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Large-scale photonic-electronic integration for next generation neuromorphic computing systems


   Institute of Photonics

  , Dr Javier Porte-Parera  Friday, March 31, 2023  Funded PhD Project (UK Students Only)

About the Project

Start date: October 2023

Duration: 3.5yrs

Description: Neuromorphic computing has gained huge momentum in the last decade thanks to the emergence of novel machine learning algorithms such as deep learning. Artificial neural networks are at the forefront of this revolution and their efficient hardware implementation poses significant challenges that impact on many fields of science and technology. The major problem posed by neural network computing is the handling of large matrix multiplications resulting from the parallel flux of information between densely connected layers of neurons. Photonics offers unique advantages for such demanding task as parallel operation is intrinsic to optical systems.

In recent years, a number of schemes based on free-space optical setups have been proposed which have successfully implemented densely connected neural networks with hundreds of thousands of neurons. Such schemes largely rely on spatial-light modulators (SLM) to simultaneously tune millions of neuron interconnects. However, the main drawbacks of commercial SLMs are speed and integrability. An extraordinary opportunity for both high-bandwidth and integrability comes from the recent development of high-speed, high-brightness micro-light emitting diode (µLED) arrays integrated with complementary metal-oxide semiconductor (CMOS) drive electronics. In particular, gallium nitride µLED arrays with GHz-order modulation bandwidths, sub-micron pixel pitches, and large pixel counts have been demonstrated within the past few years by our group. As a result such combined µLED-on-CMOS arrays offer integrated, reconfigurable, all-optical control eliminating the need of additional electronic tuning elements and external optical sources.

In this project, the limits in terms of number of elements and bandwidth will be explored for µLED-on-COMs arrays. Moreover, this system will be combined with optical interconnectivity schemes and advanced learning algorithms to build integrated photonic neural networks. The student will gain expertise in massively parallel drive electronics (LED array drivers) and PIC design, delivering flexible photonic-electronic integration on-a-chip. Furthermore, the student will implement photonic neural network computing with immediate applicability to complex tasks like all-optical signal regeneration and processing, optical pattern recognition and smart sensing. This will require gaining expertise on free-space optical setups and advanced learning algorithms. The student will be part of a larger research group with the opportunity to work with others in a collegiate and enthusiastic team. Research findings will be published in high impact journals with the opportunity to present at international conferences.

Institute of Photonics: The Institute of Photonics (IoP), part of the Department of Physics, is a centre of excellence in applications-oriented research at the University of Strathclyde. The Institute’s key objective is to bridge the gap between academic research and industrial applications and development in the area of photonics. The IoP is located in the £100M Technology and Innovation Centre on Strathclyde’s Glasgow city centre campus, at the heart of Glasgow’s Innovation District, where it is co-located with the UK’s first Fraunhofer Research Centre. Researchers at the IoP are active in a broad range of photonics fields under the areas of Photonic Devices, Advanced Lasers and Neurophotonics, please see:

http://www.strath.ac.uk/science/physics/instituteofphotonics/ourresearch/

Strathclyde Physics is a member of SUPA, the Scottish Universities Physics Alliance.

The University of Strathclyde has, in recent years, been the recipient of the following awards: The Queen’s Anniversary Prizes for Higher and Further Education (2019 & 2021); The Times and The Sunday Times Scottish University of the Year (2020), Times Higher Education University of the Year 2012 & 2019.

Student eligibility: To enter our PhD programme, applicants require an upper-second or first class BSc Honours degree, or a Masters qualification of equal or higher standard, in Physics, Engineering or a related discipline. Full funding, covering fees and stipend, is available for applicants who are UK Nationals (meeting residency requirements) or have settled status (meeting residency requirements), pre-settled status or otherwise have indefinite leave to remain or enter.

How to apply: Applicants should send an up-to-date CV to


Funding Notes

The funding covers the full stipend and tuition fees at the home rate (not the international rate). To be classed as a home student, applicants must meet the following criteria:
• Be a UK national (meeting residency requirements), or
• Have settled status, or
• Have pre-settled status (meeting residency requirements), or
• Have indefinite leave to remain or enter.

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