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Pages

Posts

Future Blog Post

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Blog Post number 4

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Blog Post number 3

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Blog Post number 2

less than 1 minute read

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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 1

less than 1 minute read

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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Research

publications

Invasive Optical Pumping for Room-Temperature Masers, Time-Resolved EPR, Triplet-DNP, and Quantum Engines Exploiting Strong Coupling

Published in Optics Express, Volume 28, Issue 20, 2020

This study demonstrates waveguide-based invasive optical pumping of pentacene crystals, enabling enhanced energy delivery for room-temperature masers and triplet-DNP systems.

Recommended citation: Hao Wu, Shamil Mirkhanov, Wern Ng, Kuan-Cheng Chen, Yuling Xiong, Mark Oxborrow (2020). "Invasive Optical Pumping for Room-Temperature Masers, Time-Resolved EPR, Triplet-DNP, and Quantum Engines Exploiting Strong Coupling." Optics Express, 28(20), 29691–29702.
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Short-depth circuits and error mitigation for large-scale GHZ-state preparation, and benchmarking on IBM’s 127-qubit system

Published in 2023 IEEE International Conference on Quantum Computing and Engineering (QCE), 2023

Depth-reduced circuit designs and error-mitigation strategies boost GHZ-state fidelity on IBM’s 127-qubit Eagle and 27-qubit Falcon processors.

Recommended citation: Chen, Kuan-Cheng. (2023). "Short-depth circuits and error mitigation for large-scale GHZ-state preparation, and benchmarking on IBM's 127-qubit system." Proceedings of the 2023 IEEE International Conference on Quantum Computing and Engineering (QCE), 2, 207-210.
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Shedding Light on the Future: Exploring Quantum Neural Networks through Optics

Published in Advanced Quantum Technologies, 2024

This paper reviews the design and optical implementation of quantum neural networks (QNNs), exploring architectures such as quantum perceptrons and quantum Boltzmann machines and their feasibility in quantum optics.

Recommended citation: Shang Yu, Zhian Jia, Aonan Zhang, Ewan Mer, Zhenghao Li, Valerio Crescimanna, Kuan‐Cheng Chen, Raj B. Patel, Ian A. Walmsley, Dagomir Kaszlikowski (2024). "Shedding Light on the Future: Exploring Quantum Neural Networks through Optics." Advanced Quantum Technologies, 2400074.
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HamilToniQ: An Open-Source Benchmark Toolkit for Quantum Computers

Published in 2024 IEEE International Conference on Quantum Computing and Engineering (QCE), 2024

HamilToniQ and its H-Score metric provide an open, transparent framework for benchmarking the fidelity and reliability of quantum processors.

Recommended citation: Xu, Xiaotian; Chen, Kuan-Cheng; & Wille, Robert. (2024). "HamilToniQ: An Open-Source Benchmark Toolkit for Quantum Computers." Proceedings of the 2024 IEEE International Conference on Quantum Computing and Engineering (QCE).
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Learning quantum phase estimation by variational quantum circuits

Published in 2024 International Joint Conference on Neural Networks (IJCNN), 2024

A variational circuit approximation of Quantum Phase Estimation cuts circuit depth and boosts accuracy on noisy quantum devices.

Recommended citation: Liu, Chen-Yu; Chen, Kuan-Cheng; & Lin, Chu-Hsuan Abraham. (2024). "Learning quantum phase estimation by variational quantum circuits." Proceedings of the 2024 International Joint Conference on Neural Networks (IJCNN), 1–6.
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Quantum-Classical-Quantum Workflow in Quantum-HPC Middleware with GPU Acceleration

Published in 2024 International Conference on Quantum Communications, Networking, and Computing (QCNC), 2024

A distribution-aware QCQ architecture integrates QPUs and GPU-accelerated HPC for efficient quantum simulations and phase transition classification.

Recommended citation: Chen, Kuan-Cheng; Li, Xiaoren; Xu, Xiaotian; Wang, Yun-Yuan; & Liu, Chen-Yu. (2024). "Quantum-Classical-Quantum Workflow in Quantum-HPC Middleware with GPU Acceleration." Proceedings of the 2024 International Conference on Quantum Communications, Networking, and Computing (QCNC), 304–311.
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QTRL: Toward Practical Quantum Reinforcement Learning via Quantum-Train

Published in 2024 IEEE International Conference on Quantum Computing and Engineering (QCE), 2024

QTRL trains classical policy models using quantum circuits, avoiding quantum inference and enabling practical quantum reinforcement learning.

