My Academic Life

My research focus is on the intersection of Automated Machine Learning (AutoML), Automated Artificial Intelligence (AutoAI), and Time Series Analysis.

Selected Publications

Denoising Architecture for Unsupervised Anomaly Detection in Time-Series

Wadie Skaf and Tomáš Horváth
European Conference on Advances in Databases and Information Systems, 2022
DOI

Towards Automatic Forecasting: Evaluation of Time-Series Forecasting Models for Chickenpox Cases Estimation in Hungary

Wadie Skaf, Arzu Tosayeva, and Dániel T Várkonyi
International Conference on Intelligent Systems Design and Applications, 2022
DOI

Full list of publications can be found on Google Scholar

Academic Supervision

Current Students

Erfan Moeini

Master of Science (M.Sc.)
Informatik
RWTH Aachen University
2024 - Ongoing

Thesis Title

Minimizing the Gap between AutoML and Time Series Domain

Co-supervised with: Marie Anastacio

In collaboration with:
Volkswagen AG (Supervisor: Christopher Vox)

Jesse Kroll

Bachelor of Science (B.Sc.)
Data Science and Artificial Intelligence
Leiden University (Universiteit Leiden)
2024 - Ongoing

Thesis Title

Towards Robust Time Series Representation Learning

Co-supervised with: Mitra Baratchi

Simon Klemp

Master of Science (M.Sc.)
Informatik
RWTH Aachen University
2024 - Ongoing

Thesis Title

Automated Machine Learning (AutoML) for Feedback-Driven Optimisation of Time Series Anomaly Detection in Recycling Plants

In collaboration with:
Eggersmann Gruppe GmbH & Co. KG (Supervisors: Lukas Kreisköther, Sebastian Fedler)

Past Students

Elliot Johnson

Bachelor of Science (B.Sc.)
Informatik
RWTH Aachen University
2024 - 2025

Thesis Title

Studying the Relationship between Window Size and Other Hyperparameters in Deep Learning-based Time Series Forecasters

Mhyar Kousa

Master of Science (M.Sc.)
Computer Science
Eötvös Loránd University
2021 - 2022

Thesis Title

Hungarian Railways Passenger Traffic Analysis and Forecasting

Teaching

Academic Year 2024/2025

Summer Semester

Efficient Artificial Intelligence (AI) with Rust

EffAIRust • Lab • Graduate (Master)
RWTH Aachen University
Germany
Lead Instructor

This lab is designed to introduce students to the basics of Rust programming and its applications in artificial intelligence.

Main Topics

  • Introduction to Rust programming language
  • Implementing basic AI models and ML algorithms using Rust
  • Using Rust in combination with Python (PyO3) to accelerate ML workflows

Technologies

Rust Python PyO3

Instruction Languages

English

Academic Year 2023/2024

Summer Semester

Hyperparameter Optimisation for Machine Learning

HPOML • Lab • Graduate (Master)
RWTH Aachen University
Germany
Instructor

This lab is designed to introduce students to the basics of hyperparameter optimisation for machine learning.

Main Topics

  • Introduction to hyperparameter optimisation
  • Grid Search
  • Random Search
  • Successive Halving
  • Bayesian Optimisation

Technologies

Python Scikit-Learn Pandas NumPy SMAC

Instruction Languages

English

Academic Year 2022/2023

Summer Semester

Introduction to Data Science

ITDS • Lecture • Graduate (Master)
Eötvös Loránd University (ELTE)
Hungary
Teaching Assistant • Practical Section (Lab)

This course is designed to introduce students to the basics of data science.

Main Topics

  • Introduction to data science
  • Data cleaning and preprocessing
  • Classification
  • Regression
  • Clustering
  • Dimensionality Reduction
  • Recommender Systems
  • Natural Language Processing
  • Deep Learning

Technologies

Python Pandas Scikit-Learn PyTorch NumPy Matplotlib Seaborn Plotly SciPy

Instruction Languages

English