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Engineering Discipline:
- Electronics and Electrical Engineering
Biography:
Alan Murray is Professor of Neural Electronics and Assistant Principal, Academic Support. He introduced the Pulse Stream method for analogue neural VLSI in 1985. Alan’s interests are now primarily in implanted silicon chips for biomedical applications.
He led the £5.2M IMPACT (Implantable Microsystems for Personalised And-Cancer Treatment) project, funded by an EPSRC Programme Grant and enjoys teaching first year engineering/electronics and third year Electromagnetics courses. IMPACT produced proof-of-concept results that will be taken forward in two areas – cancer and wound-healing, as "OPTIMIST" (Optimised, Personalised Treatment & Intervention: Microsystems, Implanted Sensors & Therapeutics).
Alan is a Fellow of IET, IEEE and the Royal Society of Edinburgh, Principal Fellow of the HEA and has published over 360 academic papers. Alan’s degrees are in Physics (BSc and PhD – both from the University of Edinburgh). Subsequently, he has done this...
- 1978-80: Research Fellow, Solid – State Physics, Chalk River Nuclear Laboratories: supported by SERC NATO and Canadian NERC fellowships
- 1980-81: Research Fellow, Department of Physics, University of Edinburgh, leading the Light Scattering section of the Condensed Matter group
- 1981-84: VLSI Designer, Wolfson Microelectronics Institute
- 1984-91: Lecturer, Department of Electrical Engineering
- 1991-94: Reader, Department of Electrical Engineering
- 1994-present: Professor of Neural Electronics
- 2002-2008: Head of the Institute for Integrated Micro and Nano Systems
- 2008-2012: Head of the School of Engineering
- 2012-2015: Dean of Students, College of Science and Engineering
- 2015-2018: Head of the Institute for BioEngineering
- 2015-present: Assistant Principal, Academic Support
Academic Qualifications:
- B.Sc. Ph.D
Professional Qualifications and Memberships:
- F.I.E.E., F.I.E.E.E., F.R.S.E., C.Eng., P.F.H.E.A.
Teaching:
- Fundamentals of Electronics, Electromagnetism,
Research Interests:
Introduction to Bioengineering and Project IMPACT
You can watch this video on Media Hopper or on YouTube.
Primary Interest … Biomedical Sensing and Actuating
Silicon technology can now be integrated with sensors of temperature, pH, oxygen concentration and of biological molecules. This allows chips to be developed that can monitor the body from the inside and in great detail. This is the principle that drove the 2013-2019, £5.2M, EPSRC Programme Grant Project, IMPACT - Implanted Microsystems for Personal Anti-Cancer Treatment.
IMPACT showed:
- That miniaturised Oxygen sensors can make clinically-useful measurements of pH and oxygen saturation in vitro and in small(rat) and large (sheep) animal models
Implantable Microsystems for Personalised Anticancer Therapy
- The sensors can also be used to monitor healing in internal, post-operative wounds – demonstrated in small (rat) and large (pig) animal models.
In vivo validation of a miniaturized electrochemical oxygen sensor for measuring intestinal oxygen tension
- That electrochemical sensors can be miniaturised and implanted to measure specific biomarkers, including Caspases, Trypsine and Human Neutrophil Elastase
Electrochemical sensing of human neutrophil elastase and polymorphonuclear neutrophil active
- That is possible to develop an inert “pro drug” that, when injected systemically, can be activated ELECTRONICALLY by and implant chip at the site of the tumour to produce a cytotoxic drug such as Oxalyplatin (used for colorectal cancer) and Cisplatin (used for a wide range of solid cancers). This will reduce or remove the side-effects of conventional chemotherapy
Electrodrugs: an electrochemical prodrug activation strategy
Ancillary Interest - Silicon-Biology Interface
Particular interests include bio-sensing and the interface between live nerve cells and silicon ships.
Engineering neuronal networks on photolithographically defined, biologically activated silicon substrates
Ancillary Interest - Neural Computation and Machine Learning
Algorithms, Architectures and Applications of Artificial Neural Networks - with particular interests in Spiking Computation and Probabilistic Computation.
Synaptic Weight Noise During MLP Training: Fault Tolerance and Training Improvements
Previous Research - Novel Approaches to VLSI Design
Neural and other "funny" VLSI - to address problems of computation with the noisy, imperfect medium that is Deep-Sub-Micron VLSI.
Multi-Layer Perceptron Learning Optimised for On-Chip Implementation - a Noise-Robust System
Publications on Edinburgh Research Explorer
Further Information:
- Outside interests : Music (especially folk music - writing, playing and listening) and wood-carving
