Biography

Research

Biography

Timothy Constandinou originally trained in Electronic Engineering at Imperial College London. He is currently Deputy Director of the Centre for Bio-Inspired Technology and leads the Next Generation Neural Interfaces (NGNI) lab. His group utilises integrated circuit and microsystem technologies to create new research tools for neuroscience and neuroprosthetic devices. He has projects on brain machine interfaces, epilepsy, sleep, as well as tackling fundamental challenges in electronic and implantable technology. Within IEEE he serves on the CAS Society Board of Governors, BRAIN Initiative Steering Committee and BioCAS/Sensory Systems Technical Committees. He co-chairs the Royal Society emerging technologies group in Neural Interface Ecosystems.

Research

The key overarching aim is to utilise the capability of (currently) mainstream CMOS microelectronics to enable efficient and effective ReRAM/CMOS integration. This technology platform will then provide new opportunities for integrated circuit design by exploiting the inclusion of new nano-scale memory primitives. Our research here is firstly supporting the technology integration through customisation of electronic design automation (EDA) CAD to include ReRAM capability within design tools (e.g. modelling, schematic entry, simulation, layout design, physical verification). These will then be used to design basic building blocks that contain ReRAM devices (e.g. memory elements, read/write instrumentation, readout circuits) in addition to macros and tools for generating memory arrays. The availability of an end-to-end design methodology will then allow us to exploit the technology for new circuits and applications. From a circuit perspective we will investigate continuous-time discrete value processing based on oscillator structures or level-crossing converters. This allows “analogue” processing with high dynamic range in a highly integrated manner. From an applications perspective, our work will target two specific areas: novel research tools for neuroscience, and active implantable medical device. Here, the availability of “above circuit”, back-end integrated ReRAM will enable hybrid/distributed processing/memory architectures, providing an order of magnitude improvement in both power consumption and integration density.

Biography

Prof. Piotr Dudek is is a Professor of Circuits and Systems in the School of Electrical and Electronic Engineering, The University of Manchester, leading the Microelectronics Design Lab.  

He received his mgr inz degree from the Technical University of Gdansk, Poland, and the MSc and PhD degrees from the University of Manchester Institute of Science and Technology (UMIST) in 1996 and 2000 respectively. He worked as a Research Associate, and since 2002 as a Lecturer, at UMIST/The University of Manchester. He was a Visiting Associate Professor in the Department of Electronic and Computer Engineering at the Hong Kong University of Science and Technology during 2008/09, Visiting Professor in the Faculty of Electronics, Telecommunications and Informatics at the Gdansk University of Technology in 2015, Royal Academy of Engineering/Leverhulme Trust Senior Research Fellow in 2016/17, and a visiting researcher at the Sorbonne University in 2017/18.

He is a Senior Member of the Institute of Electrical and Electronic Engineers (IEEE) and a member of IEEE Circuits and Systems Society Technical Committees on Neural Systems, and on Cellular Neural Networks and Array Processing.  He was the Chair of the IEEE CAS Technical Committee on Sensory Systems (2015-17). He has been a member of Scientific Committees, Track Chair or Session Chair at many international conferences. He is an Associate Editor for IEEE Transactions on Circuits and Systems II and Review Editor for Frontiers in Neuroscience and an active reviewer for many journals and funding agencies. His work received several Best Paper and Best Demo awards at international conferences (ISCAS, IJCNN, CNNA, ICDSC), and he has given numerous keynote and invited talks, and examined PhD theses worldwide.

Biography

Dirk Koch was promoted to Professor for Novel Computing Technologies at Heidelberg University in April 2022, however he is still affiliated to the University of Manchester. His group works on run-time reconfigurable systems based on FPGAs ranging from embedded systems to HPC. He developed techniques and tools for self-adaptive distributed embedded control systems based on FPGAs. Current research projects include hardware security database acceleration using FPGAs-based stream processing, HPC and exascale computing, as well as reconfigurable instruction set extensions for CPUs. Furthermore, in the FORTE project he is exploring how memristors can be used for building new kinds of analogue, digital and mixed-signal reconfigurable devices.

