Research fellows / Postdocs
Adam Narbudowicz is the PI of the Science Foundation Ireland SIRG project “Wireless Physical Layer Cryptography for Post-Quantum Internet of Things using Antenna-Channel Interaction” (18/SIRG/5612).
The “Internet of Things” (IoT) requires most daily objects to be connected into Internet. It allows significant economical stimuli, however, also poses security risks due to remotely executed malicious attacks. Wireless IoT devices are often operating from small battery-powered platforms, with limited support for computationally expensive higher-layer cryptography. The project aims to create a physical-layer wireless cryptography system. As part of this work, it integrates novel antenna designs with signal processing algorithms that take the full benefit of the propagation channel. Combination of those components allows increased secrecy of the wireless communication without significantly increasing system overhead, i.e. computational complexity or power consumption. The technology is developed into two directions: for directional modulation to increase secrecy of communication; for Angle-of-Arrival estimation, that allows collection of forensic data about active attackers. Both solutions are tailored to operate from compact IoT devices.
Abel received his bachelor’s degree in information engineering from South China University of Technology in 2017, and his master’s in electrical and Software Systems Engineering from King Mongkut’s University of Technology North Bangkok in 2019. In 2018 – 2020 he studied at the Institute of High Frequency Technology of RWTH Aachen University.
Abel is pursuing his PhD on the topic of Wireless Physical Layer Cryptography for Post-Quantum Internet of Things using Antenna-Channel Interaction funded by Science Foundation Ireland. He is currently investigating advanced pattern reconfigurable antennas to allow direction modulation, Angle of Arrival estimation, and MIMO systems, from compact IoT devices. His research interest also includes leaky-wave antennas, digital beamforming, electrically small antennas, software defined radio.
André is a Ph.D. student in Electronic and Electrical Engineering at CONNECT Centre in Trinity College Dublin, Ireland, since 2019. He works on wireless communication and is particularly interested in self-organizing networks with a focus on resource allocation. He has published on applied reinforcement learning to the medium access control (MAC) sublayer and network sharing for ultra-reliable communication–find publications here. The latter comprises his ongoing research and is key to wireless networks to support emerging critical-communication services such as factory automation, mobile cloud computing, and network remote-controlled vessels. In addition to the WhyCOM lab, he is also a member of SATORI, a joint project between Trinity College Dublin, Ireland, and Tsinghua University, China, to leverage data-driven solutions to the next generation of communication networks.
Quantum-domain communications can be a potential candidate for addressing problems, like, scarcity of available electromagnetic spectrum and shortage in fibre bandwidth. In her Ph.D., Mouli Chakraborty is theoretically modelling quantum channels carrying classical information and formulating upper bounds for achievable capacity over super-activated realistic quantum channels (finite-dimensional and if possible, arbitrary-dimensional)’
Pieter Barnard graduated in 2019 with an integrated masters and bachelor’s degree in Electronic & Computer from Engineering Trinity College Dublin. During his undergraduate studies, he undertook numerous projects, including an industrial placement at Cylon Controls Ltd in 2018. At Cylon, his main achievements included the design and evaluation of a power failover system for Fast Ethernet controllers used in building automation and management. In 2019, Pieter developed a digital watermarking scheme based on the human visual system and Discrete Fourier Transform, as part of his final year master’s thesis. He is currently pursuing his PhD on the topics of Exploring Explainable AI in Wireless Networks at the CONNECT Centre for future networks, with funding from ADVANCE. His research focuses on AI and machine learning applied to resource management of wireless networks with a primary focus to develop new ways in which trust and explainability can be incorporated into the design of AI driven systems, such as those based on deep neural networks , and which are also infamously regarded as “black boxes” due to a lack of transparency in their behaviour. His current research interests include signal processing, radio resource management, machine learning and hardware design.