The Centre draws together expertise working on flexible, stretchable functional materials for electronic systems. Applications include printed electronics, sensors, energy harvesting and wearable smart textiles.
Xiaoyu Zhang (Colin) received the BEng degree in electronic information engineering from the University of Electronic Science and Technology of China (UESTC) in 2014, and the MSc and PhD degrees from the University of Southampton in 2015 and 2020, respectively. He is currently a Visiting Fellow to the Next Generation Wireless research group at the University of Southampton.
Modulation, error correction and other signal processing techniques in wireless and optical communications.
5G physical layer design techniques, such as channel estimation, channel equalisation, milimetre wave and massive MIMO.
Zhang, Xiaoyu, Wang, Qi, Zhang, Rong, Chen, Sheng and Hanzo, Lajos (2017) Performance analysis of layered ACO-OFDM. IEEE Access, 5, 18366-18381. (doi:10.1109/ACCESS.2017.2748057).
Zhang, Xiaoyu, Babar, Zunaira, Zhang, Rong, Chen, Sheng and Hanzo, Lajos (2019) Multi-class coded layered asymmetrically clipped optical OFDM. IEEE Transactions on Communications, 67 (1), 579-589. (doi:10.1109/TCOMM.2018.2869821).
Babar, Zunaira, Zhang, Xiaoyu, Botsinis, Panagiotis, Alanis, Dimitrios, Chandra, Daryus, Ng, Soon Xin and Hanzo, Lajos (2019) Near-capacity multilayered code design for LACO-OFDM-aided optical wireless systems. IEEE Transactions on Vehicular Technology, 68 (4), 4051-4054. (doi:10.1109/TVT.2019.2896764).
Zhang, Xiaoyu, Chen, Sheng and Hanzo, Lajos (2020) On the discrete-input continuous-output memoryless channel capacity of layered ACO-OFDM. IEEE Journal of Lightwave Technology, 38 (18), 4955-4968, [9098085]. (doi:10.1109/JLT.2020.2996541).
Lacava, Cosimo, Babar, Zunaira, Zhang, Xiaoyu, Demirtzioglou, Iosif, Petropoulos, Periklis and Hanzo, Lajos (2020) High-speed multi-layer coded adaptive LACO-OFDM and its experimental verification. OSA Continuum, 3 (9), 2614-2629. (doi:10.1364/OSAC.394227).
Zhang, Xiaoyu, Babar, Zunaira, Petropoulos, Periklis, Haas, Harald and Hanzo, Lajos (2021) The evolution of optical OFDM. IEEE Communications Surveys & Tutorials, 23 (3), 1430-1457, [9378787]. (doi:10.1109/COMST.2021.3065907).
Luong, Thien V, Zhang, Xiaoyu, Xiang, Luping, Hoang, Minh Tiep, Xu, Chao, Petropoulos, Periklis and Hanzo, Lajos (2021) Deep learning-aided optical IM/DD OFDM approaches the throughput of RF-OFDM. IEEE Journal on Selected Areas in Communications, 40 (1), 212-226. (doi:10.1109/JSAC.2021.3126080).
Zhang, Xiaoyu, Singh, Ravinder, Farmer, James, Faulkner, Grahame, O'Brien, Dominic, Petropoulos, Periklis and Hanzo, Lajos (2021) Experimental characterization of turbo-coded 20 Gbps fiber-wireless-fiber optical links. IEEE Access, 9, 112726-112732, [9509027]. (doi:10.1109/ACCESS.2021.3103317).
Zhang, Xiaoyu, Luong, Thien V, Petropoulos, Periklis and Hanzo, Lajos (2022) Machine-learning-aided optical OFDM for intensity modulated direct detection. Journal of Lightwave Technology, 40 (8), 2357-2369. (doi:10.1109/JLT.2022.3141222).