Dirk is author of the book "Partial Reconfiguration on FPGAs" and a co-editor of the book "FPGAs for Software Programmers" and his group is developing and maintaining the GoAhead framework that provides unique capabilities for building run-time reconfigurable systems. Recent awards include the FPL Community Award (2016) and the FPL most influential paper award (2015). 

FPGA architectures, Partial Runtime Reconfiguration, Reconfigurable system design, Tool & design flow development for implementing reconfigurable systems are only a few of his research interests. His specialities are deep low level FPGA expertise and hardware design (CPUs, network routers, SoCs, etc.)

Biography

Research

Biography

Alexantrou Serb graduated from Imperial college in 2009 as a biomedical engineer and later obtained his PhD from Imperial college in 2013 in electronics engineering. Since then he has been a research fellow in Prof. Prodromakis' group, working on memristors technology characterisation and application development. His research interests include circuit design, computational neuroscience and biology-machine interfaces. He was appointed Reader at Univ of Edinburgh in May 2022.

Research

One of the greatest challenges of current research is how to embody the level of intelligence found in the brain into a physical computer that operates with the energy efficiency of the brain. To that end, algorithmics, computer architecture design, nanotechnology and ultimately also bio-interfacing must work together, as no isolated approach can deliver this vision. Throughout project FORTE this researcher will be involved in: 1) developing new applications enabled by enmeshing memristors into existing electronics technologies and 2) understanding how the availability of memristive technologies can unlock new capabilities in artificial intelligence systems.

The applications developed in this programme will span from simple, modular micro-circuits employing several memristors to larger scale systems utilising thousands of devices. Examples of the former would include reconfigurable logic (digital) and filter (analogue) blocks that can be aggregated into much larger computational systems much like Lego pieces can be used to construct complicated superstructures. Examples of the latter would include functional blocks that can carry out probabilistic inference, biosignal processing or neutral network-type inference.

The algorithmics part of the research is oriented towards the 'problem of multiplication': multiplication is expensive to perform accurately in hardware. Memristive technologies, however, offer an opportunity to implement not only multiplication, but other basic mathematical operations such as scalar matching in hardware at very low energy. Furthermore, reducing energy budgets for such operations opens the way towards more powerful, more intelligent AI.

Dr Shiwei Wang is a Reader in the Centre for Electronics Frontiers (CEF), School of Engineering at the University of Edinburgh. He received his Bachelor degree in Electronic Engineering (Outstanding Honor) from Zhejiang University, China in 2010 and PhD degree in Microelectronics from University of Edinburgh, UK in 2014. Following his PhD research, he was with SIAT, Chinese Academy of Sciences, China as a Research Assistant Professor before moving to IMEC, Belgium where he worked as a Senior Researcher till December 2020. At IMEC he took technical lead in several projects to develop ultra-low-power integrated circuits for neural interfacing applications. His research at IMEC has led to innovative breakthroughs in high density neural probe and integrated brain machine interface technologies. He is a senior member of IEEE and has over 30 publications including premier journals and conferences such as Science, JSSC, TBCAS, ISSCC, VLSI, IEDM, etc.

He has main research expertise on analogue & mixed signal integrated circuits, with particular interest in circuits for AI, biomedical, implantable/wearable, brain machine interface, sensor instrumentation applications. 

Biography

Spyros obtained his Applied Physics diploma in 2009 and his MSc in Microelectronics and Nanotechnology in 2011, both from the National Technical University of Athens (NTUA). In 2015 he received his PhD from the Department of Physics, NTUA for his work on the effects of infrared laser annealing in the electrical characteristics of silicon and germanium. He joined the University of Southampton, UK in 2016 and transferred to Edinburgh in May 2022. 

Research

Spyros is currently working on the fabrication, characterisation and application of metal oxide memristive devices.

