Research Group: µSystems

We design and develop core circuits, algorithms, and microsystems with low to zero energy footprints. We are developing new mathematical and computational models and paradigms. We are re-evaluating fundamental physics. We explore the challenges of fabrication processes.

We perform implementation of microelectronics into physical CMOS chips. We design embedded systems using microcontroller units and programmable logic devices such as FPGAs. We are able to utilise these in the medical and artificial intelligence domains.

We have strong links with the electronics industry, as well as academic colleagues across the UK and internationally. These links are crucial. They create an industrial-academic ecosystem for promulgating our research outputs.

We provide exciting research projects for undergraduate students studying electronic and computer engineering. Our MSc programmes provide training in embedded systems, microelectronics and autonomous systems. We recruit and train PhD students in various disciplines fitting within our broad objectives.

• Prof Alex Yakovlev

Alex is Professor of Computer Systems Design at the School of Engineering, Newcastle University. He has worked at the University since 1991. He is the founder of Asynchronous Systems Lab, with 60 PhD alumni. He is an international pioneer of asynchronous circuit design and design automation. He was elected to Fellow of IET in 2015, Fellow of IEEE in 2016, and Fellow RAEng in 2017.

In 2011-2013 he was a Dream Fellow of EPSRC when he introduced the idea of energy-modulated computing. In 2018, he was awarded an IET Achievement Medal for contributions to electronic engineering.

Recently, Alex has been exploring computing at the speed of light and using clocks to measure data rather than a synchronisation tool.

• Dr Patrick Degenaar

Patrick is a professor in neuroprosthetics. He is the team leader of the neuroprosthetics lab at Newcastle University. He set up the lab in 2010. He graduated with a first class (Hons) degree in applied physics and an MRes Degree in surface science. After a short period as a medical engineering technician, he went on study a PhD at the Japan Advanced Institute of Science and Technology. A period in the software industry preceded a return to academia as a post-doctoral researcher at Imperial College London. He started becoming interested in optogenetics. He received an RCUK fellowship and lectureship in 2005. This allows him to explore the new technology for applications in retinal prosthesis.

Patrick received promotion to senior lecturer at ICL in 2008. In 2010, he moved to Newcastle to work with the Institute of Neuroscience. He became a professor in 2019. Here in Newcastle, he coordinated the Eur2.1M OptoNeuro FP7 project to develop an optogenetic retinal prosthesis. Since then, he has been the engineering workpackage leader on the CANDO project. The project is developing an optogenetic prosthesis to negate seizures in epileptic patients.

We design energy-driven and Real-Power computing for future autonomous electronic systems.

We develop new circuits and systems design methods for artificial intelligence. Our methods include energy frugality and autonomy objectives.

We combine industrially fabricated MEMS and CMOS architectures into advanced implantable microsystems. These are used for neuroprosthetics and electroceuticals.

Analogue-Mixed Signal Design Automation and Asynchronous-Analogue Co-design for complex electronics. We help to improve design productivity for future heterogeneous electronics in their trillions.

Semiconductor scaling continues, with an increasing degree of integration. At the same time, there are increasing limitations on and unpredictability of power and energy.

Thus, computation systems need more and more timing flexibility and heterogeneity. This is the case even within individual chips.

The µSystems group has a long history of successful research. Our research ranges from theoretical methods to practical implementation. We investigate all aspects of system timing and asynchrony. Our research continues with projects in:

• synchronization
• SoCs and NoCs
• GALS and
• asynchronous systems

Energy and power sources are often unreliable and unpredictable. This is especially so for embedded systems using harvested energy. How to best deliver energy to computation units and how the units can best make use of this energy become critical research problems.

Many of our current projects focus on answering these questions by:

• increasing the system survival zone
• creating methods for near-threshold computing system design
• enhancing the variation tolerance of circuits
• developing efficient on-chip power delivery and conditioning including control and sensing techniques.

Whole genome sequencing (WGS) is a Big Data application. It is used by a variety of applications in the healthcare, agriculture and pharmaceutical sectors.

Current computational WGS has major limitations. These can inhibit their widespread usage. They include low throughput and very high energy consumption.

We are designing new hardware/software co-design methods for empowering low-cost embedded genomics. We are working with genomics researchers at Newcastle University. We are designing algorithms and runtime systems to exploit computation and memory resources. At the same time, they also maintain low energy footprints.

ICT systems are more and more bound in their capabilities and operations by the energy available to them. Energy driven computing is a new paradigm which states that computation should be a result of energy supply (computing on energy).

We are one of the initiators of this paradigm. It is described in detail in Microelectronics for autonomy and survival (PDF: 175KB). The article identifies applications of this type of computing and the methods with which it can be designed.

