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mikediessner/README.md

About me

I’m a final-year PhD candidate in Computing at Newcastle University in the UK. As part of the Cloud Computing for Big Data CDT, I research how Bayesian optimisation frameworks can be utilised to optimise expensive-to-evaluate black-box functions with application in engineering, particularly fluid dynamics.

Short biography

  • 2018: BSc in Economics from the University of Bonn, Germany
  • 2020: MSc in Applied Data Science and Statistics from the University of Exeter, UK
  • Currently: PhD candidate in Computing at Newcastle University, UK

Languages and tools

Python

R

Git

GitHub

Linux

Azure

Google

Docker

Markdown

NumPy

Pandas

PyTorch



Research interests

  • Machine learning
  • Optimisation
  • Computer emulators
  • Data-driven engineering
  • Bayesian statistics

Pinned

  1. nubo nubo Public

    NUBO is a Bayesian optimisation framework for the optimisation of expensive-to-evaluate black-box functions developed by the Fluid Dynamics Lab at Newcastle University.

    Python 10

  2. simplelhs simplelhs Public

    Simple implementation of Latin Hypercube Sampling.

    Python 6 2

  3. mikediessner.github.io mikediessner.github.io Public

    Personal website.

    1

  4. benchfuncs benchfuncs Public

    Benchmark functions to test optimisation algorithms.

    Python 1 1