Biography

Sachin Maheshwari is a Research Associate at the Centre for Electronics Frontiers in the School of Engineering at the University of Edinburgh, Scotland. Prior to that, he was a Research Fellow in the Department of Electronics and Computer Science at the University of Southampton. He did his PhD in the Applied DSP and VLSI Research Group at the University of Westminster, London, UK. His doctoral thesis was focused on the Adiabatic Approach for Low-Power Passive NFC systems. He did his Master of Engineering Degree in Microelectronics from Birla Institute of Technology and Science (BITS), Pilani, India and Bachelor of Technology Degree in Electrical and Electronics Engineering from ICFAI Tech, Hyderabad, India. In the past, he was also a Lecturer in the EEE Department at BITS Pilani for over 4 years. 

Research 

His research interests include Artificial Neural Networks and Neuromorphic Computing, across energy recovery logic (adiabatic technique) and emerging technology (RRAM) for developing brain-inspired energy-efficient systems. 

Biography

Andrea received his B.Eng. in Electrical and Electronic Engineering in 2016 at the University of Malta, with a particular focus on embedded systems. He furthered his studies with an MSc in Analogue and Digital Integrated Circuit Design at Imperial College London, developing a data and power delivery system for wired implantable devices, as part of his thesis. Andrea then joined Science and Technology Facilities Council (STFC) as a CMOS Sensor Design Engineer within the CMOS Sensor Design group. As of August 2020, he joined the Next Generation Neural Interfaces (NGNI) lab and the Centre for Bio-Inspired Technology (CBIT) at Imperial College London.

Research Interests

His work focused on the design and testing of CMOS image sensors including both pixel and periphery circuit design. 

Biography:

Jing received his Bachelor of Science degree from HKBU in 2011. Then he completed his Master of Engineering in 2013 and PhD in 2019 at RMIT University, Australia. He is currently working as a research associate at Department of Computer Science, The University of Manchester.

Research Interests:

The current research is focusing on the development of memristor-based FPGA architecture. His research interest includes FPGA design, embedded systems and asynchronous logic.

Biography

Peilong Feng is a postdoctoral researcher in Next Generation Neural Interfaces Lab at Imperial College London, London, UK. He received his BEng degree from the Henan Polytechnic University, China, in 2011, and his first MSc degree with distinction from the University of Southampton, UK, in 2012. Then he obtained his second MSc degree with distinction in 2015 and his PhD degree in 2020 from Imperial College London, London, UK.

Research

His research interests include RFIC for wireless power transfer and data communication and biomedical embedded system design

Biography

Jianing Chen received a B.Eng.(Hons) degree in automatic control and systems engineering from the University of Sheffield, UK, in 2010, and completed his Ph.D. degree in systems and control engineering at the same institution, in 2015.

At present, he is working at the Micro-eletronics Design Lab, the University of Manchester.

Research Interests

His research interests lie in computer vision, self-organizing systems, and computational intelligence.

Jiawei Shen received his MSc Analogue and Digital Integrated Circuit Design from Imperial College London in 2018 and BEng. Electronic Engineering from the University of Nottingham. Jiawei joined Circuits and Systems (CAS) research group in 2019 as research assistant and part-time PhD.

Research

The primary researches of Jiawei are the analogue and RF circuits that utilises memristors.

Biography

Chaohan received his MSc Analogue and Digital Integrated Circuit Design from Imperial College London in 2019 and BEng. Electrical Engineering from the McGill University, Canada, in 2017. Chaohan joined Circuits and Systems (CAS) research group in 2020 as a full-time PhD.

Research Interests

The primary researches of Chaohan are the Multi-bit Memory based on memristor crossbar array.

Biography

Georgios received his M.Eng. degree in electrical and computer engineering (ECE) from the Democritus University of Thrace (DUTh), Greece, in 2015, and his M.Sc. degree in ECE from DUTh, Greece, in 2017. He has pursued his Ph.D. studies at University of Southampton in Electronic Materials & Devices research group, working towards the implementation of reconfigurable hybrid CMOS/memristor circuits, systems and computer architectures and has since graduated and secured a position as Research Associate for in-memory computing hardware paradigms. 

