I am a final year PhD researcher at Comenius University in Bratislava. My dissertation is "Artificial Intelligence for Data-Driven Business Decision-Making".
I develop explainable AI-tools and methods for data analysis that support human decision-making.
I am also preparing to transition into longevity research, with a focus on computational biology and aging-related data analysis.
My current research interests include:
- developing new data analysis or AI methods
- Explainable AI systems
- Machine learning
- AI workflow automation
- AI for business decision-making
- Decision support systems
- Longevity research
- Computational biology
- Epigenetic reprogramming
- Neural Semantic Retrieval Manifold (NSRM) for Sustainable Document-Centric Decision Making
- It is a novel AI-based retrieval approach that reconceptualizes document retrieval as a dynamic process of semantic navigation.
- Funded by an internal young researchers grant.
- Allocating AML Analyst Attention: An Explainable Ranking System for Suspicious Transaction Graphs
- This paper presents an explainable AI-driven AML triage system that ranks, explains, and prioritizes suspicious blockchain transaction subgraphs under limited analyst review capacity.
- A Proposal for AI-Driven Method for Strategic Business Decision-Making
- This paper proposes using AI to improve the business decision-making process, implemented within the Dara framework using the CausalNex model and integrating the interpretation of model results via ChatGPT-4.
- Data Analysis Methods Encyclopedia
- A comprehensive encyclopedia of data analysis methods that systematically documents classical, modern, emerging, and experimental approaches across data science, AI, business, bioinformatics, and quantum computing, while providing a foundation for discovering and inventing new hybrid methods.
ticina1@uniba.sk
evaticina@gmail.com
ORCID: https://orcid.org/0009-0004-2478-4054
LinkedIn: https://sk.linkedin.com/in/eva-ticina-088a04206