My research in this role focuses on developing data science and AI-based solutions and implementing and preparing applied research projects. The main topics include optimization models (heuristics), AI and Machine Learning solutions and the explainability of these models. Furthermore, I work with Fraud Analytics, developing IoT pipelines, and Virus/Influence/Churn modeling.

Optimization Data ScienceIoT Development Applied Research Project Proposals

In this role, I have an ongoing postdoc project focusing on epidemiological modeling and public transport optimization. I am also involved in the NEBAP project and am responsible for digitalization and data science-related issues. In previous years, I mentored students through their Master's studies and led learning groups in Functional programming.

In this role, I lead and develop the company's main advanced analytics modules in the frame of a Business Intelligence Analytics agile project. The modules I am involved in are price strategy optimization, sales performance prediction, sales rep optimization, and analysis of user behavior, medicine, and blood pressure data in the HABITA mobile application.

My work was focused on managing the company's subcontractors, working on ongoing projects, supervising the development of a fraud detection system, and pitching the company's services and solutions to investors and industrial actors.

I developed a significant part of a fraud detection system which we later deployed at a prominent Hungarian financial institute. I was also involved in developing reporting systems and ML/AI models for both financial institutions and insurance companies.

I participated in various industrial R&D projects, implemented and delivered an IOS mobile application supporting public transportation route planning for passengers, and was involved in different optimization-related projects delivered to public transportation companies.