Simon Garnier

Assistant Professor, College of Science and Liberal Arts New Jersey Institute of Technology

  • Newark NJ

Professor Garnier focuses on the study of collective behaviors and swarm intelligence in natural and artificial systems

Contact

New Jersey Institute of Technology

View more experts managed by New Jersey Institute of Technology

Media

Social

Biography

As principle Investigator of the Swarm Lab, Garnier performs interdisciplinary research that studies the mechanism underlying the coordination of large animal groups, such as any colonies or human crowds.

Garnier has a substantial record in academic research and scientific communication. Garnier has broad experience in all aspects of data analysis, behavioral studies and teaching. He is interested in academic and corporate work involving the analysis of behavioral data and the development of applications for the study of large scale behaviors in animal groups, collective robotics and/or human social networks.

Areas of Expertise

Biological Sciences
Swarm Robotics
Interdisciplinary Education
Collective Behavior
Swarm Intelligence
Artificial Intelligence

Accomplishments

DARPA Young Faculty Award

June 2019

Education

Université Paul Sabatier (Toulouse III)

Ph.D.

Behavioral Science, Swarm Intelligence

2008

Université Paul Sabatier (Toulouse III)

M.S.

Neuroscience, Behavior and Cognition

2004

Université Bordeaux II

B.S.

Biochemistry, Cellular Biology and Physiology

2002

Affiliations

  • Swarm Lab
  • Entomological Society of America
  • The Swarm Intelligence - Editor

Languages

  • English
  • French

Media Appearances

Striking Down the Queen Won’t Save You From the Swarm

The New York Times  

2019-05-14

It’s a common trope in science fiction, but hives in nature are not dependent on any central node for their function.

If you’ve watched any science fiction or fantasy movies in the last few decades, you’ve probably seen the following scenario play out enough times that the next paragraph shouldn’t count as a spoiler...

View More

How slime mold could shape the future of self-driving cars

The Verge  

2018-05-01

Here, assistant professor Simon Garnier studies decentralized systems like colonies of ants — or petri dishes filled with slime mold — to figure out how these organisms make decisions and solve problems together. That’s what’s called “swarm intelligence,” and in the future, this kind of information could help us design an algorithm to create a more efficient network of self-driving cars.

If you want to learn more about slime mold, watch the video above. We joined Garnier in the lab to re-create a famous slime mold experiment, and we even tasted some right out of the petri dish. (Spoiler: it tasted like moss.) Not that we walked into his lab with the idea of eating some stinky, unicellular organism. But we had to give it a try after Garnier said: “It tastes like... have you ever licked the floor?”...

View More

Slime mold gives insight into intelligence of neuron-less organisms

ScienceDaily  

2016-06-08

"Working with Physarum constantly challenges our preconceived notions of the minimum biological hardware that is required for sophisticated behavior," says Simon Garnier, an assistant professor of biology at NJIT and the principal investigator of the study...

View More

Show All +

Event Appearances

We the Swarm: lessons in problem-solving from tiny brains and neuron-less creatures

In Entomology Colloquium  University of Illinois at Urbana-Champaign

2019-02-11

Not so smart after all: How to solve problems with no neurons and too many brains

In Coffee @ Beyond  Arizona State University

2018-10-29

From Blob to Mob: my random walk through complex systems

In Collective Behavior Seminar Series  Max Planck Institute for Ornithology and Konstanz University, Germany

2018-07-19

Show All +

Research Grants

No Brainer: Cognitive-like Behaviors in a Unicellular Slime Mold

National Science Foundation

2016-07-01

The proposed project will set up a comprehensive experimental and theoretical framework that can be used beyond the scope of this project to study decision-making in other neuron-less organisms and to establish comparisons with brained animals, thereby advancing our comprehension of the emergence of cognitive processes in biological systems...

View more

Encouraging Data Sharing and Reuse in the Field of Collective Behavior through Hackathon-Style Collaborative Workshops

National Science Foundation

2018-10-01

The investigators will bring together diverse researchers who work in the field of collective and emergent behavior. Collective and emergent behavior is the study of complex biological and social systems, ranging from bacterial colonies to human groups. The hackathon-style workshop draws researchers around identifying best practice mechanisms for sharing data, communicating methods of data analysis, and reusing publicly available data. The investigators propose a series of two workshops where teams of 2-5 participants work on a specific project during the duration of the 3-day event. An objective of the workshop is to foster novel collaborations between researchers in biology, data science, mathematics, computer science and physics, all of whom have an interest in collective behavior.

View more

Articles

Stability and Responsiveness in a Self-Organized Living Architecture

PLOS: Computational Biology

Simon Garnier, Tucker Murphy, Matthew Lutz, Edward Hurme, Simon Leblanc, Iain D. Couzin

2013-03-28

Robustness and adaptability are central to the functioning of biological systems, from gene networks to animal societies. Yet the mechanisms by which living organisms achieve both stability to perturbations and sensitivity to input are poorly understood. Here, we present an integrated study of a living architecture in which army ants interconnect their bodies to span gaps. We demonstrate that these self-assembled bridges are a highly effective means of maintaining traffic flow over unpredictable terrain. The individual-level rules responsible depend only on locally-estimated traffic intensity and the number of neighbours to which ants are attached within the structure. We employ a parameterized computational model to reveal that bridges are tuned to be maximally stable in the face of regular, periodic fluctuations in traffic. However analysis of the model also suggests that interactions among ants give rise to feedback processes that result in bridges being highly responsive to sudden interruptions in traffic. Subsequent field experiments confirm this prediction and thus the dual nature of stability and flexibility in living bridges. Our study demonstrates the importance of robust and adaptive modular architecture to efficient traffic organisation and reveals general principles regarding the regulation of form in biological self-assemblies

View more

Do Ants Need to Estimate the Geometrical Properties of Trail Bifurcations to Find an Efficient Route? A Swarm Robotics Test Bed

PLOS: Computational Biology

Simon Garnier, Maud Combe, Christian Jost, Guy Theraulaz

2013

Interactions between individuals and the structure of their environment play a crucial role in shaping self-organized collective behaviors. Recent studies have shown that ants crossing asymmetrical bifurcations in a network of galleries tend to follow the branch that deviates the least from their incoming direction. At the collective level, the combination of this tendency and the pheromone-based recruitment results in a greater likelihood of selecting the shortest path between the colony's nest and a food source in a network containing asymmetrical bifurcations...

View more

Individual rules for trail pattern formation in Argentine ants (Linepithema humile)

PLOS: Computational Biology

Andrea Perna, Boris Granovskiy, Simon Garnier, Stamatios Nicolis, Marjorie Labédan, Guy Theraulaz, Vincent Fourcassié, David Sumpter

2012

We studied the formation of trail patterns by Argentine ants exploring an empty arena. Using a novel imaging and analysis technique we estimated pheromone concentrations at all spatial positions in the experimental arena and at different times. Then we derived the response function of individual ants to pheromone concentrations by looking at correlations between concentrations and changes in speed or direction of the ants...

View more

Show All +