With this Future Leaders Fellowship, I will lead a research team that will build the first self-consistent data assimilation (DA) and continuous verification scheme for space weather forecasting, which is critically needed to improve our physical understanding of, and preparedness for, hazardous space weather. Space weather is a global natural hazard which can severely impact society, industry, and be a risk-to-life. It is a known risk to energy security, communications, aviation, and satellite services. Severe space weather is driven by Coronal Mass Ejections (CMEs), which are violent eruptions of magnetised plasma from the Sun's atmosphere. Cost-effective mitigation of space weather therefore relies on forecasting the arrival and properties of CMEs at Earth. Due to the potential seriousness of space weather, it is included in the UK's National Risk Register, and is planned for in the UK's Severe Space Weather Preparedness Strategy. Thus there is a crucial need to both better understand the physics of CMEs and to improve space weather forecasting capability. However, CME prediction has failed to improve in a decade of intense research, due to both knowledge gaps and observational limitations. Sophisticated computer models are used to simulate CMEs flowing through the solar wind to Earth. However, although these models are grounded in the relevant physics, they struggle to accurately represent observed CMEs. There are two key reasons for this; firstly, the starting conditions of these models are very uncertain due to observational limitations; secondly, the representation and balance of processes in the models is incorrect - indicative of our limited knowledge of physics controlling CMEs. Heliospheric Imagers (HI), such as those developed by UKRI's STFC for NASA's STEREO mission, provide the only consistent observations of CMEs and the solar wind flowing over the whole domain from the top of the solar atmosphere to Earth. These observations show CMEs being both distorted and eroded as they flow through the highly structured solar wind, but they are under-exploited in space weather research and forecasting. DA is the process of combining models and observations, accounting for the uncertainty in each, to provide a best estimate of a system's state. By assimilating a wide range of meteorological observations, DA has revolutionised the accuracy of terrestrial weather prediction, but more importantly improved physical understanding of atmospheric processes. With DARES, we will develop a HI-based DA scheme that will revolutionise our understanding of CME physics and improve space weather forecasting skill. Working at the University of Reading, my team will collaborate with colleagues at the UK Met Office Space Weather Operations Center, UKRI's Rutherford Appleton Laboratory and KU Leuven. By comparing our HI DA constrained CME simulations against observations of CMEs flowing past Earth, and state-of-the-art spacecraft observatories such as ESA's Solar Orbiter and NASA's Parker Solar Probe, we will discover the physics crucial for understanding CME evolution. In doing so, DARES will provide the critically needed knowledge and tools required improve space weather forecasting skill. DARES is timely as it will help maximise the UK's return-on-investment from Vigil, the European Space Agency (ESA) space weather monitor to be launched in 2029. DARES also directly aligns with the UK National Space Strategy to "protect and defend our national interests in" space and "lead pioneering scientific discovery" as well as Pillar 1 of the UK Severe Space Weather Preparedness Strategy.

Cochlear implants (CIs) restore hearing to severely and profoundly deaf people by electrically stimulating the auditory nerve. Many CI patients understand speech well in quiet surroundings, but all struggle to hear well in noisy situations. In addition, the perception of pitch is usually very poor and this greatly reduces the enjoyment of music. Because normal-hearing listeners use differences in pitch between sounds to tell them apart this also contributes the difficultiess CI listeners experience when many people are talking at the same time. Our research proposal investigates ways of alleviating these problems. One strand of our approach aims to produce selective activation of the auditory nerve whilst still producing a sound sensation that is loud enough. This is important for two reasons. First, information from each frequency band of speech is sent to one electrode, with the aim of stimulating just a few neurons close to it. Unfortunately the electrical current spreads broadly to other electrodes, thereby smearing the neural response to the sound. Second, current sometimes spreads outside of the cochlea and stimulates the facial nerve, causing unpleasant twitching that can prevent the patient from using their CI. We have designed new ways of stimulating the electrodes that we hope will solve these problems, and will test them with CI patients. To better understand our results we compare them to the predictions of a computer model of the auditory system, and, in turn, use the experimental results to improve the model. We are particularly interested in how the health of the auditory nerve, which degenerates following deafness, influences the effectiveness of methods - including our own - that are designed to produce selective stimulation and improve speech perception. To do so we include measurements of two particular groups of patients. One of these are those who have become suddenly deaf in a way that is believed to leave the auditory nerve intact, and we compare them to long-term-deaf users. The other consists of children with a condition known to affect the auditory nerve, with recent evidence that it may particularly affect neurons that innervate the apex of the cochlea, which normally responds to low-frequency sounds. A second strand focusses on the poor pitch perception by CI users. Some manufacturers have tried to improve pitch perception by presenting fine timing information to a subset of the electrodes, in the cochlear apex, as part of the speech-processing strategy (which converts sound to a pattern of electrical impulses). Unfortunately, very little is known about how CI listeners actually process this information, and this is the subject of the first part of this strand. These methods usually present different patterns to each electrode, and we suspect that pitch perception would be better with the same pattern applied to all of these apical electrodes. If our first experiments show that this is indeed the case, we will implement and test new speech-processing strategies which we hope will improve pitch perception while still clearly conveying all the other information that is needed for good speech perception. Finally, we use electrophysiological methods to help understand the neural basis for poor perception by CI listeners, especially that occurring when the pitch is quite high