Community

Yifei Wang Member since: Saturday, February 25, 2017 Full Member Reviewer

Ph.D in Computing, M.Eng. in Astronautics Engineering, B.Eng. Computer Science & Technology

Eileen Young Member since: Tuesday, September 10, 2019 Full Member

B.S., Liberal Studies, University of Wisconsin - Whitewater, M.S., Disaster Science and Management, University of Delaware

Graduate student in Disaster Science and Management at the University of Delaware.

Smarzhevskiy Ivan Member since: Sunday, August 17, 2014 Full Member Reviewer

Associate professor of chair of economics and mathematical methods

Smarzhevskiy Ivan, born 1961, graduated from the Faculty of Mechanics and Mathematics of Moscow State University in 1983. Candidate of Economic Sciences since 2000. Smarzhevskiy Ivan is currently a lecturer in the magistracy of the Peoples’ Friendship University of Russia.

Research interests: individual and collective behavior in the organization, decision making, sociology of small groups.

decision making, sociology of small groups, agent based models

Tarik Hadzibeganovic Member since: Tuesday, August 09, 2022

Tarik Hadzibeganovic is a complex systems researcher and cognitive scientist interested in all challenging topics of mathematical and computational modeling, in both basic and applied sciences. His particular focus has been on several open questions in evolutionary game theory, behavioral mathematical epidemiology, sociophysics, network theory, and episodic memory research. When addressing these questions, he combines mathematical, statistical, and agent-based modeling methods with laboratory behavioral experiments and Big Data analytics.

Paul Van Liedekerke Member since: Thursday, May 31, 2018

Interested in numerical models and new conceptual ideas, applications from industry to medicine.

I focus on numerical modeling of mechanics of solid materials and cell mechanics. The models that I developed so far address granular matters, bio-fluids, cellular tissues, and individual cells.

I further develop Agent-based Models, which are methods to predict collective behavior from individual dynamics controlled by rules or differential equations. Examples: tumor growth, swarms, crowd movement.

The methods I used are Particle-based methods which offer great flexibility within physical modeling, and can operate in a large range of scales, from atomistic scales (e.g. Molecular Dynamics) to continuum approaches (e.g. Smoothed Particle Hydrodynamics).

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