M.Sc. Thesis, Maastricht University
Optimization of Inverter Placement and Cable Routing for Distributed Inverter Topologies in Solar Plants
D. Verșebeniuc
Supervised by M. Mihalák
AI researcher & engineer
M.Sc. in Artificial Intelligence
I build evaluations and research tools to understand how AI systems behave. My goal is to make them trustworthy and secure by design. My background spans research, full-stack engineering, and entrepreneurship.
My current focus is detecting reward hacking: when an agent earns reward without doing the intended task.
I’m open to research collaborations and PhD opportunities in AI security.
Current focus
Detecting agents that exploit an evaluation or reward signal instead of completing the intended task.
Conceptual illustration: The intended path earns reward by completing the task. An exploit reaches the reward without satisfying the task; a monitor inspects this behaviour.Exploring
Repeatedly testing whether safety protocols hold up when an agent deliberately tries to subvert them.
Conceptual illustration: An untrusted agent attacks a safety protocol in repeated adversarial tests. Separate held-out monitors check whether the defences generalise.Exploring
Exploring non-agentic systems that explain evidence, express uncertainty, and assess risk as guardrails.
Conceptual illustration: Evidence informs a Bayesian world model with multiple plausible explanations. Inference combines those explanations into uncertain predictions, without an action loop.M.Sc. Thesis, Maastricht University
D. Verșebeniuc
Supervised by M. Mihalák
MDPI, Electronics
A. Härmä, A. Al-Saeedi, A. Changalidis, D. Verșebeniuc, M. Pietrasik, A. Wilbik
Preprint
D. Verșebeniuc, A. Härmä
BNAIC/BeNeLearn 2024 · Post-proceedings in Springer CCIS · Oral Session
D. Verșebeniuc, M. Elands, S. Falahatkar, C. Magrone, M. Falah, M. Boussé, A. Härmä
B.Sc. Thesis, Maastricht University
D. Verșebeniuc
Supervised by J. Spanakis, M. Ntekouli
Sep 2023 – Aug 2026
Sep 2020 – Jun 2023
Dumitru Verșebeniuc is an AI security researcher and engineer building evaluations and tools to detect reward hacking and make AI systems trustworthy by design.
Research, qualifications, and collaboration interests are documented in my research summary. See my publications, ORCID profile, and Google Scholar profile for source material.