π About
I am a research scientist at the German Aerospace Center (DLR) and a final-year PhD candidate in Computing at Newcastle University in the United Kingdom. Within the university, I am part of the Cloud Computing for Big Data CDT and the Fluid Dynamics Lab.
My PhD research focuses on computer emulators and the optimisation of physical experiments and computer simulators. I am also developing NUBO
, a transparent Bayesian optimisation package in Python, with the aim of making the optimisation of expensive-to-evaluate black-box functions accessible to researchers from all disciplines. An open-source version is available here.
π° Publications
2024
Mike Diessner, Kevin J. Wilson und Richard D. Whalley. βOn the development of a practical Bayesian optimisation algorithm for expensive experiments and simulations with changing environmental conditions,β arXiv preprint arXiv:2402.03006, 2024.
2023
Mike Diessner, Kevin J. Wilson, and Richard D. Whalley. βNUBO: A Transparent Python Package for Bayesian Optimisation,β arXiv preprint arXiv:2305.06709, 2023.
Joe OβConnor, Mike Diessner, Kevin J. Wilson, Richard D. Whalley, Andrew Wynn, and Sylvain Laizet. βOptimisation and Analysis of Streamwise-Varying Wall-Normal Blowing in a Turbulent Boundary Layer,β Flow, Turbulence and Combustion, 2023.
2022
Mike Diessner, Joe OβConnor, Andrew Wynn, Sylvain Laizet, Yu Guan, Kevin J. Wilson, and Richard D. Whalley. βInvestigating Bayesian Optimization for Expensive-to-evaluate Black Box Functions: Application in Fluid Dynamics,β Frontiers in Applied Mathematics and Statistics, 2022.
Matthew L. Thomas, Gavin Shaddick, David Topping, Karyn Morrissey, Thomas J. Brannan, Mike Diessner, Ruth C. E. Bowyer, Stefan Siegert, Hugh Coe, James Evans, Fernando Benitez-Paez, and James V. Zidek. βA Data Integration Approach to Estimating Personal Exposures to Air Pollution,β 2022 IEEE International Conference on Big Data (Big Data), 2022.
π Presentations
2024
13th International Symposium on Turbulence and Shear Flow Phenomena, βOptimising Active Flow Control Strategies for Random and Controlled Wind Speeds via Bayesian Optimisation,β Centre Mont-Royal, MontrΓ©al, Canada.
2023
76th Annual Meeting of the Division of Fluid Dynamics, βLeveraging Bayesian Optimisation for Expensive Experiments and Simulations in Fluid Dynamics with Uncontrollable Dynamic Variables,β Walter E. Washington Convention Center, Washington (DC), USA.
UK Fluids Conference 2023, βA Machine Learning Framework for the Optimisation of Experiments and Simulations in Fluid Dynamics,β Technology & Innovation Centre, Glasgow, Scotland.
Open Research Awards 2023, βNUBO: An Open-Source AI Framework for Optimisation,β Newcastle University, Newcastle upon Tyne, England.
2022
European Drag Reduction and Flow Control Meeting, βOn the Development of a Bayesian Optimisation Framework for Turbulent Drag Reduction,β Conservatoire National des Arts et MΓ©tiers, Paris, France.
π» Software
NUBO
: Bayesian optimisation framework for solving expenisve-to-evaluate black-box functions (Python).
Website: NUBO Install: PyPI Source: GitHubsimplelhs
: Simple implementation of Latin hypercube sampling to generate space filling designs (Python).
Install: PyPI Source: GitHubbenchfuncs
: Selection of benchmark functions to test optimisation algorithms (Python).
Source: GitHub
π Education
PhD in Computing
Newcastle University
Advisors: Richard D. Whalley and Kevin J. Wilson
Newcastle upon Tyne, United Kingdom
Jun 2021βAug 2024
- Investigation of Bayesian optimisation for expensive-to-evaluate black-box functions.
- Application to computer simulators and physical experiments in engineering to find optimal active blowing strategies to maximise drag reduction.
PGDip in Computing
Newcastle University
Newcastle upon Tyne, United Kingdom
Sep 2020βMay 2021
MSc in Statistics
University of Exeter
Exeter, United Kingdom
Sep 2019βAug 2020
- Thesis: βUsing Agent-based Modelling to Estimate Personal Exposure to PM2.5 in Devonβ.
- Developed model was later used in the paper βA Data Integration Approach to Estimating Personal Exposures to Air Pollutionβ.
BSc in Economics
University of Bonn
Bonn, Germany
Oct 2014βFeb 2018
- Thesis: βUniversal basic income and its effects on the labour market in Germanyβ.
π‘ Teaching
I worked as a teaching assistant on the following courses:
- Data Analysis in Python: Training course for professionals in industry covering programming in Python (pandas, numpy, matplotlib, scikit-learn, etc.) and statistics.
- Computing Foundations of Data Science: Postgraduate-level module teaching the fundamentals of programming in Python.
- Data Management and Exploratory Data Analysis: Postgraduate-level module teaching students all necessary tools to analyse data with R.
- Statistics for Empirical Psychology: Undergraduate-level module teaching the fundamentals of statistics to psychology students (linear regression, mixed-effects model, hypothesis testing, etc.).
π Awards
Open Research Award for making research more transparent, accessible and reproducible. Awarded by Newcastle University at the Open Research Awards 2023 as the only student among researchers, lecturers and professors (Β£150).
Full Four-Year Studentship to attend the Cloud Computing for Big Data Centre for Doctoral Training. Awarded by Newcastle University and the Engineering and Physical Sciences Research Council covering costs of living, tuition, equipment, workshops, travel, conferences and more (over Β£100,000).
MSc Academic Award for the best overall performance on a postgraduate Mathematics programme. Awarded by the University of Exeter for the academic year 2019/20 (Β£100).
Deanβs Commendation for the performance at the top end of the First Class range. Awarded by the University of Exeter.
β Certificates
AgilePM Foundation issued by APMG International in July 2023. Knowledge of the key principles and terminology within Agile Project Management and an understanding of the underpinning philosophy and principles of Agile, as well as the lifecycle, techniques and products of an Agile project.
Professional Scrum Master 1 issued by Scrum.org in January 2024. Knowledge of the Scrum framework, the Scrum Master accountabilities and how to apply Scrum.