Luc Tortike

I am passionate about AI, tech, and automating things. I enjoy programming, logical thinking, and tinkering with new tools. Alongside the more technical side, I bring strong social skills and enjoy working with people, so feel free to reach out!


Experience

Mar 2024 – Present

Virtual Computing, Oisterwijk

AI/Cloud Engineer | Consultant | Senior Support Engineer Sep 2024 – Present

I solve complex IT challenges by handling support tickets and providing consultancy for more in-depth solutions. Additionally, I build automation workflows with n8n and develop AI agents that enhance efficiency and support our daily operations.

Junior Cloud Engineer Mar 2024 – Sep 2024

Nov 2021 – Feb 2024 TU/e logo

Eindhoven University of Technology, Eindhoven

Information Management and Services (IMS) - ICT desk Nov 2021 – Feb 2024

Provided IT support and troubleshooting for TU/e staff, assisting with hardware, software, and general ICT issues.

Python Programming Tutor Sep 2023 – Nov 2023

Python Programming Tutor Sep 2022 – Nov 2022

Apr 2020 – Aug 2020 Stamhuis logo

Stamhuis

Orderpicker Apr 2020 – Aug 2020

Jun 2019 – Dec 2019

Gimeg Nederland B.V.

Orderpicker Jun 2019 – Dec 2019

Education

Sep 2024 – Present TU/e logo

MSc. Data Science & Artificial Intelligence

Eindhoven University of Technology

Erasmus Exchange semester 'MSc Data Science and Engineering' at Instituto Superior Técnico, Lisbon (Feb 2025 – Jul 2025)

Sep 2020 – Feb 2024 TU/e logo

BSc. Psychology & Technology – ICT track

Eindhoven University of Technology

Sep 2013 – Jun 2019 Gerrit Rietveld College logo

VWO (N&T + N&G profile)

Gerrit Rietveld College, Utrecht

Publications

2025
C.V. Heinrich, T. Lombarts, J. Mallens, L. Tortike, D. Wolf & W. Duivesteijn
Local Subgroup Discovery on Attributed Network Graphs — Springer Nature, 2025

We explore how to identify locally exceptional subgroups in attributed graphs by combining both node attributes and structural information. Instead of comparing behavior across the entire graph, we focus on how subgroups differ from a relevant local peer group. To do this, we rank nodes based on their similarity to a reference node. The method is demonstrated on three real world datasets.

Certificates

2025

MigrationWiz for Microsoft 365

BitTitan

2025

MigrationWiz for Sales

BitTitan

Contact

Feel free to shoot me a message!