Research

Georgios currently participates in the research of novel nano-electronic circuits and systems design for reconfigurable mixed-signal CMOS/memristor computer architectures towards developing a post-von-Neumann computing paradigm. 

Chris holds a PhD in and has secured a position as Research Associate in Graph Database Accelerators. He is specialising in neuromorphic engineering. His aim is to study and exploit the physical properties of memristive devices and develop novel applications for emulating synaptic memory consolidation.

Biography

Jiaqi received her Bachelor of Science in Microelectronic Science and Engineering from Shenzhen University, China, in 2017. Then she obtained her Master of Science in Microelectronic Systems Design from University of Southampton, in 2018. She pursued her PhD in Electronic Materials & Devices Research Group, University of Southampton.

Research Interests

She is working towards the memristor-based analogue & mixed-signal integrated circuit (IC) design. In neural recording system, we intend to design a front-end system outputting directly a digital, back-end processed waveform corresponding to neural spikes and demonstrate extremely low power dissipation in the process. The front-end contains an integrating amplifier and a dynamic latch comparator (DLC). Instead of purely amplifying the minute signal, we opt for integrating the micron-volt level signal. The integration process not only filters out noise, but also provides amplification. With memristors implanted along the differential current path, the offset can be tuneable precisely, making the systems operate with power efficiency and high precision. 

Biography

Patrick obtained a Masters Degree in Electrical and Electronic Engineering from Imperial College London in 2018. He joined the University of Southampton to study for a Doctorate in 2019 and transferred to Edinburgh in early 2023. He has successfully completed his PhD and secured a post as Research Associate with the School of Engineering, University of Edinburgh. 

Research

Patrick's research focuses on the measurement and testing of electronic devices, supporting the research group through the design of test hardware and instrumentation.

Biography

Yihan Pan received her B.Eng. degree in electronic engineering from the University of Manchester, Manchester, U.K., in 2018 and her M.Sc. degree in analogue and digital integrated circuit design from Imperial College London, London, U.K., in 2019. She is currently pursuing a Ph.D. degree in the Centre for Electronics Frontiers at the University of Edinburgh.

Research Interests

Yihan's research interests include RRAM-based content addressable memory architectures and hardware topologies for data processing.

Grahame’s research focuses on designing novel Compute-In-Memory architectures using novel devices, to address the von Neumann bottleneck. After graduating from the University of Surrey in 1984, he accumulated four decades of experience in semiconductor IC design, having held positions within Philips, Cypress, Semtech, Atmel, vivaMOS and Nordson.

Vasileios is studying the capacitive memory effects that appear in certain memristor configurations. His goal is to create variable capacitors without the need for lengthy fabrication procedures and/or moving parts.

Biography

Research Interests

Biography

Research Interests

Zhaoguang Si received his Msc Analogue and Digital Integrated Circuit Design from Imperial College London in 2021 and BEng. Electrical and Electronic Engineering (Electronics) from University of Liverpool in 2020. Zhaoguang joined Circuits and Systems (CAS) research group in 2022 as a full-time PhD candidate. 

Research Interests  Analogue applications of the memristor, conventional and memristor-assisted data converters. 

Abdulaziz Alshaya received his B.S degree in Electrical Engineering from Qassim University, Qassim, Saudi Arabia in 2010, and M.S. degrees in Electrical Engineering from Loyola Marymount University, United States, in 2014. He is a senior researcher at King Abdulaziz City for Science and Technology(KACST), Saudi Arabia, from 2014-present. He is now a PhD candidate at Imperial College London. Abdulaziz joined Circuits and Systems (CAS) research group in 2020 as a full-time PhD student.

Research Interests: Analogue and mixed-signal integrated circuits involving memristos for neurotrophic computing and memory application. 

Xiongfei received a B.Eng degree in optoelectronic information science and engineering from UESTC, Chengdu, China, and a M.Sc degree in analogue and digital integrated circuit design from Imperial College London, London, U.K. He is now a Ph.D. candidate researching ultra-low power integrated circuits for in-sensor and near-sensor computing in neuromorphic electronics and neural interfaces.