Liu, Haochen (2022) Dataset supporting the article - Deep Learning Assisted Adaptive Index Modulation for mmWave Communications with Channel Estimation. University of Southampton doi:10.5258/SOTON/D2250 [Dataset]
Liu, Haochen, Zhang, Yaoyuan, Zhang, Xiaoyu, El-Hajjar, Mohammed and Yang, Lie-Liang (2022) Deep learning assisted adaptive index modulation for mmWave communications with channel estimation. IEEE Transactions on Vehicular Technology. (doi:10.1109/TVT.2022.3181825).
Telephone: +44 (0) 23 8059 9317
Email: xy.zhang@soton.ac.uk
Thorburn, Robert, Paci, Federica, Sassone, Vladimiro and Stalla-Bourdillon, Sophie (2021) Connecting regulatory requirements to audit outcomes: a model-driven approach to auditable compliance. In Companion Proceedings - 24th International Conference on Model-Driven Engineering Languages and Systems, MODELS-C 2021. Institute of Electrical and Electronics Engineers Inc. pp. 641-642 . (doi:10.1109/MODELS-C53483.2021.00100).
PhD Student in Web Science.
Project Title: AI for Future Society Studentship: Ethics of AI and Data Science. Sponsored and supported by the Alan Turing Institute and DSTL.
Eryn is a PhD Student of the Web Science Institute, researching ethics in AI applications. She completed an integrated MA in Philosophy at the University of Edinburgh, focusing on AI ethics and environmental ethics. She went on to study for a post graduated MSc in Artificial Intelligence and Applications at Strathclyde University, applying ethical decision making in autonomous system development. Her research is now focusing on including ethics into AI research and development for use in the military.
Artificial Intelligence Ethics, Autonomous Systems, XAI, XAIP, Environmental Ethics
Email: er1u21@soton.ac.uk
Using solar power to address poverty alleviation in low-middle income countries is key to tackling the worst effects of climate change. Yazan will lead a team tackling poverty alleviation with solar power in low-middle income countries. For solar energy to become a more important part of the renewable energy mix, it is essential to understand the reliability of modules. This Ph.D. project focuses on:
Yazan is a Ph.D. Student in Electronic & Electrical Engineering at the University of Southampton. His research focuses on the Optimisation of Bifacial and Tandem Photovoltaic Modules through Outdoor Testing. Before enrolling at Southampton, he was an Electrical Power Engineering undergraduate at Newcastle University in the United Kingdom. He achieved a first-class grade in every module and thus, graduating with a high First Class Hons degree. As a result, he was awarded the Nominated Student Prize and Student Performance Prize. During his time at Newcastle University, Yazan was the Lead Course Representative for Electrical and Electronic Engineering Undergraduates; where he was nominated as the UG Course Rep of the Year Award.
Outside of academia, Yazan did dedicate his time-off to continuously developing his interpersonal skills. Yazan did work as an Electronic Design Automation (EDA) intern at Pulsic inc. for a 4 month period in 2020; his role was to help software engineers to analyse the performance of the revolutionary Animate Preview software across a wide range of data. He was responsible for analysing circuits to discern the desired results and report back on how well the software had performed relative to these requirements. Moreover, he was a Photovoltaic Design Engineering Intern at the award-winning firm Modern Arabia for Solar Energy (MASE); where he experienced first-hand designing, building, operating, and maintaining retail as well as utility-scale solar PV plants in the Hashemite Kingdom of Jordan.
Yazan joined Dr. Tasmiat Rahman's team as a Ph.D. researcher in September 2021 following his award of the "Electronic and Computer Science Research Studentship within the Faculty of Engineering and Physical Sciences."
Project Title: “Optimising Bifacial Tracking Systems for High Latitude and Diffuse Climate Applications through Outdoor Testing.”
