Henri Riihimäki

Henri Riihimäki

WINQ Fellow

Complex Systems

Office 6311

henri.riihimaki@su.se

About

WINQ research fellow. My research is in topological data analysis, and in particular developing methods to understand both biological and artificial neural networks. I'm also trying to explore connections between networks and quantum information.

"Hochschild homology, and a persistent approach via connectivity digraphs."

Caputi, L.; Riihimäki, H.. Journal of Applied and Computational Topology (2024).

"On reachability categories, persistence, and commuting algebras of quivers."

Caputi, L.; Riihimäki, H.. Theory and Applications of Categories (2024).

"Simplicial q-Connectivity of Directed Graphs with Applications to Network Analysis."

Riihimäki, H.. SIAM Journal on Mathematics of Data Science (2023).

"An application of neighbourhoods in digraphs to the classification of binary dynamics."

Conceição, P.; Govc, D.; Lazovskis, J.; Levi, R.; Riihimäki, H.; Smith, J. P.. Network Neuroscience (2022).

Exploring graph theory in quantum entanglement

Review on complex quantum networks

Topological data analysis of complex networks

Topology of the configuration model