Andrei Buliga

About
The research project of Andrei Buliga at the Weizenbaum Institute will focus on developing context-aware counterfactual explanation methods, with the objective of integrating control-flow dependencies with the data payload of the events within a trace or the process to ensure realistic counterfactual explanations. Such an approach would ensure that counterfactuals propose realistic, structurally valid changes, enhancing the reliability and interpretability of predictions.
Andrei Buliga is a PhD student with the Free University of Bozen-Bolzano (unibz) and Fondazione Bruno Kessler (FBK) in Italy. His interests include: Multidimensional Process Mining, Symbolic and sub-symbolic AI techniques for Process Mining, Explainable and verifiable AI. He has published works in top Process Mining conferences such as CAiSE, BPM, and ICPM on the topics presented above.
Stay at the Weizenbaum Institute in the research group: Security and Transparency of Digital Processes from 02.12 - 13.12.2024.
Fields of Research
Andrei Buliga conducts research on:
- Explainable AI
- Predictive Process Monitoring
- Process Mining