Dr. Sendy Phang Profile

Dr. Sendy Phang

Assistant Professor at Univ of Nottingham

SPIE Involvement:

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Area of Expertise:

metamaterial , parity time symmetric material , optical modelling , electromagnetics theory

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Sendy Phang was born in Jakarta, Indonesia in 1988. He received the BEng degree in engineering physics with first class honours, from Bandung Institute of Technology (ITB), Bandung, Indonesia in 2010, the MSc degree in electromagnetic design and PhD degree from the University of Nottingham in 2011 and 2016, respectively. His research interests includes electromagnetics theory in particular of light-matter interaction, metamaterials, photonic crystals, PT structure in optics and its applications.

Proceedings Article | 13 March 2024 Presentation

Vibrational biospectroscopy of blood plasma: an alternative approach to endometrial cancer diagnosis and screening

Roberta Schiemer, Jessica Grant, David Furniss, Sendy Phang, Angela Seddon, Ioan Notingher, William Atiomo, Ketankumar Gajjar

Proceedings Volume PC12836, PC128360D (2024) https://doi.org/10.1117/12.2689565

KEYWORDS: Cancer, Blood, Vibration, Plasma, Raman spectroscopy, Spectroscopy, Reflectance spectroscopy, Plasma spectroscopy, Histopathology, Diagnostics

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Proceedings Article | 5 March 2021 Paper

Mid-infrared sources, based on chalcogenide glass fibres, for biomedical diagnostics

Angela Seddon, Łukasz Sójka, David Furniss, Zhuoqi Tang, Richard Crane, Joel Nunes, Sendy Phang, Emma Barney, Mark Farries, Trevor Benson, Slawomir Sujecki

Proceedings Volume 11635, 1163503 (2021) https://doi.org/10.1117/12.2593181

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Proceedings Article | 5 March 2021 Presentation

Neuromorphic sensing via temporal signal signature processed by photonic reservoir computer

Sendy Phang, David Furniss, Christopher Mellor, Günther Roelkens, Angela Seddon, Peter Bientsman, Trevor Benson

Proceedings Volume 11636, 116360H (2021) https://doi.org/10.1117/12.2584187

KEYWORDS: Signal processing, Optical computing, Optical microcavities, Retina, Brain, Receptors, Photonic crystals, Neuroscience, Molecules, Molecular photonics

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Proceedings Article | 12 June 2020 Paper

Analysis of atherosclerotic lesions in the human body

Natalia Malinowska, Zygmunt Domagała, Sendy Phang, Trevor Benson, Elżbieta Bereś-Pawlik

Proceedings Volume 11456, 114560D (2020) https://doi.org/10.1117/12.2566533

KEYWORDS: Tissues, Endoscopes, Blood vessels, Machine learning, Cameras, Databases, Image analysis, CCD cameras, Analytical research, In vivo imaging

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A very important problem in modern medicine is the identification of atherosclerotic lesions within human tubular vessels. Current methods such as OCT and intravascular ultrasonography are very expensive and do not provide conclusive information about the formation of atherosclerotic plaques, especially within the human thoracic aorta. This paper presents a new solution to the identification of atherosclerotic lesions based on a specially constructed endoscope that uses CCD cameras. The endoscope analyses the condition of the walls of the blood vessels (side analysis) and represents a step towards an in vivo investigation of part of the human body. The remaining problem is the exact identification of the places where changes occur in the human tubular vessels. Research using the fluorescence phenomenon gives a summary result from an area whose location can be determined with an accuracy of millimetres. For pipes with sufficiently large internal diameter CCD cameras can be used to produce images of the examined tissues. It is possible for doctors to use the images so obtained to identify diseased areas with high accuracy. An alternative approach for identifying atherosclerosis is to use a neural network method to analyse the received pictures. Popular methods such as Machine Learning and Deep Learning can also be used to identify features in medical images. Creating a ‘learning’ database of endoscopic images in which a doctor identifies regions of healthy and atherosclerotic tissue is time consuming. However, after creating the database, the image identification algorithm works much faster than known numerical methods. It can significantly contribute to improving the effectiveness of atherosclerosis diagnostics. This paper presents initial results that confirm the effectiveness of a Machine Learning approach in identifying atherosclerotic lesions from the analysis of endoscope images obtained with a black and white camera following fluorescence stimulation and with a colour CCD camera using white light illumination. These findings are important since histological tests are not possible in in vivo investigations.

Proceedings Article | 9 April 2020 Presentation + Paper

Mid-infrared sources for biomedical applications based on chalcogenide glass fibres

Angela Seddon, Slawomir Sujecki, Lukasz Sojka, David Furniss, Zhuoqi Tang, David Mabwa, Joel Nunes, Richard Crane, Harriet Parnell, Dinuka Jayasuriya, Meili Shen, Yuanrong Fang, Sendy Phang, Elżbieta Bereś-Pawlik, Emma Barney, Mark Farries, Trevor Benson

Proceedings Volume 11357, 1135710 (2020) https://doi.org/10.1117/12.2568040

KEYWORDS: Glasses, Chalcogenide glass, Absorption, Mid-IR, Luminescence, Ions, Terbium, Fiber lasers, Lanthanides, Biomedical optics

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Proceedings Article | 25 February 2020 Presentation + Paper

A chaotic microresonator structure for an optical implementation of an artificial neural network

Sendy Phang, Peter Bienstman, Angela Seddon, Chris Mellor, Trevor Benson

Proceedings Volume 11283, 1128313 (2020) https://doi.org/10.1117/12.2548716

KEYWORDS: Photonics, Picosecond phenomena, Microresonators, Artificial neural networks, Sensors, Spectroscopy, Integrated optics, Tissues, Neural networks, Finite-difference time-domain method

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Proceedings Article | 23 April 2018 Presentation + Paper

Finite difference time domain modeling of wavefront aberrations in bone using second harmonic generation microscopy

Kayvan Forouhesh Tehrani, Sendy Phang, Peter Kner, Ana Vukovic, Luke Mortensen

Proceedings Volume 10502, 105020R (2018) https://doi.org/10.1117/12.2290376

KEYWORDS: Bone, Finite-difference time-domain method, Refractive index, Harmonic generation, Light scattering, Scattering, Microscopy, Second-harmonic generation, Wavefront aberrations, Adaptive optics

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Proceedings Article | 23 February 2018 Paper

Resolution enhancement of 2-photon microscopy using high-refractive index microspheres

Kayvan Forouhesh Tehrani, Arash Darafsheh, Sendy Phang, Luke Mortensen

Proceedings Volume 10498, 1049833 (2018) https://doi.org/10.1117/12.2290613

KEYWORDS: Microscopy, Tissues, Second-harmonic generation, Bone, Optical fibers, Multiphoton microscopy, Point spread functions, Microscopes, Finite-difference time-domain method, Resolution enhancement technologies

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Proceedings Article | 19 March 2015 Paper

Highly non-linear optical microresonators for frequency combs generation

Daniil Zhivotkov, Elena Romanova, Ana Vukovic, Sendy Phang

Proceedings Volume 9448, 94482A (2015) https://doi.org/10.1117/12.2179964

KEYWORDS: Dispersion, Microresonators, Frequency combs, Chalcogenide glass, Solitons, Mid-IR, Refractive index, Chalcogenides, Resonators, Nonlinear optics

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