Two innovative research projects launched in Open Competition Science-M

News - 25 January 2022 - Communication

The NWO Domain Board Science has accepted 17 applications in the Open Competition Domain Science-M programme. Two of these fortunate scientists work at the Faculty of Electrical Engineering, Mathematics and Computer Science: Maksim Kitsak will do mathematical research into complementarity, by looking at the probability of individual parts of a network connecting. Frank Redig will research the mutual behaviour of particles in non-Euclidean space – for example proteins across a cell membrane.

Complementarity in complex networks

Complementarity is key in many crucial processes: successful teams consist of players with complementary skills, interacting molecules often have complementary interfaces and words in a sentence complement each other to convey a statement. In short: wherever connections can be made, complementarity comes into play. Maksim Kitsak investigates mathematical methods to find rules of complementarity – are there general laws behind complementarity? – in real network systems. The project will not only develop these theories of complementarity but also devise computational algorithms to learn complementarity representations of real networks, primarily in domains of Biomedicine and Science of Science.

Interacting particles in non-Euclidean space

The collective behaviour of a large number of particles in a curved space is shrouded in mystery. One of the main questions is how from the collective motion of the particles can be derived from a relatively simple partial differential equation for the particle density. For example, one can think of the movement of a large number of proteins across a cell membrane. That is the first part of the research. The second part of the project is about the evolution of curvature itself. Here, the specific challenge is how a natural equation for a time-dependent geometry, the so-called Ricci flow, can be understood from a microscopic model of time-dependent, weighted graphs.

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