Research

PhD Research: (Artificial) Mind over Matter: Integrating Humans and Algorithms in Solving Matching Problems.

• My research is inherently interdisciplinary, combining state-of-the-art data science with the understanding of human behavior and intelligence.

• My main research contributions have been to model and design machine (deep) learning algorithms to advance matching problems research both methodologically and applicatively.

• Matching is at the heart of any process that integrates structured and semi-structured data with applications in a variety of domains including healthcare and digital economy.

• In my research I undertook the challenge of understanding the role of humans in the matching process, improving the human-in-the-loop in matching tasks and create improved Human–AI collaboration.