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.
Interests
- Machine Learning
- Causality
- Time Series Forecasting
- Network Science
Education
-
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.
(2023).
Causal Component Analysis.
arXiv.
(2023).
On the DCI Framework for Evaluating Disentangled Representations: Extensions and Connections to Identifiability.
ICLR.
(2022).
A Network Approach to Atomic Spectra.
arXiv.
Experience
Applied Scientist
Development of high-dimensional time series models based on deep neural networks that are used for algorithmic price optimisation.
Research Intern
Design of an optical set-up for Rydberg-atom imaging using electromagnetically induced transparency.