Jann Aschersleben

About me

I'm a Physics PhD student at the University of Groningen working on dark matter searches under the application of machine learning methods with the H.E.S.S. and CTA experiments.

• Physicist & Astronomer
  
• Data Analyst & Software Developer
  
• Machine Learning Expert
  

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

A summary of my CV is listed below. My full CV is available here.

Work Experience

Since 2020: PhD, Physics
Thesis title: Application of Artificial Neural Networks for Dark Matter searches around Intermediate Mass Black Holes with H.E.S.S. and CTA
University of Groningen, 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

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
NumPy, Pandas, Scipy, PySpark

Operating Systems
macOS, Linux, Windows

Miscellaneous
Git/GitLab, LaTex, Microsoft Office

Languages

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

Publications

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

• 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
  Submitted to NIM-A (2023)
  arXiv:2307.05301
• 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

Software to calculate dark matter spikes around intermediate mass black holes

CheckmAIte

A chess engine based on a convolutional neural network

PSNet

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

Daily Paper

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

Contact

Email
j.j.m.aschersleben@rug.nl

Address
Jann Aschersleben
Faculty of Science and Engineering Astronomy Institute
Kapteyn Astronomical
Landleven 12 (room 0192)
9747 AD Groningen
The Netherlands

• GitHub
• linkedin
• orcid
• google
• firefox-browser

Elements

i = 0;

while (!deck.isInOrder()) {
    print 'Iteration ' + i;
    deck.shuffle();
    i++;
}

print 'It took ' + i + ' iterations to sort the deck.';