‌The µSystems group is traditionally very closely connected to the School of Computing. We continue to carry out research on the edge between computer science and electronic engineering.

We are currently engaged in research on powerful modelling methods. These support the design of computation units for use in environments where power and energy supplies are uncertain.

Andrey Mokhov is leading the research.

Computing and electronics could generate considerable new ways of helping society. A crucial technological area is the potential use of computing in real-time health monitoring and care. An exciting aspect is the interfacing of silicon-based computation devices with biological neurons.

‌Power and energy availability affects system performance and survivability. It also impacts system reliability. There is a complex, but poorly understood, interplay between:

• power supply (related to voltage)
• system computation throughput
• reliability
• how fast the circuits age and degrade.

The µSystems group is applying its considerable expertise in related areas to new research which aims to:

• improve the understanding of these complex relationships
• develop methods to improve system designs based on such discoveries.

Electronic applications enabling pervasive artificial intelligence (AI) have unique and conflicting challenges. These include extreme energy efficiency, accuracy and continuous learning. We are developing a new generation of AI hardware architecture to address these challenges.

We have built our architecture on the principle of learning automata. Mikhail Tsetlin proposed the theory of learning automata in the 1960s. It has long been a basis for non-linear control systems. It allows for formulation of machine learning using propositional logic and game theory.

We are working with our collaborators at the University of Agder, Norway, led by Professor Ole-Christoffer Granmo. Together, we are enabling powerful new AI applications through our hardware innovations.

The µSystems group includes the Neuro-prosthesis lab. Its primary interest is in developing neural stimulators and state of the art implantable systems. The new field of optogenetic neuroprosthesis uses this technology. Our research in this area will generate new understanding in core neurobiology. We are using neuro-inspired designs to make better circuits and systems.

For more information, please see the Neuro-prosthesis lab.

The µSystems group and the Institute of Neuroscience are working together. They re providing an enabling technology to support neuroscientists. This technology will help them in their research into how the brain works. In the long term, this research will lead to improved treatment of nervous system injuries such as strokes and spinal cord injuries.

We are developing a radio telemetry system to transmit multiple muscle or nerve signals from a device which is implanted within the body. Radio frequency induction provides the power from an external coil placed over the skin. This avoids the need for battery replacement.

Check out our technical memos and reports, and have a look at our gallery of chips.

We explore rigorous methods in designing systems for power, performance, reliability and security.

• Working with the School of Computing

We are investigating controlling abnormal network dynamics using optogenetics.

• Working with the Medical School

• Working with Newcastle Institute of Genetic Medicine

• Working with E-Therapeutics

• Working with Microsoft Research

• Working with Intel

• Working with TU Eindhoven and RWTH Aachen

The Royal Academy of Engineering funds a Visiting Professorship for Dr Shidhartha Das from Arm. Dr Das is a Senior Principal Research Engineer in the Devices, Circuits, and Systems Group in Arm Research, based in Cambridge, UK.

Shidhartha is one of the key inventors at Arm. He has more than 35 US granted patents, several national and international awards, and many major publications. He teaches low-power processor and artificial intelligence systems design.

Our group was commended by the REF panel as producing best research outputs. We contributed to one of the best University Research Impact case studies: Powering Industry with Causality Modelling.

Our students take part in and win design awards from national and international competitions. These are hosted by professional institutions, such as IEEE, IET and ACM, and by industry.

• The Microsystems team of PhD students won the Xilinx Open Hardware 2018 award with FANTASI (FAst NeTwork Analysis in SIlicon)
• Tousif Sheikh Rahman won an IET Final Year Student Project Competition in 2019 with his presentation Implementation of whole genome sequencing algorithms

Our researchers regularly present at prestigious conferences around the world.

• IET Computers & Digital Techniques Premium Award
• Dahir N, Mak T, Al-Dujaily R, Missailidis P, Yakovlev A. Highly adaptive and deadlock-free routing for three-dimensional networks-on-chip. In: IET Computers & Digital Techniques 2013, 7(6) 255-263
• Graeme M. Bragg, Charles Leech , Domenico Balsamo , James J. Davis , Eduardo Wachter , Geoff V. Merrett , George A. Constantinides and Bashir M. Al-Hashimi. An Application- and Platform-agnostic Control and Monitoring Framework for Multicore Systems. 3rd International Conference on Pervasive and Embedded Computing, Porto Portugal, 29-31 July 2018 . Best Paper Award. 
• Abeyrathna, K. Darshana, Ole-Christoffer Granmo, Rishad Shafik, Alex Yakovlev, Adrian Wheeldon, Jie Lei, and Morten Goodwin. “A Novel Multi-step Finite-State Automaton for Arbitrarily Deterministic Tsetlin Machine Learning.” In International Conference on Innovative Techniques and applications of Artificial Intelligence, pp. 108-122, Springer, 2020. Best Paper Award. 
• Jie Lei, Adrian Wheeldon, Rishad Shafik, Alex Yakovlev and Ole-Christoffer Granmo, From Arithmetic to Logic Based AI: a Comparative Analysis of Neural Networks and Tsetlin Machine, 27th IEEE International Conference on Electronics Circuits and Systems, 2020. Best Poster Award. 