Recommended citation: Liu, Chen-Yu; Lin, Chu-Hsuan Abraham; Yang, Chao-Han Huck; Chen, Kuan-Cheng; & Hsieh, Min-Hsiu. (2024). "QTRL: Toward Practical Quantum Reinforcement Learning via Quantum-Train." Proceedings of the 2024 IEEE International Conference on Quantum Computing and Engineering (QCE).
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Quantum-Train Long Short-Term Memory: Application on Flood Prediction Problem

Published in 2024 IEEE International Conference on Quantum Computing and Engineering (QCE), 2024

A Quantum-Train LSTM model reduces parameters and improves practicality for flood prediction in climate change scenarios.

Recommended citation: Lin, Chu-Hsuan Abraham; Liu, Chen-Yu; & Chen, Kuan-Cheng. (2024). "Quantum-Train Long Short-Term Memory: Application on Flood Prediction Problem." Proceedings of the 2024 IEEE International Conference on Quantum Computing and Engineering (QCE).
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Quantum Computing for Climate Resilience and Sustainability Challenges

Published in 2024 IEEE International Conference on Quantum Computing and Engineering (QCE), 2024

This review explores how quantum computing can address climate resilience and sustainability through machine learning and optimization techniques.

Recommended citation: Ho, Kin Tung Michael; Chen, Kuan-Cheng; Lee, Lily; Burt, Felix; Yu, Shang; & Lee, Po-Heng. (2024). "Quantum Computing for Climate Resilience and Sustainability Challenges." Proceedings of the 2024 IEEE International Conference on Quantum Computing and Engineering (QCE).
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Noise-Aware Distributed Quantum Approximate Optimization Algorithm on Near-term Quantum Hardware

Published in 2024 IEEE International Conference on Quantum Computing and Engineering (QCE), 2024

A distributed, noise-aware QAOA framework enhances scalability and reliability for optimization tasks on near-term quantum hardware.

Recommended citation: Chen, Kuan-Cheng; Xu, Xiaotian; Burt, Felix; Liu, Chen-Yu; Yu, Shang; & Leung, Kin K. (2024). "Noise-Aware Distributed Quantum Approximate Optimization Algorithm on Near-term Quantum Hardware." Proceedings of the 2024 IEEE International Conference on Quantum Computing and Engineering (QCE).
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Quantum-enhanced Support Vector Machine for Large-scale Multi-class Stellar Classification

Published in International Conference on Intelligent Computing, 2024

A quantum-enhanced SVM model improves precision and speed in stellar classification, outperforming classical methods across large datasets.

Recommended citation: Chen, Kuan-Cheng; Xu, Xiaotian; Makhanov, Henry; Chung, Hui-Hsuan; & Liu, Chen-Yu. (2024). "Quantum-enhanced Support Vector Machine for Large-scale Multi-class Stellar Classification." In Proceedings of the International Conference on Intelligent Computing, Springer, pp. 155–168.
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Generalised Circuit Partitioning for Distributed Quantum Computing

Published in 2024 IEEE International Conference on Quantum Computing and Engineering (QCE), 2024

A graph-based framework jointly optimizes gate and state teleportation to minimize entanglement cost in distributed quantum computing.

Recommended citation: Burt, Felix; Chen, Kuan-Cheng; & Leung, Kin. (2024). "Generalised Circuit Partitioning for Distributed Quantum Computing." Proceedings of the 2024 IEEE International Conference on Quantum Computing and Engineering (QCE).
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Unlocking the Potential of Photoexcited Molecular Electron Spins for Room Temperature Quantum Information Processing

Published in Materials for Quantum Technology, Volume 4, Issue 4, 2024

This work demonstrates a room-temperature spin system with long coherence times, leveraging photoexcited molecular radicals in viscous media for future quantum information applications.

Recommended citation: Kuan-Cheng Chen, Alberto Collauto, Ciarán J. Rogers, Shang Yu, Mark Oxborrow, Max Attwood (2024). "Unlocking the Potential of Photoexcited Molecular Electron Spins for Room Temperature Quantum Information Processing." Materials for Quantum Technology, 4(4), 045901.
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Toward Large-Scale-Qubit Quantum Circuit Simulation in Quantum Machine Learning with cuTN-QSVM

Published in Quantum Techniques in Machine Learning (QTML 2024), 2024

cuTensorNet-accelerated QSVM simulations (cuTN-QSVM) enable faster, larger-scale quantum kernel evaluations on NVIDIA GPUs.

