Hannah Steventon: Speaker at the TFNetwork Lightning Talk competition

Let's Get Physical - Autumn 2020 Virtual Conference
PGR SPOTLIGHT DAY

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Dr Hannah Steventon is a Research Associate at the University of Suffolk, working on the DfT-funded Smarter Suffolk project with Suffolk County Council, BT and other partners. Smarter Suffolk is building a county-wide Live Lab of thousands of Internet of Things (IoT) sensors, measuring environmental and traffic conditions across the county to showcase competing innovative technologies. Big Data sets will be accumulated in a vendor-neutral data exchange for analytics applied to a range of Local Authority services. Existing and new communications networks are enabling the IoT deployment, in part using the existing powered lighting column infrastructure.

Initially a hydrogeologist, in her early career Hannah led regeneration projects for large civil engineering firms to assess and remediate contaminated land. Her professional experience includes sophisticated software analysis and modelling of large data sets, site project management of civils contractors, and laboratory chemical analysis. Her doctoral research showed how natural organic matter affects the movement of contaminants through the ground, and she taught Hydrogeology and Pollution at Birkbeck, University of London.

In recent years, as a computing educator and STEM Ambassador, Hannah taught hundreds of children coding, electronics and control systems, using the Raspberry Pi, Arduino, Crumble and Micro:Bit. Projects have included running children’s code on the International Space Station; developing an IoT device to win a major national competition; robots in school corridors; and a large class of 10 year olds soldering self-built games consoles.

Hannah holds a MA in Natural Sciences from the University of Cambridge, and an MSc and PhD in Hydrogeology from University College London. She is a Chartered Geologist and Fellow of the Geological Society, and a Raspberry Pi Certified Educator.

Interesting fact

When Hannah used to teach computing to ten year olds, the children wrote Python programmes to run on a Raspberry Pi to measure temperature and warn when it was too hot or cold. The children’s code was sent to run in space measuring temperature on the International Space Station and displaying the outcome to the astronauts. 
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Poster presentation

Smarter Suffolk: Sensors and data for public services
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Daniel O'Connor, UCL: Speaker at the TFNetwork Lightning Talk competition

Let's Get Physical - Autumn 2020 Virtual Conference
PGR SPOTLIGHT DAY

Held on 12th - 16th October 2020: Five days of Physics goodness on 

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Daniel O'Connor is a University College London (UCL) PhD student sponsored by BT, researching quantum annealing and its potential for practical implementation. 

He enjoys a good cup of coffee, and a game of football.
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Quantum annealing for network optimisation
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Yi-Tun Lin: Speaker at the TFNetwork Lightning Talk competition

Let's Get Physical - Autumn 2020 Virtual Conference
PGR SPOTLIGHT DAY

Held on 12th - 16th October 2020: Five days of Physics goodness on 

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Yi-Tun (Ethan) Lin is a Ph.D. student in the Colour & Imaging Lab, School of Computing Sciences, University of East Anglia, UK. 

He received a joint M.Sc. degree in Colour Science in 2018, from University Jean Monnet (France), University of Granada (Spain) and University of Eastern Finland (Finland), and a B.Sc. degree in Physics in 2016, from National Taiwan University, Taiwan. His research interest is physics and machine learning-based spectral reconstruction.
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Physically Plausible Spectral Reconstruction
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Kakia Chatsiou, University of Essex: Speaker at the TFNetwork Lightning Talk competition

Let's Get Physical - Autumn 2020 Virtual Conference
PGR SPOTLIGHT DAY

Held on 12th - 16th October 2020: Five days of Physics goodness on 

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I am currently working as a Senior Researcher, at the ESRC Business and Local Government Data Research Centre. 

My research focuses on automated, quantitative methods of processing large amounts of textual and other forms of unstructured data – mainly political texts and social media – and the methodology of text mining for social science. I have published on applications of measurement and the analysis of text as data on machine learning methods and deep learning. I am also applying machine learning and natural language processing techniques to the analysis of public policy. My substantive research interests centre on resilience and the role of public policies and institutions at different levels of governance in shaping it. 

