Stephane Bonneaud

Ph.D. computer science, artificial intelligence

Entrepreneur, 2014 - now

artificial intelligence, virtual reality, education

Head of development, 2015 - now

Creative Smarts Inc.

Co-inventor US patent #14/526,404 ; Int. #PCT/US2014/062668

Virtual Reality Methods and Systems. Brown U.

Entrepreneur

I am passionate with technologies that help focus and think. I want to use virtual reality and artificial intelligence to expand human cognition. Currently, I am also working with an educational venture on helping kids learn better.

At Brown, in parallel with my own research, I developed some of the core components of the VENLab software and lead its development team. From the drivers to the 3D experience, I coded most of the VR headset system that is now both nationally and internationally patented. This wireless VR system enabled back then anybody anywhere in the world to walk in shared simulations, see and interact with each others in real-time using body tracking and reconstruction. This experience transformed my academic focus and propelled me into the exciting challenges of entrepreneurship.

Researcher

I was lucky to achieve a rich academic journey in artificial intelligence. I studied many approaches, like complex system modeling, agent simulation, or machine learning. I worked in and with some of the best labs in the world on some of the most sophisticated systems, such as virtual reality headsets and robots. I learned to solve problems and became fond of the creative process. And, I was so thrilled to build innovative tools to help people understand or do something better.

I studied and designed artificial agents with a multidisciplinary approach in computer science, artificial intelligence, and cognitive science. I was particularly interested in perception-action systems that exhibit stable, yet flexible behavioral patterns, adapting to chaotic and dynamic environments while maintaining a goal-directed behavior. Understanding ubiquitous and apparently elementary behaviors, such as locomotion/navigation, can lead to more fundamental questions on human behavior and cognition.

Highlights

  • Human perception, visual-based locomotion, computer vision

    Post doctorate fellow, Serre’s lab, Brown University 2012-2013

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  • Human locomotion, crowd behavior, agent-based virtual reality

    Post doctorate fellow, VENLab Brown University 2009-2012

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  • Agent based modeling and simulation of complex systems

    Ph.D. artificial intelligence 2008

  • Master of artificial intelligence, Paris 6

    Master of cognitive science, Paris 11

© 2016, Stephane Bonneaud. All rights reserved.

Human perception, visual-based locomotion, computer vision

Post doctorate fellow, Serre’s lab, Brown University 2012-2013

The presentation of my projects reflects my interests. Please refer to the PI's communications, publications, or lab's webpages of these projects for more information.

Agent / Perception-Action Architecture

The aim of this project was to build a biologically-inspired vision system for the visual control of online steering in complex environments [Bonneaud et al. 2013]. We propose to use the mathematical psychology model of locomotor dynamics developed in the VENLab [Warren and Fajen 2008] coupled to the neurally plausible computational model developed in Serre's lab [Serre et al. 2007]. The computational vision model processes the visual information (simulated optic flow and stereo vision) to extract information on the environment for the locomotion model to steer the agent towards its goals while interacting with the other objects of the environment (e.g. avoid obstacles, walk along walls, or form groups).

Top figure shows four sub pictures: top-left subfigure is a first-person perspective of a virtual scene with different types of objects, and the top-right is a heat map showing the motion energy extracted by the vision model (S2 layers); bottom-left shows the ground-truth depth map and bottom-right the approximated depth map based on the motion energy. The bottom figure is a snapshot of a virtual world in which we run our agent using both the vision and the locomotion models.

This work is supported by the ONR grant #N000141110743 and Robert J. and Nancy D. Carney Fund for Scientific Innovation.

Collaborators: Pr. Thomas Serre, Youssef Barhomi (Serre's Lab, Brown Univ.); Pr. William H. Warren (VENLab, Brown Univ.).

