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School of Electronics, Electrical Engineering and Computer Science

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Dr Nikolaos Athanasopoulos No more applications being accepted Competition Funded PhD Project (Students Worldwide)
Belfast United Kingdom Electrical Engineering

About the Project

Start Date: 1 October 2021

Supervisors: Dr Nikolaos Athanasopoulos and Dr Georgios Karakonstantis Industry 4.0 is a new emerging paradigm aiming at transforming the manufacturing processes by automating them through the use of autonomous robots and smart edge/cloud computing infrastructure. The operation of robots relies on a range of computationally intensive algorithms from control theory to computer vision and machine learning for autonomously moving, deciding and performing critical operations in real time. Most of these operations need to be performed under stringent power envelopes and dynamically changing environmental conditions that include varying levels of heat, electromagnetism, radiation and humidity. Such conditions make the delicate electronic processing and storage circuits prone to intermittent failures, which in turn threaten the correct functionality of robots and eventually the reliable, non-disruptive and safe, accident-free operation of factories. The project brings together experts on low-power fault-tolerant systems, control theory and robotics and machine learning for digital manufacturing from Queen’s Electronics, Communications and Information Technology (ECIT) Global-Research-Institute and the Intelligent Autonomous Manufacturing Systems (i-AMS) Pioneer Research Programme. Active collaboration is planned also with researchers from the Bosch Center for Artificial Intelligence (BCAI) in Germany, with a possibility of short research visits. The student will join an award winning research team in Queen’s ECIT- GRI and the i-AMS centre taking advantage of the unique infrastructure on system design, characterization. The project is expected to result in several publications in top-tier international conferences and journals venues and the ideas will be disseminated through international networks of excellence and technical committees of which the supervisors are members and through a workshop at the last year that we aim at organizing in one of the relevant top-tier international conferences. Applicants should have a 1st or 2.1 honours degree (or equivalent) in Computer Science, Control Engineering, Applied Mathematics or similar. Students who have a 2.2 honours degree and a Master’s degree may also be considered, but the School reserves the right to shortlist for interview only those applicants who have demonstrated high academic attainment to date.

This project aims at addressing a truly interdisciplinary challenge by developing low cost adaptive mechanisms that enable the provably correct operation of robot tasks, specifically planning challenges in robotic manipulators. This will be achieved through algorithm-hardware co-design that allows the adaptation of kernels typically found in robots based on feedback from the underlying hardware. To enable this we will first study the impact of potential hardware failures on such kernels using Machine Learning based failure prediction models. Task scheduling mechanisms will then be developed giving priority to critical tasks, while meeting stringent power and performance requirements. We plan to also exploit the dynamic reduction of arithmetic precision, which we have recently shown can reduce the power consumption but also the number and impact of failures on applications.


The School of Electronics, Electrical Engineering and Computer Science (EEECS) aims to enhance the way we use technology in communication, data science, computing systems, cyber security, power electronics, intelligent control, and many related areas.

You’ll be part of a dynamic doctoral research environment and will study alongside students from over 40 countries worldwide; we supervise students undertaking research in key areas of electronics and electrical engineering, including: power electronics,robotics, wireless communications, cybersecurity and sensor-based systems. As part of a lively community of over 100 full-time and part-time research students you’ll have the opportunity to develop your research potential in a vibrant research community that prioritises the cross-fertilisation of ideas and innovation in the advancement of knowledge.

Within the School we have a number of specialist research centres including a Global Research Institute, the Institute of Electronics, Communications and Information Technology (ECIT) specialising in Cyber Security, Wireless Innovation and Data Science and scalable computing.

Many PhD studentships attract scholarships and top-up supplements. PhD programmes provide our students with the opportunity to acquire an extensive training in research techniques.

Funding Notes

The PC of the student will be provided by Queen’s ECIT-GRI . The latest ECIT cluster and QUB’s Kelvin machine will be used for executing the algorithms. Furthermore access to ECIT’s Cyber lab and the unique in house experimental setups and servers will be provided equipped with oven and thermal testbeds for performing system characterization under various environmental conditions. The student will have access to the Autonomous Systems Laboratory of the i-AMS (Intelligent Autonomous Manufacturing Systems) centre and the industrial robotic setups in Northern Ireland Technology Centre (e.g. KUKA LBR IIWA, Staubli TX2-90)
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