Recommended citation: Li, Tai-Yue; Chen, Kuan-Cheng; & Wang, Yun-Yuan. (2024). "Toward Large-Scale-Qubit Quantum Circuit Simulation in Quantum Machine Learning with cuTN-QSVM." Proceedings of the Quantum Techniques in Machine Learning (QTML 2024).
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Overcoming the Thermal-Noise Limit of Microwave Measurements by Precooling with an Active Cold Load

Published in Physical Review Applied, 2024

This work introduces active pre-cooling (APC), a method that significantly reduces thermal noise in microwave cavities by coupling to an active cold load.

Recommended citation: Chen, Kuan-Cheng; & Oxborrow, Mark. (2024). "Overcoming the Thermal-Noise Limit of Microwave Measurements by Precooling with an Active Cold Load." Phys. Rev. Appl., American Physical Society. https://doi.org/10.1103/bjky-3yb3
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Validating Large-Scale Quantum Machine Learning: Efficient Simulation of Quantum Support Vector Machines Using Tensor Networks

Published in Machine Learning: Science and Technology, Volume 6, Number 1, 2025

We present an efficient tensor-network-based approach for simulating large-scale quantum support vector machines (QSVMs), scaling to hundreds of qubits using cuTensorNet and MPI for multi-GPU acceleration.

Recommended citation: Kuan-Cheng Chen*, Tai-Yue Li, Yun-Yuan Wang, Simon See, Chun-Chieh Wang, Robert Wille, Nan-Yow Chen, An-Cheng Yang, Chun-Yu Lin (2025). "Validating Large-Scale Quantum Machine Learning: Efficient Simulation of Quantum Support Vector Machines Using Tensor Networks." Machine Learning: Science and Technology, 6(1), 015047. DOI: 10.1088/2632-2153/adb4ba
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Quantum-Train-Based Distributed Multi-Agent Reinforcement Learning

Published in 2025 IEEE Symposium for Multidisciplinary Computational Intelligence Incubators (MCII Companion), 2025

Dist-QTRL leverages quantum-train methods in distributed multi-agent reinforcement learning, enabling scalable, parallel training with parameter reduction.

Recommended citation: Chen, Kuan-Cheng; Chen, Samuel Yen-Chi; Liu, Chen-Yu; & Leung, Kin K. (2025). "Quantum-Train-Based Distributed Multi-Agent Reinforcement Learning." Proceedings of the 2025 IEEE Symposium for Multidisciplinary Computational Intelligence Incubators (MCII Companion), 1–5.
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Programming Variational Quantum Circuits with Quantum-Train Agent

Published in 2025 International Conference on Quantum Communications, Networking, and Computing (QCNC), 2025

The QT-QFWP framework leverages quantum-driven updates to efficiently program variational quantum circuits for predictive time-series tasks.

Recommended citation: Liu, Chen-Yu; Chen, Samuel Yen-Chi; Chen, Kuan-Cheng; Huang, Wei-Jia; & Chang, Yen-Jui. (2025). "Programming Variational Quantum Circuits with Quantum-Train Agent." Proceedings of the 2025 International Conference on Quantum Communications, Networking, and Computing (QCNC), 544–548.
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Noise-Aware Detectable Byzantine Agreement for Consensus-based Distributed Quantum Computing

Published in 2025 International Conference on Quantum Communications, Networking, and Computing (QCNC), 2025

This work enhances Byzantine agreement in distributed quantum systems with error mitigation and verification mechanisms for secure consensus.

Recommended citation: Chen, Kuan-Cheng; Prest, Matthew; Burt, Felix; Yu, Shang; & Leung, Kin K. (2025). "Noise-Aware Detectable Byzantine Agreement for Consensus-based Distributed Quantum Computing." Proceedings of the 2025 International Conference on Quantum Communications, Networking, and Computing (QCNC), 210–215.
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Quantum Kernel-Based Long Short-Term Memory for Climate Time-Series Forecasting

Published in 2025 International Conference on Quantum Communications, Networking, and Computing (QCNC), 2025

QK-LSTM integrates quantum kernels into LSTM models for efficient, accurate forecasting of climate-related time-series like AQI.