This Ph.D. project focuses on modelling emerging photovoltaic module technologies, including bifacial modules. A combination of outdoor testing stands and state-of-the-art laboratories and characterisation facilities will be used for experimental validation. It will be necessary to model these modules in order to determine the optimal configuration of module components and peripherals based on environmental factors such as sunlight (angular and spectral distribution) and weather conditions (temperature, humidity, wind, etc.). In addition, standards for bifacial and tracking technologies will be thoroughly explored, with the aim of contributing to international standards for the wide PV community.
Please contact Yazan for possible collaborations with his Supervisory team via email.
Telephone: +44 (0) 23 8059 447753990522
Email: Y.Musleh@soton.ac.uk
I am a computer scientist with expertise in Machine learning, Computer Vision and Natural Language Processing. I received my masters degree in Computer Science from the National University of Computer and Emerging Sciences, Islamabad, in 2009 and earned doctorate in Computer Science from the University of Southampton, Southampton, in 2014. Soon after completing my Phd, I worked as a Data Scientist with the Horizon Research Institute in University of Nottingham, and then as a Research Scientist at Cortexica Vision Systems, Imperial College of London, U.K. My first industrial assignment as a Research Associate in Horizon research institute was on the exploration of identifying customers’ behavioural trends via topic models, whereas my second industrial assignment as a Research Scientist in Cortexica Vision Systems included the deployment of deep models for improving image retrieval performance offered by the retailers (ASOS and Zalando). Both the jobs gave me an exposure to work on big multimedia data problems using deep learning models in the industry. This also paved my way to initiate research on natural language processing (NLP) tasks, as topic models tend to mine abstract themes in a collection of documents. I further pursued my research in this direction on joining academia as an Assistant Professor of Computer Science.
My doctoral research highlighted the possibility of deploying deep learning models for improving the classification performance of state of the art kernel methods like support vector machines. The research showed how such a hybrid approach can combine the best of both the paradigms for computer vision problems. The research experience gained from my doctoral program cultivated and nurtured lifelong skills of working on daunting ideas that can create a difference. From the last six years, I have extended this research by focussing on developing Fisher kernel methods that can bridge the gap between the two popular frameworks: Deep learning and Kernel methods. This research has helped me in winning several national and international research grants from the industry and academia. I am recipient of a Startup Research Grant, a National Grassroots ICT Research Initiative Fund, a National ICT Research and Development Grant, and an have received the Best Paper Award at ICPRAM, in 2017.
I have also worked as a technical reviewer of the following journals, conferences and organisations: IEEE Transactions on Neural Networks, IEEE Access, IET Electronics letters, Neural Processing letters, Journal of Information Sciences. Journal of Pattern Recognition, IGNITE National ICT R&D, Pakistan, IEEE International Conference on Emerging Technologies (ICET) and IEEE International Conference on Industrial and Information Systems (ICIIS).
My current research interests include deep learning methods for graphs in NLP. Im also interested in self-supervised learning methods for deep models to develop intelligent chat bots. Such learning techniques are useful for online lifelong and continual learning, where most of the encountered real world data is unlabelled. Zero shot and one shot learning techniques are also of significant interest to me in this regard.
I have experience of teaching in the Higher Education sector both in the UK and abroad in Pakistan. This experience has enriched my knowledge of cultural and societal differences, crucial elements to promote diversity in a learning environment. Under my recent occupation as an Assistant Professor at the Institute of management Sciences, I have served various roles as a course instructor and manager industry academia linkages. As an inclusive practitioner the new courses I introduced in campus are: Data Science, Multimedia Databases and Machine learning. Besides delivering lectures, I was actively involved in curriculum development and have applied various learning strategies to engage all students in an effective teaching and learning environment and not focus on a specific group or diversity dimension.
Azim, Tayyaba, Loitongbam, Gyanendro Singh and Middleton, Stuart (2022) Detecting moments of shange and suicidal risks in longitudinal user texts using multi-task learning. Workshop on Computational Linguistics and Clinical Psychology: North American Chapter of the Association for Computational Linguistics 2022 (NAACL-2022), , Seattle, United States. 15 Jul 2022. (In Press)