The University of Southampton

Email:
er1u21@soton.ac.uk

 

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.

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Artificial Intelligence Ethics, Autonomous Systems, XAI, XAIP, Environmental Ethics

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Telephone:
+447753990522
Email:
Y.Musleh@soton.ac.uk

 

https://twitter.com/yazanmusleh12
https://www.linkedin.com/in/yazanabbadi/

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:

  • The modeling of emerging Photovoltaic technologies, including bifacial modules and tracking under different algorithms.
  • Engineering outdoor testing stands for experimental validation as well as using Southampton’s state-of-the-art laboratories and characterisation facilities.
  • Constructing and developing solar insolation instruments that are strategically positioned for the best collection of irradiance for bifacial modules in high diffuse climates.
  • Contribute to the development of instrumentation standards and testing procedures for solar insolation measurement.

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."

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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.

  • PV for Developing Communities
  • Bifacial Modules
  • Cost-effectiveness & Feasibility of PV Systems 
  • Single Axis & Dual-Axis tracking of PV on a System Level

Please contact Yazan for possible collaborations with his Supervisory team via email.

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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.

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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.

Teaching

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.

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Email:
m.p.napari@soton.ac.uk

 

Mari received her BSc and MSc degrees in physics from University of Jyvaskyla, Finland, where she also did her PhD in the Accelerator Based Materials Research Group. Her work was focused on atomic layer deposition (ALD) of metal oxide thin films with a special interest in studying the effect of fundamental low-temperature plasma physics on the plasma-enhanced ALD. After finishing her PhD she moved to United Kingdom and joined the University of Cambridge, where she worked in the Device Materials Group, Department of Materials Science and Metallurgy, investigating oxide materials for CMOS devices, with focus on development of new processes for p-type semiconducting oxide thin films and thin film transistors. In September 2019 she joined the Electronic Devices and Materials Group in Southampton to work on memristors and RRAM, where her role includes development and characterisation of oxide materials and devices.

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Email:
f.m.simanjuntak@soton.ac.uk

 SMIEE MInstP

https://scholar.google.com/citations?user=n61uJa4AAAAJ&hl=en

Dr. Firman is a scientist at the School of Electronics & Computer Science, University of Southampton (UoS - UK). He received full scholarships for his M.Sc. in Mechanical Engineering and Ph.D. in Materials Science & Engineering from Taiwan top universities. He has been recently granted the prestigious Marie Skłodowska-Curie European Fellowship to run MENESIS project (Memristor-Enabled NEuromorphic System for Intelligence in Space) delivering cloud servers technology in the sky (satellites, space stations, interplanetary probes, etc). He is an expert in the synthesis and characterization of nanostructured materials, and his research interests are memristive and sensor technologies, as well as materials processing and analysis for advanced electronics. Prior to joining the UoS, he was with World Premier  – Advanced Institute for Materials Research, Tohoku University - Japan, where he pioneered the neutral ions irradiations technique to control the synaptic behaviour of memristor devices. He has published more than seventy peer-reviewed research articles and conference papers within the last seven years.  Currently, his work focuses on AI-hardware accelerators for space and nuclear applications.

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Research interests

Materials processing and analysis for advanced electronics; data/energy storage, sensors, neuromorphic computing, etc.

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Secretary of the Airsoft society at the University of Southampton, previously the president from 2018 to 2020

I have graduated from the University of Southampton in 2020 with a BSc in Computer Science and am currently a PhD candidate at the UKRI MINDS Centre for Doctoral Training at the University of Southampton.

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My research interests focus on explainable AI within reinforcement learning.

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Reinforcement learning, programming, explainable AI

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Email:
D.Georgiadou@soton.ac.uk

 PhD FHEA

Dimitra is UKRI Future Leaders Fellow leading the Organic and Flexible Nanoelectronics Lab within the Smart Electronic Materials and Systems (SEMS) Research Group at Electronics and Computer Science. She also serves as the Deputy Impact Champion and Outreach Officer in the UKRI Centre for Doctoral Training in Machine Intelligence for Nano- Electronic Devices and Systems (MINDS-CDT) at the University of Southampton. Previously she held a position as Post-Doctoral Industrial Fellow at the Department of Materials, Imperial College London (ICL), working on a Knowledge Transfer project with PragmatIC, a UK-SME developing flexible radiofrequency electronic devices enabling the Internet of Things. Before that she was awarded a Marie Skłodowska-Curie Fellowship, hosted within the Experimental Solid State Physics group at the Department of Physics (ICL), where she is still an Acedemic Visitor. She is also serving as Associate Editor in Frontiers in Nanotechnology (Nanodevices sector), and is member of the programme committee of InnoLAE conference (Innovations in Large Area Electronics), taking place annually in Cambridge, and of Flexible & Wearable Electronics subcommittee of IEEE EDTM 2022.

Dimitra earned her PhD in Chemical Engineering/Organic Electronics from the National Technical University of Athens (NTUA), Greece, while she holds a BSc in Chemical Engineering (majoring Materials Science) from the same University. She also holds a Master’s Degree (Honours) in Advanced Materials Science awarded jointly from the Technical University of Munich, Ludvig-Maximilians University of Munich and University of Augsburg in Germany. As a post-graduate, she gained industrial experience through internships in Procter & Gamble, Italy, and Schreiner Group, Germany.

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Research interests

Dimitra’s research interests involve the fabrication and optimisation of nanoscale opto/electronic devices by applying novel materials concepts, alternative patterning techniques and solution-based processes compatible with flexible substrates and printable electronics. During her PhD and first post-doc positions, she developed organic and inorganic materials-based thin films to act as interfacial layers in high performance Organic Light-Emitting Diodes (OLEDs) and Organic Photovoltaic Cells (OPVs). Then, she went on to explore the fabrication and characterisation of coplanar nanogap separated metal electrodes on rigid or flexible substrates using a high throughput, scalable, inexpensive technique, named adhesion lithography. Dimitra is currently interested in combining these coplanar electrodes with functional organic, inorganic and hybrid materials to develop advanced opto/electronic devices targeting high speed applications, such as high– and ultra-high frequency (HF & UHF) radio frequency diodes, high response speed photodetectors, fast switching light-emitting diodes and novel optoelectronic memristors operating as photonic artificial synapses.

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