Recommended citation: Hsu, Yu-Chao; Chen, Nan-Yow; Li, Tai-Yu; Lee, Po-Heng Henry; & Chen, Kuan-Cheng. (2025). "Quantum Kernel-Based Long Short-Term Memory for Climate Time-Series Forecasting." Proceedings of the 2025 International Conference on Quantum Communications, Networking, and Computing (QCNC), 421–426.
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CompressedMediQ: Hybrid Quantum Machine Learning Pipeline for High-Dimensional Neuroimaging Data

Published in ICASSP 2025 – IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2025

CompressedMediQ integrates classical pre-processing with QSVM-based classification to tackle high-dimensional neuroimaging data in dementia diagnostics.

Recommended citation: Chen, Kuan-Cheng; Li, Yi-Tien; Li, Tai-Yu; Liu, Chen-Yu; Lee, Po-Heng; & Chen, Cheng-Yu. (2025). "CompressedMediQ: Hybrid Quantum Machine Learning Pipeline for High-Dimensional Neuroimaging Data." Proceedings of ICASSP 2025 – IEEE International Conference on Acoustics, Speech, and Signal Processing.
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Consensus-based Distributed Quantum Kernel Learning for Speech Recognition

Published in ICASSP 2025 – IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2025

CDQKL leverages distributed quantum kernel learning to enhance speech recognition while preserving data privacy across quantum nodes.

Recommended citation: Chen, Kuan-Cheng; Ma, Wenxuan; & Xu, Xiaotian. (2025). "Consensus-based Distributed Quantum Kernel Learning for Speech Recognition." Proceedings of ICASSP 2025 – IEEE International Conference on Acoustics, Speech, and Signal Processing.
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Quantum Kernel-Based Long Short-Term Memory

Published in ICASSP 2025 – IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2025

QK-LSTM integrates quantum kernels into LSTM networks, achieving efficient temporal modeling with reduced parameters for resource-constrained environments.

Recommended citation: Hsu, Yu-Chao; Li, Tai-Yu; & Chen, Kuan-Cheng. (2025). "Quantum Kernel-Based Long Short-Term Memory." Proceedings of ICASSP 2025 – IEEE International Conference on Acoustics, Speech, and Signal Processing.
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Quantum-Trained Convolutional Neural Network for Deepfake Audio Detection

Published in ICASSP 2025 – IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2025

QT-CNN leverages quantum parameter training to enhance deepfake audio detection with reduced model complexity and high classification accuracy.

Recommended citation: Lin, Chu-Hsuan Abraham; Liu, Chen-Yu; Chen, Samuel Yen-Chi; & Chen, Kuan-Cheng. (2025). "Quantum-Trained Convolutional Neural Network for Deepfake Audio Detection." Proceedings of ICASSP 2025 – IEEE International Conference on Acoustics, Speech, and Signal Processing.
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Tensor Network-Based Quantum-Train with Distributed Ansatz for Scalable Quantum-Classical Models

Published in ICASSP 2025 – IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2025

A scalable Quantum-Train framework replaces MLPs with tensor networks and introduces a distributed ansatz for large-scale quantum-classical learning.

Recommended citation: Liu, Chen-Yu; Lin, Chu-Hsuan Abraham; & Chen, Kuan-Cheng. (2025). "Tensor Network-Based Quantum-Train with Distributed Ansatz for Scalable Quantum-Classical Models." Proceedings of ICASSP 2025 – IEEE International Conference on Acoustics, Speech and Signal Processing, 1–4.
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Frame Generation in Hilbert Space: Generative Interpolation of Measurement Data for Quantum Parameter Adaptation

Published in ICLR 2025 DeLTa Workshop on Deep Generative Models, 2025

Generative Interpolation reduces quantum measurement overhead in QPA by treating quantum outcomes like video frames and interpolating missing data.

Recommended citation: Liu, Chen-Yu; Chen, Kuan-Cheng; Chen, Samuel Yen-Chi; Huang, Wei-Jia; & Chang, Yen Jui. (2025). "Frame Generation in Hilbert Space: Generative Interpolation of Measurement Data for Quantum Parameter Adaptation." ICLR 2025 Workshop on Deep Generative Models.
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Toward Large-Scale Distributed Quantum Long Short-Term Memory with Modular Quantum Computers

Published in IWCMC 2025 – The 21st International Wireless Communications & Mobile Computing Conference, 2025

This work introduces a scalable Distributed QLSTM framework using modular quantum computers for large-scale temporal sequence modeling.

