About me

I'm a Data Scientist in Sustainable Transport at TNO in The Hague, Netherlands. My work focuses on analyzing and modeling real-world vehicle emissions to support cleaner and more efficient transportation solutions. Among others, I'm involved in the following key projects at TNO:

  • Estimating real-world brake wear emissions to assess the impact of particulate matter from braking on air quality.
  • Measuring NOx emissions using the plume chase method, which involves real-world data collection and modeling to improve emission estimates.

I obtained my PhD in Physics from the University of Groningen in 2025, with my thesis titled Intermediate Mass Black Holes as Targets for Dark Matter Searches - A Gamma-ray Analysis Incorporating Machine Learning Techniques.
With over 10 years of Python experience, I have strong expertise in machine learning, data analysis, and software development, with a focus on artificial neural networks and predictive modeling.

Some of my favourite books:

  • The 7 Habits of Highly Effective People by Stephen R. Covey
  • Thinking. Fast and Slow by Daniel Kahneman
  • Atomic Habits by James Clear
  • Mindfullness in Plain English by Bhante Henepola Gunaratana
  • The Culture Map by Erin Meyer
  • A Random Walk Down Wall Street by Burton G. Malkiel
  • Das Zeitalter der Unschärfe by Tobias Hürter

CV

Profile picture

A summary of my CV is listed below.

Work Experience


since 2024: Data Scientist
Analyzing and modeling real-world vehicle emissions to support cleaner and more efficient transportation solutions.
TNO, The Hague, the Netherlands

2017-2019: Student Assistant
Conducting experiments in the field of thin film processing with laser radiation.
Fraunhofer Institute for Laser Technology ILT, Aachen, Germany

Education


2020-2025: PhD, Physics
Thesis title: Intermediate Mass Black Holes as Targets for Dark Matter Searches - A Gamma-ray Analysis Incorporating Machine Learning Techniques
University of Groningen, the Netherlands

2018-2020: Master of Science, Physics
Thesis title: X-ray Studies of the Galaxy Group UGC03957 using eROSITA, XMM-Newton and Suzaku Data
RWTH Aachen University in cooperation with University of Bonn, Germany

2014-2018: Bachelor of Science, Physics
Thesis title: Study of Matrix Element Methods for the Higgs Boson CP Measurement in CMS
RWTH Aachen University, Germany

Skills


Programming Languages
Proficient with: Python, bash
Comfortable or Familiar with: C/C++, SQL, MATLAB, HTML & CSS

Machine Learning
Artificial Neural Networks, Boosted Decision Trees, Random Forest, Support Vector Machines, Linear Regression, Tensorflow, Keras, Scikit-learn

Data Science / Visualisation
NumPy, Pandas, Scipy, PySpark, Matplotlib

High-Performance Computing
Parallel Processing, Remote Job Submission, GPU Acceleration

Operating Systems
macOS, Linux, Windows

Miscellaneous
Git / GitLab, Jupyter Notebook, LaTex, Microsoft Office

Languages


English (proficient)
German (mother tongue)
Dutch (basic)
French (basic)

Scholarships


Since 2020: Fundamentals of the Universe PhD Scholarship Programme
Awarded a PhD scholarship via a competitive process, evaluated by top physics and astronomy experts.

Volunteer Work


2021-2022: President of Young Minds Groningen
2022-2024: Coordinator of Machine Learning Journal Club

Publications

Below a selection of publications I've contributed to. A full list of my publications is available here.

  • Gamma rays from dark matter spikes in EAGLE simulations
    J. Aschersleben, G. Bertone, D. Horns, E. Moulin, R.F. Peletier, M. Vecchi
    Journal of Cosmology and Astroparticle Physics 2024.09 (2024): 005

    DOI: 10.1088/1475-7516/2024/09/005
  • Signal-background separation and energy reconstruction of gamma rays using pattern spectra and convolutional neural networks for the Small-Sized Telescopes of the Cherenkov Telescope Array
    J. Aschersleben, T. T. H. Arnesen, R. F. Peletier, M. Vecchi, C. Vlasakidis, M. H. F. Wilkinson
    Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 1059 (2024): 168942

    DOI: 10.1016/j.nima.2023.168942
  • eROSITA spectro-imaging analysis of the Abell 3408 galaxy cluster
    J. Iljenkarevic, T. H. Reiprich, F. Pacaud, A. Veronica, B. Whelan, J. Aschersleben, K. Migkas, E. Bulbul, J. S. Sanders, M. E. Ramos-Ceja, T. Liu, V. Ghirardini, A. Liu, T. Boller
    Astronomy & Astrophysics 661 (2022): A26

    DOI: 10.1051/0004-6361/202141411
  • X-ray studies of the Abell 3158 galaxy cluster with eROSITA
    B. Whelan, A. Veronica, F. Pacaud, T. H. Reiprich, E. Bulbul, M. E. Ramos-Ceja, J. S. Sanders, J. Aschersleben, J. Iljenkarevic, K. Migkas, M. Freyberg, K. Dennerl, M. Kara, A. Liu, V. Ghirardini, N. Ota
    Astronomy & Astrophysics 663 (2022): A171

    DOI: 10.1051/0004-6361/202141621
  • The Abell 3391/95 galaxy cluster system-A 15 Mpc intergalactic medium emission filament, a warm gas bridge, infalling matter clumps, and (re-) accelerated plasma discovered by combining SRG/eROSITA data with ASKAP/EMU and DECam data.
    T.H. Reiprich, A. Veronica, F. Pacaud, M.E. Ramos-Ceja, N. Ota, J. Sanders, M. Kara, T. Erben, M. Klein, J. Erler, J. Kerp, D.N. Hoang, M. Brüggen, J. Marvil, L. Rudnick, V. Biffi, K. Dolag, J. Aschersleben, K. Basu, H. Brunner, E. Bulbul, K. Dennerl, D. Eckert, M. Freyberg, E. Gatuzz, V. Ghi Käfer, A. Merloni, K. Migkas, K. Nandra, P. Predehl, J. Robrade, M. Salvato, B. Whelan, A. Diaz Hernandez-Lang, A. Zenteno, M.J.I. Brown, J.D. Collier, J.M. Diego, A.M. Hopkins, A. Kapinska, B. Kor Mroczkowski, R.P. Norris, A. O'Brien, E. Vardoulaki
    Astronomy & Astrophysics 647 (2021): A2

    DOI: 10.1051/0004-6361/202039590

Projects

Below a few project that I've developed at work or during my spare time in the past few years. More details are available on my -page.

damspi logo

DAMSPI

Software to calculate dark matter spikes around intermediate mass black holes

chessai logo

CheckmAIte

A chess engine based on a convolutional neural network

PSNet logo

PSNet

A convolutional neural network for the analysis of gamma-ray data

Daily paper logo

Daily Paper

A software that searches and opens papers on arXiv that were uploaded on the previous day based on your keywords

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