Armin Kekić

Armin Kekić

PhD Student in Causality and Machine Learning

Welcome to my website!

I’m a PhD Student at the Max Planck Institute for Intelligent Systems, specializing in integrating causal inference and reasoning into machine learning algorithms.

Prior to my PhD, I worked as an applied scientist at Zalando, where I developed machine-learning-based demand forecast models for price optimization.

My academic background includes studies in physics and applied mathematics at Heidelberg, Oxford, and Paris, with a specific focus on theoretical quantum dynamics and simulation methods.

On this website, I share projects that I work on.

Download my cv.

  • Machine Learning
  • Causality
  • Time Series Forecasting
  • Network Science
  • MSc in Applied Mathematics, 2016

    University of Oxford

  • BSc in Physics, 2015

    University of Heidelberg

Recent Publications

Quickly discover relevant content by filtering publications.
(2023). Evaluating vaccine allocation strategies using simulation-assisted causal modeling. Cell Patterns.

PDF Cite Code Poster Slides DOI

(2023). Causal Component Analysis. arXiv.


(2023). Deep Learning based Forecasting: a case study from the online fashion industry. arXiv.


(2023). On the DCI Framework for Evaluating Disentangled Representations: Extensions and Connections to Identifiability. ICLR.

PDF Cite Code DOI

(2022). A Network Approach to Atomic Spectra. arXiv.



PhD Student
Sep 2021 – Present Tübingen, Germany
Working on Causality and Machine Learning.
Applied Scientist
Feb 2018 – Aug 2021 Berlin, Germany
Development of high-dimensional time series models based on deep neural networks that are used for algorithmic price optimisation.
Mar 2017 – Jan 2018 Heidelberg, Germany
Research on spectroscopic networks.
Research Intern
Jul 2014 – Sep 2014 Singapore
Design of an optical set-up for Rydberg-atom imaging using electromagnetically induced transparency.