Giann Karlo

I am currently:


I earned a B.Sc. (BAC+5) degree in Computer Science and Engineering, and a B.Sc. (BAC+5) degree in Biology from the Pontificia Universidad Javeriana (Cali). My main research interests are in Systems Ecology and Biology, Machine Learning, Concurrency, Algorithms, and Climate Change.


I am involved in the ESCAPE project (EcoSystem Causal Analysis using PEtri Net Unfoldings) whose goal is to design and implement data structures and algorithms that: (1) permit a representation of ecosystem dynamics to provide a causal and possibilistic exaplanation, and (2) find bifurcation points (tipping points) that lead to different ecosystem fates like collapse or stability. For this endeavor I use read and reset arcs plus the traditional production and consumption arcs in Petri nets. Besides, I developed a software called Ecofolder for a graphic representation of the unfolding procedure.

PhD Defense

Title : Ecosystem Causal Analysis using Petri Net Unfoldings.
Keywords : Concurrency, Causal analysis, Rule systems, Discrete event systems, Unfoldings.


Many verification problems for concurrent systems have been successfully addressed by various methods over the years, particularly Petri net unfoldings. However, questions of long-term behavior and stabilization have received relatively little attention. For instance, crucial features of the long-term dynamics of ecosystems, such as basins of attraction and tipping points, remain difficult to identify and quantify with good coverage. A central reason for this is the focus, in ecological modeling, on continuous models, which provide refined simulations but do not generally allow a survey of how the system evolution would be altered under additional events or in otherwise different situations. In this work, we aimed to provide a toolkit for modeling and analyzing ecosystem dynamics. We advocate for safe contextual reset Petri nets for modeling since they have the potential to give an exhaustive possibilistic overview of the different feasible evolution scenarios. The unfolding of Petri nets provides us with the right tools to determine system trajectories leading to collapse or survival and eventually characterize those actions or inactions that help to support ecosystem stabilization. This characterization of the token’s production/consumption was used to separate minimally doomed configurations from free ones, meaning executions leading inevitably to the system’s collapse even though these executions are not identified a priori as bad ones and executions that keep the system stable, excluding bad or doomed states, respectively. The unfolding of safe reset nets and the algorithmic part for finding minimally doomed configurations have been successfully implemented in a software tool called Ecofolder and tested with some intriguing examples.


  • Alain Denise, Professor, Université Paris-Saclay (President)
  • Dimitri Lefebvre, Professor, Université Le Havre Normandie (Reviewer)
  • Madalena Chaves, INRIA Senior Scientist, Inria d’Université Côte d’Azur (Reviewer)
  • Cédric Lhoussaine, Professor, Université de Lille (Examiner)
  • Jérôme Feret, Associated Professor, ENS Paris (Examiner)
  • Franck Pommereau, Professor, Université d’Évry (Co-supervisor)
  • Stefan Haar, INRIA Senior Scientist, Inria Saclay (Thesis director)


  • Aguirre-Samboní G, Haar S, Paulevé L, Schwoon S and Würdemann N. Avoid One’s Doom: Finding Cliff-Edge Configurations in Petri Nets. GandALF 2022: Games, Automata, Logics, and Formal Verification, Sep 2022, Madrid, Spain. pp. 178--193.
  • Aguirre-Samboní G, Guacherel C, Haar S and Pommereau F. Reset Petri Net Unfolding Semantics for Ecosystem Hypergraphs. International Workshop on Petri Nets and Software Engineering (PNSE 2022), Jul 2022, Bergen, Norway. pp. 213--214.
  • Aguirre-Samboní G, Haar S, Paulevé L, Schwoon S and Würdemann N. Protection against doom and why fairness may not help you.
    In preparation.
  • Aguirre-Samboní G, Haar S, Paulevé L and Schwoon S. Regimes of Biological Networks.
    In preparation.
  • More.


For research purpose or other subjects, please contact me at: giann-karlo [dot] aguirre-samboni [at] inria [dot] fr

I have another website: Giann Karlo