  • Bonneaud, S., Warren, W.H., Olfers, K., Irwin, G., and Serre, T. (2013). Towards a biologically-inspired vision system for the control of locomotion in complex environments. VSS 2013 conference, Naples FL, 2013.
  • Warren, W. and Fajen, B. (2008). Behavioral dynamics of visually guided locomotion. In Fuchs, A. and Jirsa, V., editors, Coordination: Neural, Behavioral and Social Dynamics, vol.17 Journal of Experimental Psychology: Human Perception and Performance, 21: 996–1014.
  • Serre, T. and Oliva, A. and Poggio, T. (2007). A feedforward architecture accounts for rapid categorization. Proc. Nat. Academy of Science, 104(15): 6424-6429.

Human / Robot locomotion

The goal of this project is to port our perception-action model accounting for human locomotion to robotic platforms. To do that, we borrowed two turtlebots from Brown's RLab (P.I. Chad Jenkins) and have had access to their PR-2 robot. We want to show here that our model can be ported to ROS (Willow Garage) and that we can achieve human-like trajectories in space with a robot following a human.

Figure shows me confronted for the first time to the massive PR-2 of the RLab (Brown Univ.). Thanks to the WPI-RAIL lab members who let us visit them, as the PR-2 was at that time in their hands.

This work is supported by the ONR grant #N000141110743 and Robert J. and Nancy D. Carney Fund for Scientific Innovation.

Collaborators: Pr. Thomas Serre and Youssef Barhomi (Serre Lab, Brown Univ.); Pr. Chad Jenkins (RLab, Brown Univ.).

Human locomotion, crowd behavior, agent-based virtual reality

Post doctorate fellow, VENLab Brown University 2009-2012

The presentation of my projects reflects my interests. Please refer to the PI's communications, publications, or lab's webpages of these projects for more information.

Crowd / Agent Interactions

In this project, we try to model individual locomotor behavior in complex locomotor scenarios and self-organized behavior in crowds. I work on developing the dynamic model for online steering that is being developed in the VENLab [Warren 2008]. The model simulates the observed human paths, and in the case of obstacle avoidance, the routes selected around the obstacle. A current challenge is to scale the model to account for the dynamics of groups and crowds. Locomotion is here a case study to investigate the coupling of a perception-action system with its environment. Based on the dynamics of perception and action [Warren 2006, Kelso 1995, Beer 2000], we inquire how behavior can emerge as a stable solution of the system's dynamics (self-organization), which we call the behavioral dynamics [Warren 2006]. In crowds, the collective behavior also emerges from the interactions in the system agent(s)-environment, with the self-organizing pedestrians determining the group and the group partially enslaving the dynamics of the pedestrians.

Top figure shows 2 groups of 10 artificial agents walking towards each other. Middle figure shows artificial agents walking in a virtual corridor. Bottom figure shows a swarm of artificial agents. Snapshots from the locomotion multi-agent simulator, VENLab.

This work is supported by the NIH grant R01 EY010923.

Collaborators: Pr. William H. Warren, Kevin Rio, and Dr. Adam Kiefer (VENLab, Brown U.); Pr. Pierre Chevaillier (CERV/LISyC, France).

  • Beer, R. (2000). Dynamical approaches to cognitive science. Trends in Cognitive Sciences, 4: 91–99.
  • Bonneaud, S., Warren, W.H. (2012). Multi-agent simulation platform for the study of individual and crowd locomotor dynamics. (in preparation)
  • Bonneaud, S., Rio, K., Chevaillier, P., Warren, W. (2011). Accounting for patterns of collective be- havior in crowd locomotor dynamics for realistic simulations. In: Z. Pan, A. Cheok, W. Muller, M. Chang, M.E. Zhang (eds.) Transactions on Edutainment VII, LNCS, vol. 7145, pp. 1–12. Springer, Heidelberg.
  • Kelso, J. A. S. (1995). Dynamic patterns: the self-organization of brain and behavior, ch. Intentional dynamics, p.137–158. MIT Press.
  • Warren, W. (2006). The dynamics of perception and action. Psychological review, 113: 358–389.
  • Warren, W. and Fajen, B. (2008). Behavioral dynamics of visually guided locomotion. In Fuchs, A. and Jirsa, V., editors, Coordination: Neural, Behavioral and Social Dynamics, vol.17 Journal of Experimental Psychology: Human Perception and Performance, 21: 996–1014.

