Dr Hamid Tebyanian

Profile

Dr Hamid Tebyanian is a quantum physicist specialising in quantum communication and secure technologies. As a Marie Curie Fellow on the European project “Quantum Communication for All” at the University of Geneva, Vigo, and Padova, his research focused on developing practical quantum communication protocols to bring quantum technologies one step closer to users’ backdoors. At ID Quantique Switzerland, he worked on the design and fabrication of multimode fibre-coupled superconducting nanowire single-photon detectors (SNSPDs), addressing applications in quantum optics, single-photon imaging, and low-light-level detection. He subsequently contributed to a UK-wide project on the assurance of quantum random number generators, collaborating with 14 partners – including Toshiba and Quantinuum – to rigorously assess and validate the security of commercial QRNG devices. At the National Physical Laboratory, his research has concentrated on developing entanglement sources for experimental Bell inequality violations, with direct relevance to secure quantum communication. He is currently a lecturer at Queen Mary University of London, where his work bridges quantum science with advances in artificial intelligence, machine learning, and computing.

Teaching

Machine and Deep Learning 2024/5

Scientific Measurement 2026/27

AI in the Real World, Applied AI 2026/27

Research

Research Interests:

Dr Hamid Tebyanian’s research focuses on artificial intelligence, post-quantum cryptography, quantum security, quantum communication and quantum photonics. His work combines machine learning, information theory, optimisation and experimental quantum technologies, with a main interest in developing systems that remain reliable and secure under realistic noise, imperfect devices and adversarial conditions.

A growing part of his research is on AI for security and scientific systems. He develops machine-learning methods for analysing quantum devices, identifying hidden structure in physical data and improving security monitoring. His work includes deep-learning-based assessment of quantum random number generators, device-aware machine-learning diagnostics, physics-informed time-series models and learning-guided security auditing. A key part of this work is to use AI as an additional diagnostic and decision tool while keeping the final security or scientific claim independently verifiable.

His recent work in post-quantum cryptography studies how the quality and structure of randomness affects modern cryptographic schemes such as ML-DSA. This includes analysing whether conventional entropy guarantees remain valid after cryptographic processing, identifying structured and correlated source failures, and studying how post-quantum cryptography can be combined with QKD and certified quantum randomness. More broadly, he is interested in crypto-agility and hybrid quantum-safe systems that combine classical, post-quantum and quantum security technologies.

In quantum cryptography, he develops device-independent, semi-device-independent and source-device-independent approaches for quantum random number generation and quantum communication. His research uses information-theoretic methods, convex and semidefinite optimisation and finite-size statistical analysis to determine what can be securely certified from experimentally accessible information without assuming that every device is fully trusted.

His work in quantum randomness spans both continuous-variable and discrete-variable systems. This includes homodyne and heterodyne detection, squeezed and coherent states, time-bin encoding, orbital angular momentum, contextuality-based randomness and high-speed source-device-independent architectures. Recent work includes a 33 Gbit/s heterodyne QRNG with real-time FPGA-integrated extraction, squeezed-state semi-device-independent randomness generation and integrated silicon-photonic randomness based on quantum contextuality.

In quantum optics and communication, he works with nonlinear and entangled-photon sources, SPDC, SHG and SFWM, single-photon detectors, integrated photonics and balanced optical receivers. His work at the National Physical Laboratory included the optimisation of high-quality entangled-photon sources for Bell inequality violations and device-independent quantum communication. He has also worked on semiconductor spin-noise systems and solid-state emitters as scalable physical sources for certified quantum randomness.
Another part of his research focuses on quantum technology assurance. This includes understanding how detector behaviour, calibration errors, technical noise, finite statistics and implementation assumptions affect the security that can actually be claimed from a quantum device. This work aims to connect formal security proofs with practical hardware and has involved collaborations with academic, industrial and national-laboratory partners.

His broader research interests include quantum foundations, contextuality, Bell inequalities, quantum-state indistinguishability and the possible effects of quantum-gravity-inspired models on quantum correlations.

Publications

Generalized time-bin quantum random number generator with uncharacterized devices

Quantum randomness generation via orbital angular momentum modes crosstalk in a ring-core fiber

Unbounded randomness from uncharacterized sources

Holographic vacuum energy regularization and corrected entropy of de Sitter space

Practical Semi-Device Independent Randomness Generation Based on Quantum State's Indistinguishably

Visit Hamid Tebyanian's Google Scholar profile for a full list of publications.

Supervision

Pradnya Chandrakant Bhakare — Physics-Informed Transformers for Day-Ahead Electricity Price Forecasting: A Regime-Shift Analysis for Germany

Alessandro Manfredi — Physics-Informed Temporal Fusion Transformers for Joint Forecasting of Electricity Prices and Renewable Energy Generation

Gonzalo Roberto Guerrero Pichén — Testing the Faithfulness of Temporal Fusion Transformer Explanations in Influenza Forecasting

Nijat Khalilov — Stress-testing the Interpretability of Temporal Fusion Transformer for Influenza Forecasting