Robin Upham Email & Phone Number

London, Gb

London, England, United Kingdom

Researching, developing and implementing quantitative data analysis and uncertainty quantification methods for novel measurements of above-ground biomass and soil organic carbon using remote sensing

London, England, United Kingdom

- Developed and tested advanced statistical, probabilistic, and machine learning techniques for high-precision analysis of future data from the Euclid satellite, which is an upcoming ESA cosmology mission aiming to uncover the nature of dark energy - Implemented analyses in Python and C in a Linux environment, developing new code alongside use of common numerical and statistical packages such as NumPy, SciPy, scikit-learn, and Pandas, with data visualisation using matplotlib, executed both on a single remote machine and a distributed cluster using Slurm - Carried out original research using classical machine learning and statistical learning techniques including Bayesian inference, model fitting, parameter estimation, covariance estimation, kernel density estimation, and mutual information estimation, as well as deep learning with convolutional neural networks using TensorFlow - Published three first-author peer-reviewed articles on applied statistical methods (open access link below) - Published open-source Python and C code, with documentation using Sphinx, on GitHub (link below) ​​ - Collaborated with colleagues locally and internationally, presented work orally at regular international videoconference meetings, and provided technical and strategic support to more junior researchers - Organised internal seminar talks: recruited and coordinated speakers, managed technical aspects of presentations, introduced talks and chaired questions, both in person and remotely over Zoom

Taught mathematics tutorials to 4 groups of 5 first-year physics students, both in person and over Zoom

Data Engineering experience: - Management and development of relational (MS SQL Server) and NoSQL (MongoDB) databasesDevelopment and use—both manual and automated—of Extract, Transform and Load data pipelines in SQL, using Airflow for automation - Led support of data warehouse analysis dashboard for major national supermarket chain, and held responsibility for conducting real-time investigations and implementing fixes for technical problems and data errorsSoftware Engineering experience: - Full-stack development using JavaScript stack: Express for back-end and API development, Knockout/Angular web frameworks, Node runtime environment, and HTML & CSS - Everyday use of software development best practices and technologies: agile methodology, coding standards, source control with git including reviewing pull requests, unit testing with Mocha, continuous integration with Jenkins, containerisation with Docker, and cloud computing with Azure

Developed in C++ on existing large object-oriented codebase to implement novel statistical analysis methods for reliable particle identification

Phd, Astrophysics (Statistical Cosmology)

Msc By Research, Astrophysics

Mphys, Physics With Theoretical Physics, First Class