting-edge research, contribute to open-source projects, and collaborate with academic and industry partners on real-world privacy and security challenges.


Key Areas of Research:

  • Privacy-Enhancing Technologies (PETs). Dr. Abadi develops practical PETs that enable organizations to extract value from data while rigorously protecting individual privacy. His work combines theoretical security models with real-world constraints, offering deployable solutions that preserve confidentiality without sacrificing utility. His research in this broad field includes:
  • Efficient data processing techniques over encrypted or partitioned data.
  • Privacy-preserving deduplication for federated learning systems.
  • Adaptable PETs for constrained environments (e.g., drones, IoT, mobile clients).
  • Secure Multi-Party Computation and Private Set Intersection (PSI). Dr. Abadi's research in secure multi-party computation (MPC) and PSI addresses the need for collaborative data analysis among distrusting parties without compromising individual data privacy. He develops lightweight, efficient protocols that minimize communication and computational overhead, making privacy-preserving collaboration practical in real-world deployments.
  • Delegated PSI: Protocols that enable outsourcing of PSI computation to untrusted servers while preserving privacy and correctness.
  • Incentive-Based PSI: Protocols that incorporate reward mechanisms to encourage honest participation, particularly useful in open environments where parties may have misaligned interests.
  • PSI for Federated Learning: Specialized PSI schemes designed to align datasets across distributed clients in FL setups, enabling accurate model training without disclosing raw data.
  • Secure Payment Systems & Financial Cryptography. In the FinTech space, Dr. Abadi focuses on securing the lifecycle of digital transactions, from authentication to fraud mitigation.
  • Protocols to deal with Authorized Push Payment (APP) fraud.
  • Fair exchange systems for verifiable, atomic delivery of digital services.
  • Blockchain-based insurance and payment dispute resolution using smart contracts.
  • Cryptanalysis. He rigorously analyzes the security of cryptographic protocols, identifying subtle flaws in widely accepted schemes and proposing countermeasures to strengthen their robustness. His work combines cryptanalytic insight with constructive design improvements, contributing to both the theoretical and practical advancement of secure systems.
  • Developing Core Cryptographic Primitives. Dr. Abadi designs and refines foundational cryptographic protocols that serve as building blocks for secure computation and communication. His work addresses both theoretical soundness and practical efficiency, ensuring these primitives can be integrated into real-world systems with strong security guarantees.
  • Oblivious Transfer (OT): Aydin has developed highly efficient and scalable OT protocols, with a focus on post-quantum security and composability. 
  • Time-Lock Puzzles: He explores verifiable and scalable time-lock constructions, mechanisms that enforce time-delayed access to data. These constructs are vital in scenarios such as fair exchange, sealed-bid auctions, digital wills, and time-based access control in decentralized environments.

Awards:


Dr. Abadi's contributions have been recognized with several awards, including the Euan Minto Prize for the best research paper by a postgraduate student at the University of Strathclyde, and a joint first-place award in the prestigious UK–US Privacy Enhancing Technologies Prize Challenge (2023) for his work on privacy-preserving federated learning. He was also nominated for a Staff Excellence Award at the University of Gloucestershire in 2021.




Publications