Recommended citation: Chen, Kuan-Cheng; Chen, Samuel Yen-Chi; Liu, Chen-Yu; & Leung, Kin K. (2025). "Toward Large-Scale Distributed Quantum Long Short-Term Memory with Modular Quantum Computers." Proceedings of IWCMC 2025 – The 21st International Wireless Communications & Mobile Computing Conference.
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Quantum-Enhanced Parameter-Efficient Learning for Typhoon Trajectory Forecasting

Published in IEEE INFOCOM 2025 – IEEE International Conference on Computer Communications, 2025

This study applies Quantum Parameter Adaptation (QPA) to efficiently train a typhoon trajectory forecasting model using hybrid quantum-classical learning.

Recommended citation: Liu, Chen-Yu; Chen, Kuan-Cheng; Chen, Yi-Chien; Chen, Samuel Yen-Chi; Huang, Wei-Hao; Huang, Wei-Jia; & Chang, Yen-Jui. (2025). "Quantum-Enhanced Parameter-Efficient Learning for Typhoon Trajectory Forecasting." Proceedings of IEEE INFOCOM 2025 – IEEE International Conference on Computer Communications.
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Resource-Efficient Compilation of Distributed Quantum Circuits for Solving Large-Scale Wireless Communication Network Problems

Published in ISCAS 2025 – IEEE International Symposium on Circuits and Systems, 2025

This work proposes a hybrid quantum-classical compiler for optimizing large-scale wireless sensor network routing via distributed QAOA and spectral clustering.

Recommended citation: Chen, Kuan-Cheng; Burt, Felix; Yu, Shang; Liu, Chen-Yu; Hsieh, Min-Hsiu; & Leung, Kin K. (2025). "Resource-Efficient Compilation of Distributed Quantum Circuits for Solving Large-Scale Wireless Communication Network Problems." Proceedings of ISCAS 2025 – IEEE International Symposium on Circuits and Systems.
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Quantum Stochastic Walks for Portfolio Optimization: Theory and Implementation on Financial Networks

Published in npj Unconventional Computing, 3, 7, 2026

A quantum stochastic-walk approach to portfolio optimization over financial networks.

Recommended citation: Chang, Y.-J.; Wang, W.-T.; Wang, Y.-Y.; Liu, C.-Y.; Chen, K.-C.; and Chang, C.-R. (2026). "Quantum Stochastic Walks for Portfolio Optimization: Theory and Implementation on Financial Networks." npj Unconventional Computing, 3, 7.
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Adaptive Resource Orchestration for Distributed Quantum Computing Systems

Published in IEEE Internet Computing, 2026

A distributed quantum-computing orchestration framework for scalable entanglement generation, scheduling, and quantum-HPC operation.

Recommended citation: Chen, K.-C.; Burt, F.; Panigrahy, N. K.; and Leung, K. K. (2026). "Adaptive Resource Orchestration for Distributed Quantum Computing Systems." IEEE Internet Computing.
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Consensus Protocols for Entanglement-Aware Scheduling in Distributed Quantum Neural Networks

Published in 2026 International Conference on Quantum Communications, Networking, and Computing (QCNC), 2026

A consensus and scheduling framework for robust distributed quantum neural-network training over fragile entanglement resources.

Recommended citation: Chen, K.-C.; Chen, S. Y.-C.; Chehimi, M.; Burt, F.; and Leung, K. K. (2026). "Consensus Protocols for Entanglement-Aware Scheduling in Distributed Quantum Neural Networks." IEEE QCNC 2026.
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Lightweight Noise Diagnosis for Photonic Quantum Detectable Byzantine Agreement

Published in 2026 International Conference on Quantum Communications, Networking, and Computing (QCNC), pp. 759–763, 2026

A lightweight diagnostic approach for photonic quantum detectable Byzantine agreement protocols.

Recommended citation: Bogner, K.; Chen, K.-C.; Abidin, A.; and Leung, K. K. (2026). "Lightweight Noise Diagnosis for Photonic Quantum Detectable Byzantine Agreement." IEEE QCNC 2026, pp. 759–763.

Applied Quantum Machine Learning on PCB Multi-Class Defect Detection

Published in 2026 International Conference on Quantum Communications, Networking, and Computing (QCNC), pp. 1–6, 2026

An applied QML study for multi-class printed-circuit-board defect detection.

