Robert M. Gray
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Photonic integrated circuit optical parametric oscillators Open
Optical parametric oscillators (OPOs) are versatile nonlinear optical devices for wavelength generation from the visible to the mid-infrared. Recently, OPO research has merged with photonic integrated circuits (PICs) in the advancement of …
View article: DEEP MULTI-MODAL REPRESENTATIONAL PHENOTYPING OF GLIOMA
DEEP MULTI-MODAL REPRESENTATIONAL PHENOTYPING OF GLIOMA Open
AIMS Complex heterogeneity is a major obstacle to clinical and scientific progress in neuro-oncology, resolvable only with highly expressive models powered by large-scale data and high-performance compute. We sought to de- velop a comprehen…
View article: Generalizable automated ischaemic stroke lesion segmentation with vision transformers
Generalizable automated ischaemic stroke lesion segmentation with vision transformers Open
Ischaemic stroke, a leading cause of death and disability, critically relies on neuroimaging for characterising the anatomical pattern of injury. Diffusion-weighted imaging (DWI) provides the highest expressivity in ischemic stroke but pos…
Ultrafast neuromorphic computing with nanophotonic optical parametric oscillators Open
Over the past decade, artificial intelligence (AI) has led to disruptive advancements in fundamental sciences and everyday technologies. Among various machine learning algorithms, deep neural networks have become instrumental in revealing …
Two-optical-cycle pulses from nanophotonic two-color soliton compression Open
Few- and single-cycle optical pulses and their associated ultra-broadband spectra have been crucial in the progress of ultrafast science and technology. Moreover, multi-color waveforms composed of independently manipulable ultrashort pulse…
Ultrashort pulse biphoton source in lithium niobate nanophotonics at 2 μm Open
Photonics offers unique capabilities for quantum information processing (QIP) such as room-temperature operation, the scalability of nanophotonics, and access to ultrabroad bandwidths and consequently ultrafast operation. Ultrashort pulse …
Ultra-Short Pulse Biphoton Source in Lithium Niobate Nanophotonics at 2$\textμ$m Open
Photonics offers unique capabilities for quantum information processing (QIP) such as room-temperature operation, the scalability of nanophotonics, and access to ultrabroad bandwidths and consequently ultrafast operation. Ultrashort-pulse …
Optical-parametric-amplification-enhanced background-free spectroscopy Open
Traditional absorption spectroscopy has fundamental difficulty in resolving small absorbance from strong background due to the instability of laser sources. Existing background-free methods in broadband vibrational spectroscopy help to all…
An Analysis of Training of the Remote Medical Provider and Recommended Standards Open
This article summarizes the mindset, educational requirements, different training aspects, and specific treatment protocols that help establish the Remote Medical Provider (RMP) concept's baseline proficiency criteria and recommended insti…
BRAIN TUMOUR GENETIC NETWORK SIGNATURES SUPERIORLY FORECAST SURVIVAL Open
AIMS Gliomas typically exhibit a spectrum of genetic mutations, reflecting multiple, potentially complex interactions across distinct molecular pathways. Predicting disease evolution and prescribing individually optimal treatment plausibly…
Brain tumour genetic network signatures of survival Open
Tumour heterogeneity is increasingly recognized as a major obstacle to therapeutic success across neuro-oncology. Gliomas are characterized by distinct combinations of genetic and epigenetic alterations, resulting in complex interactions a…
Mode-locked laser in nanophotonic lithium niobate Open
Mode-locked lasers (MLLs) have enabled ultrafast sciences and technologies by generating ultrashort pulses with peak powers substantially exceeding their average powers. Recently, tremendous efforts have been focused on realizing integrate…
Deep Variational Lesion-Deficit Mapping Open
Causal mapping of the functional organisation of the human brain requires evidence of \textit{necessity} available at adequate scale only from pathological lesions of natural origin. This demands inferential models with sufficient flexibil…
Quadratic-soliton-enhanced mid-IR molecular sensing Open
Optical solitons have long been of interest both from a fundamental perspective and because of their application potential. Both cubic (Kerr) and quadratic nonlinearities can lead to soliton formation, but quadratic solitons can practicall…
Brain tumour genetic network signatures of survival Open
Tumour heterogeneity is increasingly recognized as a major obstacle to therapeutic success across neuro-oncology. Gliomas are characterised by distinct combinations of genetic and epigenetic alterations, resulting in complex interactions a…
View article: Visible-to-mid-IR tunable frequency comb in nanophotonics
Visible-to-mid-IR tunable frequency comb in nanophotonics Open
Optical frequency comb is an enabling technology for a multitude of applications from metrology to ranging and communications. The tremendous progress in sources of optical frequency combs has mostly been centered around the near-infrared …
Few-cycle vacuum squeezing in nanophotonics Open
One of the most fundamental quantum states of light is the squeezed vacuum, in which noise in one of the quadratures is less than the standard quantum noise limit. In nanophotonics, it remains challenging to generate, manipulate, and measu…
Could the ‘Wow’ signal have originated from a stochastic repeating beacon? Open
The famous ‘Wow’ signal detected in 1977 remains arguably the most compelling SETI signal ever found. The original Big Ear data require that the signal turned on/off over the span of ∼3 min (time difference between the dual antennae), yet …
Fast Unsupervised Brain Anomaly Detection and Segmentation with Diffusion Models Open
Deep generative models have emerged as promising tools for detecting arbitrary anomalies in data, dispensing with the necessity for manual labelling. Recently, autoregressive transformers have achieved state-of-the-art performance for anom…
All-optical ultrafast ReLU function for energy-efficient nanophotonic deep learning Open
In recent years, the computational demands of deep learning applications have necessitated the introduction of energy-efficient hardware accelerators. Optical neural networks are a promising option; however, thus far they have been largely…
Equitable modelling of brain imaging by counterfactual augmentation with morphologically constrained 3D deep generative models Open
We describe Countersynth, a conditional generative model of diffeomorphic deformations that induce label-driven, biologically plausible changes in volumetric brain images. The model is intended to synthesise counterfactual training data au…
Hierarchical Graph-Convolutional Variational AutoEncoding for Generative\n Modelling of Human Motion Open
Models of human motion commonly focus either on trajectory prediction or\naction classification but rarely both. The marked heterogeneity and intricate\ncompositionality of human motion render each task vulnerable to the data\ndegradation …
View article: Femtojoule, femtosecond all-optical switching in lithium niobate nanophotonics
Femtojoule, femtosecond all-optical switching in lithium niobate nanophotonics Open
Optical nonlinear functions are crucial for various applications in integrated photonics, such as all-optical information processing, photonic neural networks and on-chip ultrafast light sources. Due to the weak nonlinearities in most inte…
Bayesian Volumetric Autoregressive generative models for better\n semisupervised learning Open
Deep generative models are rapidly gaining traction in medical imaging.\nNonetheless, most generative architectures struggle to capture the underlying\nprobability distributions of volumetric data, exhibit convergence problems, and\noffer …
Application of Machine Learning in Package Holiday Selling Price Prediction Open
This report looks at the statistical relationships between the price a holiday is historically sold for and the features of a holiday. From that analysis it demonstrates the application of machine learning in holiday selling price predicti…