Agent Modeling and Multi-agent Simulation

I built this project to provide a relevant simulation framework for running virtual experiments with many agents in the VENLab's VR equipment. This simulation platform provides the lab with a multi-agent simulator to easily prototype new scenarios of locomotor dynamics using configuration files. The simulator supports real-time rendering simulations of navigating agents in virtual environments. A GUI enables to quickly design new scenarios based on the existing agent behavior library for multi-agent simulation in complex environments. The simulator also provides a modular computational framework for developers to easily add new behaviors for agents. The software relies on C++, POSIX, OpenGL, and X11/Win32 (cross-platform), and is based on the AReVi library.

Articles

2013

Stéphane Bonneaud, William H. Warren, Kerwin Olfers, Gerrit Irwin, and Thomas Serre.

Towards a biologically-inspired vision system for the control of locomotion in complex environments.

VSS 2013 Conference, Naples FL, May 2013.

Adam W. Kiefer, Stéphane Bonneaud, Kevin Rio, and William H. Warren.

Quantifying the Coherence of Pedestrian Groups.

35th Annual Conference of the Cognitive Science Society (IN PRESS).

2012

Stéphane Bonneaud and William H. Warren.

A behavioral dynamics approach to modeling realistic pedestrian behavior.

In the Proceedings of the PED'2012, the Int. Conference on Pedestrian and Evacuation Dynamics, Switzerland, June 2012.

Kevin Rio, Stéphane Bonneaud, and William H. Warren.

Speed coordination in pedestrian groups : Linking individual locomotion with crowd behavior.

Journal of Vision 12(9).

Stéphane Bonneaud, Pierre Chevaillier and William H. Warren.

Modélisation multi-agents de la locomotion collective de groupes de piétons.

In the Proceedings of the JFSMA'2012, Journées Francophones des Systèmes Multi-Agents, France, October 2012.

2011

Stéphane Bonneaud, Kevin Rio, Pierre Chevaillier and William H. Warren.

Accounting for patterns of collective behavior in crowd locomotor dynamics for realistic simulations.

In the journal LNCS Transactions on Edutainment (Springer).

2010

Stéphane Bonneaud and Pierre Chevaillier.

Analyse expérimentale des biais dans les simulations à base de populations d'agents (Experimental analysis of biases in the simulations of agents populations).

Revue d’Intelligence Artificielle, 2010, 24(5), 601-624.

2009

Gireg Desmeulles, Stéphane Bonneaud, Pascal Redou, Vincent Rodin, Jacques Tisseau.

In virtuo experiments based on the multi-interaction system framework : the RéISCOP meta-model.

CMES : Computer Modeling in Engineering & Sciences, 2009, 47, 299-330.

Pierre Chevaillier, Stéphane Bonneaud, Gireg Desmeulles, Pascal Redou.

Experimental Study of Agent Population Models with a Specific Attention to the Discretization Biases.

In the proceedings of the European Simulation and Modelling Conference ESM’09, UK, October, 2009, 323-331.

Mikael Bourhis, Gireg Desmeulles, Stéphane Bonneaud, Francois Guerrero, Vincent Rodin.

Data consistency in distributed virtual reality simulations applied to biology.

In the proceedings of the ICAS'09, The 5th Int. Conference on Autonomic and Autonomous Systems, Spain, April 20-25 2009.

Stéphane Bonneaud, Pascal Redou, Gireg Desmeulles, Pierre Chevaillier.

Biais computationnels dans les modèles de peuplements d’agents.

In the proceedings of the Journées Francophones sur les Systèmes Multi-Agents JFSMA'09, France, 2009, 145-154.

2007

Stéphane Bonneaud, Pierre Chevaillier.

Oriented pattern agent-based multi-modeling of exploited ecosystems.

In the proceedings of the 6th EUROSIM congress on modelling and simulation, Ljubljana, Slovenia, september 9-13, 2007, 7 pages.

Stéphane Bonneaud, Fabian Blanchard, Damien Thébault, Pierre Chevaillier, