«Complexity on socio- techno- economic systems»

Prof. Dr. Claudio J. Tessone , Assistant Professor for Network Science

at the University of Zurich (Faculty of Economics, Business Administration and Information Technologies), where he also serves as co-director of the University Priority Programme on Social Networks. He holds a Masters and PhD in Physics, where he studied stochastic processes and the role of heterogeneity in complex, interacting systems. Prior to his current appointment, he was senior researcher at the Chair of Systems Design of the Department of Management, Economics and Technology at ETH Zurich, where he obtained a Habilitation on “Complex socio-economic systems”. He is an expert in the modelling of economic, social and technical systems from a quantitative and interdisciplinary perspective and has more than 60 papers in diverse areas. His current research focuses on complex socio-economic systems: formal and informal organisations, their communication and knowledge exchange, by means of theoretical models, the development of methodological tools and data analysis. Another research line focuses on blockchain and Bitcoin, specifically in the economic and technical aspects of these groundbreaking technology: Emergent economic patterns, apparent and hidden incentive schemes, the design of new systems, design of decentralised, scalable architecures

Title

Authors

Area

Year

A Taxonomy of Blockchain Technologies: Principles of Identification and Classification

Tasca, Paolo / Tessone, Claudio Juan

Networks and Enterprises

2019

Nestedness in complex networks: Observation, emergence, and implications

Abel, et al.

Networks and Enterprises

2018

Nestedness Maximization in Complex Networks through the Fitness-Complexity Algorithm

Claudio, et al.

Networks and Enterprises

2018

Quantifying knowledge exchange in R&D networks: a data-driven model

Claudio Juan, et al.

Networks and Enterprises

2018

Link Prediction in Bipartite Nested Networks

Claudio, et al.

Networks and Enterprises

2018

Identification of influencers through the wisdom of crowds

Algesheimer, et al.

Networks and Consumers

2018

Revealing in-block nestedness: Detection and benchmarking

Albert, et al.

Networks and Enterprises

2018

Social influence: identification, effect and extensions (Dissertation)

Algesheimer, et al.

Networks and Consumers,
Networks and Society

2018

Three essays on social network theory (Dissertation)

Abel, et al.

Networks and Consumers

2018

Analysing the sensitivity of nestedness detection methods

Alexander, et al.

Networks and Enterprises

2017

Hierarchical benchmark graphs for testing community detection algorithms

Claudio Juan, et al.

Networks and Consumers

2017

Detecting Nestedness in Graphs (Conference paper)

Alexander, et al.

Networks and Enterprises

2016

A Comparative Analysis of Community Detection Algorithms on Artificial Networks

Algesheimer, et al.

Networks and Consumers

2016

A model of dynamic rewiring and knowledge exchange in R&D networks

Claudio J., et al.

Networks and Enterprises

2016

Hierarchical mutual information for the comparison of hierarchical community structures in complex networks

caldarelli, et al.

Networks and Enterprises

2015

The effect of R&D collaborations on firms’ technological positions

Claudio Juan, et al.

Networks and Enterprises

2015