I am a member of the Natural Language and Information Processing Research Group, the Berkeley Initiative for Transparency in the Social Sciences.
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Recent publications:

• Chatsiou, K. and Mikhaylov, SJ., (2020). Deep Learning for Political Science. In: The SAGE Handbook of Research Methods in Political Science and International Relations. Editors: Curini, L. and Franzese, R., . SAGE Publications Ltd. 1053- 1078. 9781526459930
• Chamberlain, J., Turpin, B., Maged, A., Chatsiou, A. and O'Callaghan, K., (2020) Designing for Collective Intelligence and Community Resilience on Social Networks. Human Computation 
• Yannitell Reinhardt, G. and Chatsiou, K., (2019). Using community education interventions to build resilience and avert crises: how accidental dwelling fires decreased in Essex County, UK. Local Government Studies. 45 (3), 394-412

Political text classification using Neural Networks

We build a sentence-level political discourse classifier using existing human expert annotated corpora of political manifestos from the Manifestos Project (Volkens et al.,2020a) and applying them to a corpus of COVID-19 Press Briefings (Chatsiou,2020). We use manually annotated political manifestos as training data to train a local topic Convolutional Neural Network (CNN) classifier; then apply it to the COVID-19 Press Briefings Corpus to automatically classify sentences in the test corpus. We report on a series of experiments with CNN trained on top of pre-trained embeddings for sentence-level classification tasks. We show that CNN combined with transformers like BERT outperforms CNN combined with other embeddings (Word2Vec, Glove, ELMo) and that it is possible to use a pre-trained classifier to conduct automatic classification on different political texts without additional training.

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Eleanor Crane, UCL/IBM: Speaker at the TFNetwork Lightning Talk competition

Let's Get Physical - Autumn 2020 Virtual Conference
PGR SPOTLIGHT DAY

Held on 12th - 16th October 2020: Five days of Physics goodness on 

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I'm a PhD student researching quantum computer entangling gates in silicon at the London Center for Nanotechnology. Being part of the Advanced Characterisation of Materials CDT has linked me up with many like-minded PhD students here at University College London and Imperial College London. I'm also on IBM's community team for the open source quantum algorithm software Qiskit.

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From two qubit entangling gates to quantum algorithms, and the steps in-between

 

Carmen Palacios-Berraquero, CEO Nu Quantum: Speaker at our virtual Autumn 2020 conference "Let's get Physical"

Let's Get Physical - Autumn 2020 Virtual Conference
QUANTUM

Held on 12th - 16th October 2020 - 5 days of Physics goodness on 

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- Wireless
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Carmen Palacios-Berraquero is CEO of Nu-Quantum. 

Nu Quantum aims to be the platform technology for the Quantum Internet. Our key is that we have technology that can generate quantum light: this means single particles of light (single photons) that will carry single quantum bits of information, and this will be the medium through which links are established between the nodes of a quantum network. This network, the so-called Quantum Internet / Quantum Cloud, is the predicted parallel network of the future, where super secure and super powerful computations will be done. 

Before starting her company, Carmen was a research scientist at the University of Cambridge. Her PhD thesis title was: 'Quantum-confined Excitons in 2-dimensional Materials'. The family of 2D materials she studies are transition metal dichalcogenides (2D-TMDs). She won the 2018 Jocelyn Bell Burnell prize for discovering and patenting a method to create single-photon emitting sites in atomically-thin materials and for using a 2-dimensional decive to all-electrically induce quantum emission from these sites.

Read more about Carmen here.
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Quantum, an Industry Perspective
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Prof Robert Piechocki, University of Bristo: Speaker at our conference "Let's get Physical"

Let's Get Physical - Autumn 2020 Virtual Conference
WIRELESS

Held on 12th - 16th October 2020 - 5 days of Physics goodness on 

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Robert J Piechocki is Professor in the School of Computer Science, Electrical and Electronic Engineering, and Engineering Maths. His research interests span all areas of connected intelligent systems. His domain expertise is Connected and Automated Vehicles (CAV), and wireless sensing for eHealth.  

He has published over 200 papers in peer-reviewed international journals and conferences and holds 13 patents in these areas. Robert is leading wireless connectivity and sensing research activities for the IRC SPHERE project (winner of 2016 World Technology Award). Robert is also a PI for several current high-profile projects in networks, connectivity and sensing funded by industry, Innovate UK and EPSRC such as VENTURER, FLOURISH, NG-CDI, OPERA.
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Wireless Systems, Self-driving Vehicles and Digital Twins
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