We often have exciting opportunities available to join our team. We regularly recruit talented new students and researchers. Check Newcastle University job vacancies for current opportunities.

We welcome applications for those with fellowship funding. We can provide mentorship, office space and cutting edge lab facilities, as well as state of the art servers operating the latest CAD design tools.

Contact Prof Alex Yakovlev or Prof Patrick Degenaar.

We produce high-quality PhD graduates. Most go on to successful academic and industrial careers, in the UK, Europe, Asia and the Americas.

The area of µSystems is experiencing continuous worldwide growth. The skills involved in obtaining a PhD degree in this rapidly growing area is extremely useful. This is the case not only for people who intend to follow a career within microelectronics, but also elsewhere.

Our PhD graduates hold senior positions in diverse fields, from computing science to rail transport systems.

You will make contributions to and attend high-quality international conferences. You will collaborate with colleagues and external experts. You will publish papers in recognised research journals.

The group has a highly connected environment and friendly atmosphere. Students on different projects work with one another:

• formally through our regular seminars, such as the ASL series, which is co-hosted with the School of Computing
• informally through daily contacts in the office and recreation spaces around the School

Our students include mathematicians, programmers, circuit designers, biologists, and others from diverse backgrounds.

Computing systems, especially hardware, are becoming more and more energy and power constrained. You will investigate the relationship between energy and power on one hand and computation on the other. You’ll also work on:

• energy modulated computing
• low power electronics
• energy harvesting
• storage and distribution on chip

Asynchronous techniques do not rely on a consistent global clock. Thus, they offer solutions to many of the current and future problems encountered in computing.

You will explore and develop novel solutions for asynchronous circuits and systems . You will work at all levels of abstraction, from theoretical studies and algorithmic development to design of specific circuit elements.

Computing systems are increasingly limited by the utilisation wall. This forces the use of dynamic feedback control at the smallest granularity, which is on-chip circuits.

You will investigate issues related to building on-chip dynamic control of computation. Your investigations will be in relation to variations in the environment and the circuits. You will develop:

• novel control algorithms
• control data communication solutions
• the hardware needed to deliver these solutions

We can control computation dynamically on-chip. To do this requires sensing of the physical parameters related to the environment and circuit conditions.

On-chip sensing of these parameters is non-trivial. Reliable references are usually missing and the sensors themselves are based on the same kind of circuit as the system.

You will develop novel sensing techniques to overcome these problems.

Current system-level strategies to deal with power variability in the environment are multi-modal. For instance, a laptop may have a number of operating modes. These may include mains plugged in, on battery with networking, low activity, sleep, and so on.

You will work at the lowest hardware level to develop an entirely new paradigm. This will be based on multiple layers of circuits and functions targeting the ultimate survivability of computation.

Microelectronic systems are increasingly used in applications where security and privacy are essential.

As semiconductor technology moves into the nanoscale range, variability increases. The properties of hardware-level security change with it, including possible uses and nature of attacks.

You will investigate various aspects of nanoscale security due to variability, including:

• theoretical foundations
• attacks and countermeasures
• approaches that can harness the effects of variability for designed-in security
• security-enabling technologies for use in silicon chips

Biomedical systems such as heart pacemakers and visual prostheses need advanced electronic processing architectures.

You will develop digital/analogue FPGA/CMOS designs to mimic key computational centres in the eye and brain. Successful outcomes will be translated to retinal and visual prostheses.

This is an opportunity to work on implantable optoelectronic neural stimulators and sensors.

You will explore implantable structures which link micro-optoelectronics stimulator and sensing systems. Real time close loop systems connect biosensor inputs and neural stimulation. They have particular application to brain prostheses, motor neurone disease and visual prosthesis.

You should have at least a 2:1 honours degree (ideally a first class degree), or a combination of qualifications and/or experience equivalent to that level in a relevant discipline (typically in computer science, engineering, mathematics or in the physical sciences).

To apply for the open opportunities, discuss your potential interest with the relevant academic staff member.