About
Maryam Naeem is a quantum researcher and engineer with experience in quantum computing, quantum machine learning and quantum communication. She has worked across both academic and applied domains, contributing to research and development in emerging quantum technologies.
She previously served as a Marie Curie Doctoral Researcher at Eindhoven University of Technology (TU/e), Netherlands, where her work focused on quantum communication and information systems. In industry she was Lead Quantum Artificial Intelligence Engineer at STEMIAC (Europe), where she led teams, supervised projects, and contributed to research in quantum-enhanced machine learning and improvements to quantum algorithms.
Her research includes quantum-enhanced reinforcement learning, improvements to the HHL algorithm, continuous-variable quantum key distribution (CV-QKD), and quantum teleportation protocols.
Through QLogix she aims to bridge the gap between quantum theory and practical implementation, building a foundation for applied quantum technologies in Pakistan.
M.Phil research
Cavity QED based quantum teleportation protocol
IEEE Quantum Week · 2024 · 14 citations · Research track
Abstract. This work is a foundational research effort in quantum communication, focusing on the physical realisation of quantum teleportation using cavity quantum electrodynamics (QED) systems. It develops a complete teleportation protocol by integrating the components required for practical implementation: the generation of remote entanglement to establish a quantum communication channel, and the realisation of fundamental quantum logic operations such as controlled-NOT and Hadamard gates. A major focus is the modelling of atom-cavity interactions, enabling the transfer and manipulation of quantum states within controlled environments, and the study of how quantum states can be transmitted securely through entanglement-based communication. The work establishes a basis in quantum information processing, quantum optics and quantum communication systems for advanced quantum technologies and real-world applications.
- QKD
- Quantum communication
- Security
Projects
Multidimensional reconciliation for continuous-variable QKD Ongoing
Improving the performance of CV-QKD systems, particularly under low signal-to-noise conditions, through advanced reconciliation techniques including multidimensional encoding and LDPC-based error correction, to raise decoding efficiency and secure key generation rates. Project page
Hybrid quantum-classical reinforcement learning using the HHL algorithm Planned
Integrating the Harrow-Hassidim-Lloyd (HHL) quantum algorithm with reinforcement learning frameworks to solve real-world decision-making problems. By reformulating reinforcement learning models into linear systems, HHL computes value functions more efficiently, leveraging quantum parallelism for potential exponential speedup. Project page
Improving the efficiency of HHL-based learning systems Planned
Addressing the practical limitations of the HHL algorithm, including matrix sparsity, condition number and scalability. Optimisation strategies to improve time complexity and enable more practical applications of quantum algorithms in machine learning.
