Flaviu Cipcigan

My research aims to connect artificial intelligence with science. I am motivated by open challenges in healthcare and energy, such as design of antimicrobial peptides and molecules or porous solids that capture carbon dioxide.

Methodologicaly, I am interested in probabilistic machine learning, self-supervised learning, geometric learning, knowledge representation, reasoning, energy-based modelling, decision making under uncertainty and symbolic learning.

I work as a Staff Research Scientist at IBM Research in Accelerated Discovery. There I also:

I hold a PhD in physics from the University of Edinburgh. In my thesis, I built electronically coarse-grained water and showed it predicts water behaviour throughout its phase diagram. These results established electronic coarse-graining as arguably the most powerful Hamiltonian for accurate and efficient modeling of forces between molecules.

Besides research, I dance tango, co-founded a volunteering organisation, wrote about the connection between science and art, worked on algorithmic music composition and collaborated with artists to build a glass sculpture expressing my research.

My work has been recognised, with awards such as Forbes 30 under 30, 2021 Pat Goldberg Award (selected out of thousands), two IBM Research Accomplishmets and a journal cover. My PhD was shortlisted for a national prize. I also won multiple presentation awards.

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