Yoga Rahulamathavan, PhD

For Students

I am always enthusiastic to supervise strongly motivated MSc and PhD students willing to work in my research area (in brief: security and privacy). If you are interested, please email me with a short note and your CV.

Short Bio

Yogachandran Rahulamathavan is a Reader in Cybersecurity and Privacy and joined Loughborough University London in 2016.

After obtaining a PhD in Signal Processing from Loughborough University in 2012, Rahul joined the Information Security group at City, University of London as a Research Fellow to lead the signal processing in encrypted domain research theme. During this time, he was a security and privacy work package leader for the large-scale integrated project SpeechXrays (H2020 Grant 653586, 2015–2019) funded by the European Commission.

Since April 2016, he joined Loughborough University's postgraduate campus in London as a Lecturer, was promoted to Senior Lecturer in January 2020, and to Reader in January 2024. He is the module leader for Cybersecurity and Forensics, Principles of Artificial Intelligence and Data Analytics, and Information Management. He is one of the recipients of British Council's UK-India research funding (2017) and led a project between Loughborough, City and IIT Kharagpur. Rahul leads a team of PhD students and serves as the principal investigator for an industry-funded project supported by Airbus Defence.

Rahul is Programme Director for MSc Cyber Security and Data Analytics at Loughborough University London.

News

• Appointed as an Associate Editor for IEEE Transactions on Dependable and Secure Computing.
• One of our papers has been cited in a NIST internal report, proposing how attribute-based encryption can enhance data privacy in blockchain. NIST report.

Academic Background

• BSc (Hons) Engineering, University of Moratuwa, Sri Lanka, 2008 (First Class)
• PhD Signal Processing, Loughborough University, UK, 2012
• PG Cert in Academic Practice, Loughborough University, 2018
• Lecturer, Loughborough University, 2016–2020

Current Research and Collaborations

Rahul and his students work on the following fundamental areas of research within the field of Responsible AI.

• Privacy-preserving Machine Learning: Techniques enabling training and inference while protecting sensitive data, including federated learning and homomorphic encryption (from lattice-based cryptography).
• Interpretable and Explainable AI (XAI): Methods to make models more transparent and interpretable. Current work includes using 2nd order sensitivity analysis to enhance the explainability of machine learning algorithms.

Research Product: BioOnPaper — Secure Ownership Verification Solution

BioOnPaper is an ownership verification solution designed to address the challenges of secure, privacy-enhanced, and cost-effective verification at the edge. It connects physical objects (tickets, keys, documents, and more) with their rightful owners in the digital realm, without requiring complex infrastructure or internet connectivity.

Key features

• Biometric enrolment and verification : Two-step workflow. During enrolment, biometric features are extracted, processed, encrypted, and imprinted onto objects. During verification, the algorithm compares imprinted features with facial biometrics to validate ownership.
• Robust security, zero internet dependency: Eliminates the need for internet connectivity during verification.
• Biometric morphing attack protection: Algorithms designed to counter morphing attacks and unauthorized ownership attempts.
• Data compression for easy printing: Compresses biometric data for printing on various materials without chips or specialized equipment.
• Privacy-preserving encryption: Encryption ensures biometric data remains confidential; the edge verification device cannot decrypt sensitive information.

Research Talk Abstract

Rahul has been invited to deliver keynote talks by conferences and organizations, recognizing his expertise and contributions to privacy-preserving machine learning.

• PLEX: Perturbation-free Local Explanations for LLM-Based Text Classification, University of Jaffna, Mar 2026
• Role of AI/ML in Marketing, IBA University, Pakistan, Sep 2025
• Privacy-Preserving Data Sharing: Tools and Applications, University of Warwick, 2023
• ICCS, Wales, UK, 2022
• Sixth International Conference on Information Technology Research, Moratuwa, Sri Lanka, 2021
• Public Key Infrastructure and Its Applications, Bangalore, India, 2021

Keynote title: Hide-and-Seek: Machine Learning in Encrypted Domain

Keynote abstract: Machine learning models are trained on large volumes of high-quality data, but privacy concerns can prevent sharing sensitive inputs with service providers. Encryption helps during storage and transmission, yet privacy-preserving computation is needed to process data without exposing it. This talk introduces privacy-preserving techniques for processing data in the encrypted domain, highlighting the role of fully homomorphic encryption from lattice-based cryptography, and surveys state-of-the-art work, challenges, and trends.

Research Funding

• Project PI for UK-India collaborative project (£220k) funded by British Council (75k for Loughborough) on secure IoT networks [Jun 2017 – Jun 2020]
• LU PI for Airbus Defence project (£120k) on lattice cryptography for next-generation access control (£42k for Loughborough) [Sep 2023 – Aug 2026]
• LU Co-I for EPSRC HappierFeet (£400k) on data analytics and machine learning for healthcare data (£60k for LU) [Sep 2021 – Sep 2023]

Publications

• ORCID: 0000-0002-1722-8621
• Google Scholar: profile
• DBLP search: Yoga Rahulamathavan
• Loughborough staff profile: page

PhD Supervision

Current PhD students

• Mr Zohaib Shahid (2022–2025) — Explainability and Fairness in AI
• Miss Misbah Farooq (2022–2026) — LLM explainability via steering
• Mr Nasir Iqbal (2023–2027) — Machine unlearning
• Mr John Smith (2025–2028) — Privacy-preserving techniques in healthcare

Past PhD supervision

• Dr Charuka Kotagaloluwegedara-Herath-Mudi (2022–Mar 2026) — Privacy-preserving Federated Machine Learning
• Mr Flavio Pinto (2018–2024) — Distributed Technologies to transform Anti-Doping Control Mechanism
• Dr Omattage Madushi Pathmaperuma (2018–2022) — Machine learning techniques to classify encrypted network traffic (currently Senior Lecturer in Sri Lanka)
• Dr Fauzia Idrees Abro (2015–2018) — Investigating Android permissions and intents for malware detection (Senior Lecturer at Royal Holloway, University of London, UK)
• Dr Fei Li (2012–2016) — Attribute-based encryption for fine-grain access control (Senior Engineer at HC Financial Services)

Selected/Recent Professional Activities

Conferences

• Conference TPC (IEEE CNS 2023; IEEE ICC 2020–now; IEEE Globecom; 2019–now)
• Conference Chair (IEEE MetaCom 2022; PST 2023; FHE 2023; IEEE Blockchain 2023; FCN 2023)
• General Chair, International Workshop in Internet of Things and Security, London, 2020

Editorship

• Book editor: Data Protection in a Post-Pandemic Society: Laws, Regulations, Best Practices and Recent Solutions
• Topical Advisory Panel member, Sensors (MDPI)
• Associate Editor for IEEE TDSC (2024–now)
• Guest Editor (Hindawi 2016; IJFCS 2017; Sage 2018; IEEE Access 2019; Sensors 2021; Springer 2023)
• Associate Editor for IEEE Access (2020–2023)
• Associate Editor for Sensors (2020–now)
• Associate Editor for Springer PPNA (2021–now)

External Examining

• NUST, Pakistan
• VIT, India
• Newcastle University, UK

Other: Fellow of Higher Education Academy (2018).

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