Recommended citation: Huang, C.-W.; Chen, K.-C.; and Lai, C.-J. (2026). "Applied Quantum Machine Learning on PCB Multi-Class Defect Detection." IEEE QCNC 2026, pp. 1–6.

Generative Quantum-Inspired Kolmogorov–Arnold Eigensolver

Published in arXiv preprint arXiv:2605.04604, 2026

A quantum-inspired Kolmogorov–Arnold eigensolver for parameter-efficient quantum chemistry workflows.

Recommended citation: Lin, Y.-C.; Hsu, Y.-C.; Tsai, I.; Lin, C.-H.; Peng, K.-C.; Jiang, J.-C.; Wang, Y.-Y.; Huang, T.-C.; Li, T.-Y.; Chen, K.-C.; Chen, S. Y.-C.; and Chen, N.-Y. (2026). "Generative Quantum-Inspired Kolmogorov–Arnold Eigensolver." arXiv:2605.04604.
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Heterogeneous Optically-Detected Spin-Acoustic Resonance in Solid-State Molecular Thin Film

Published in Communications Physics, 2026

Accepted Communications Physics article on room-temperature molecular spin-acoustic resonance in a solid-state thin-film platform.

Recommended citation: Chen, K.-C.; Wen, Y.; Xu, X.; Attwood, M.; Xu, J.; Fu, C.; Ramadan, S.; Yu, S.; Heutz, S.; and Oxborrow, M. (2026). "Heterogeneous Optically-Detected Spin-Acoustic Resonance in Solid-State Molecular Thin Film." Communications Physics. Accepted.

Extensible Universal Photonic Quantum Computing with Nonlinearity

Published in Nature Photonics, 2026

Accepted Nature Photonics article on extensible universal photonic quantum computing enabled by nonlinearity.

Recommended citation: Yu, S.; Sun, J.; Chen, K.-C.; Yang, Z.-H.; Li, Z.; Mer, E.; Alwehaibi, Y. K.; Winston, S. H.; Lopena, D. M. D.; Zhang, Z.-C.; Yang, G.; Tao, R.; Zhou, M.; Machado, G. J.; Dong, Y.; Bondesan, R.; Vedral, V.; Kim, M. S.; Walmsley, I. A.; and Patel, R. B. (2026). "Extensible Universal Photonic Quantum Computing with Nonlinearity." Nature Photonics. Accepted.

talks

teaching

An Introduction to the Imperative Part of C++

Postgraduate course, Taipei Medical University, Department of Medical Engineering, 2024

Teaching Overview

This course provides a comprehensive introduction to programming through the imperative core of the C++ language. It is designed specifically for postgraduate students in the Department of Medical Engineering at Taipei Medical University, many of whom come from non-computing backgrounds. The course content is adapted from a long-established version taught at Imperial College London, with a strong emphasis on practical problem-solving using ANSI/ISO standard C++ and the GNU g++ compiler.

Data Engineering and Machine Learning

Undergraduate course, Imperial College London, Department of Civil and Environmental Engineering, 2025

Teaching Overview

During the official Spring Term at Imperial College London, I served as a guest lecturer for the undergraduate module CIVE70122: Data Engineering, hosted by the Department of Civil and Environmental Engineering. This module focused on the practical application of data engineering and machine learning techniques for solving real-world analytical problems.

Quantum Computing

MSc invited lecture, Imperial College London, Department of Computing, 2026

Teaching Overview

I delivered an invited lecture for the MSc Advanced Computing course Quantum Computing in the Department of Computing. The lecture introduced students to superconducting qubits as one of the leading hardware platforms for gate-based quantum computing, connecting the physical principles of qubit implementation with practical execution on real quantum processors.

Emerging Topics in Integrated Machine Learning Systems

MSc guest lecture, UCL, Department of Electronic and Electrical Engineering, 2026

Teaching Overview

I delivered a guest lecture for the MSc course Emerging Topics in Integrated Machine Learning Systems within the Integrated Machine Learning Systems MSc at UCL’s Department of Electronic and Electrical Engineering. My lecture, titled “Quantum Artificial Intelligence: From Optimisation and Machine Learning to Solving Real-World Problems,” introduced students to the emerging field of Quantum Artificial Intelligence (QAI) and its relevance to next-generation machine learning systems.