Ioannis Nikiteas

PhD candidate for Nuclear Computational Modelling

Imperial College London, Applied Modelling and Computation Group (AMCG)

About me

I am a PhD candidate at Imperial College London based in the Applied Modelling and Computation Group (AMCG). My research at the moment is primarily focused on using adaptive mesh methods to perform high fidelity computational modelling on radiation transport problems, which are particularly challenging due to their high dimensionality. I am also one of the main developers of FETCH, our in-house radiation transport code.

In my free time I also develop and maintain the Fortran Language Server fortls and Modern Fortran the most used Fortran extension for Visual Studio Code.

Download my resumé.

Interests

Computational Neutronics
Optimisation Problems
Energy Markets & Sustainable Energy Sources
Molecular Dynamics
Data Visualisation
Machine Learning

Education

PhD in Computational Physics, 2022

Imperial College London
MSc in Advanced Nuclear Engineering, 2018

Imperial College London
BSc in Experimental Physics, 2014

Royal Holloway University of London

Skills

C/C++/Fortran/Python

HPC Computational Modelling

Data Analysis & Visualisation

Featured Publications

Reentrant melting and multiple occupancy crystals of bounded potentials: Simple theory and direct observation by molecular dynamics simulations

Visualisation of crystals forming in a fluid using a Generalized exponential (GEM-m) pair potential with m = 4 at a temperature of T = 0.4 using 3456 particles.

Load balancing angular adaptivity on energy dependent reactor problems

Impact of load balancing on parallel performance with Haar wavelets angular adaptivity

Bounded inverse power potentials: Isomorphism and isosbestic points

Projects

Oct 30, 2021

tkinter-tooltip

A feature rich and theme aware tooltip for tkinter

Oct 27, 2021

findent PyPi

Wrapper around findent to allow for PyPi release

Oct 27, 2021

Magnetic Field Dual Coil Visualisation

A GUI which generates Mayavi interactive plots for magnetic fields

Apr 27, 2016

Dynamic Load Balancing on tensor product spaces - Part 1

Implementation of a Dynamic Load Balancing algorithm for regular and goal-based adaptivity to ensure scalable runtimes at the largest HPCs.

Apr 27, 2012

Gallery with ... "ELPIDA"

Art exhibition gallery where proceeds were donated to the Association of Friends and Children with Cancer “ELPIDA”

Recent Publications

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Ioannis Nikiteas, David M. Heyes (2020). Reentrant melting and multiple occupancy crystals of bounded potentials: Simple theory and direct observation by molecular dynamics simulations. Phys. Rev. E.

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Ioannis Nikiteas, Steven Dargaville, Paul N Smith, Richard P Smedley-stevenson, Christopher C. Pain (2020). Load balancing angular adaptivity on energy dependent reactor problems. PHYSOR2020 conference proceedings.

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Ioannis Nikiteas, Steven Dargaville, Christopher C. Pain, Paul N. Smith, Richard P. Smedley-Stevenson (2019). Impact of load balancing on parallel performance with Haar wavelets angular adaptivity. International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering, (M&C 2019).

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Ioannis Nikiteas, David M. Heyes (2019). Bounded inverse power potentials: Isomorphism and isosbestic points. J. Chem. Phys.

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Experience

Freelance Software Developer

Sep 2021 – Present London, UK

Created and actively develops a new Language Server for Fortran, fortls to allow for enhanced functionality across multiple code editors and IDEs
Active development and maintainance of the Modern Fortran VS Code extension
Wrote and currently maintaining a Python Release wrapper for findent, Fortran formatter
Created various CI and CD pipelines for Fortran tools

Graduate Teaching Assistant

Imperial College London

Dec 2018 – Apr 2022 London, UK

Taught various principles of programming, linear algebra, numerical methods, MPI parallelism and computational modelling to both final year Undergraduate students and Master’s students from multiple MSc courses: Applied Computational Science and Engineering (ACSE), Environmental Data Science and Machine Learning, Geo-Energy with Machine Learning and Data Science.

Module: 375 Advanced Programming C++ (2018-2019)
Module: ACSE-5 Numerical methods with C++ (2020-2022)
Module: ACSE-6 Parallel Programming using MPI (2020)
Module: Advanced Programming (C++) (2022)

Intern Engineer in Maintenance of Alumina, Non-Invasive Testing Methods

Aluminium of Greece

Jul 2016 – Aug 2016 Viotia, Greece

Was part of a team responsible for the optimisation and maintenance of equipment used in the production of aluminium oxide (alumina).
Was familiarised with methods and techniques used to investigate for structural failures in industrial equipment.
Performed non-destructive testing (e.g. Ultrasonic testing, liquid penetrant, eddy-current testing, remote visual inspection)

Accomplishments

Academic excellence scholarship

Alexander S. Onassis Public Benefit Foundation Sep 2017 – Sep 2018

Received a grant of £13,000 for academic excellence

Contact

Phone: Available upon Request
Royal School of Mines, Prince Consort Road, London, London SW7 2BP
480.30, Earth Science and Engineering
Email me for an appointment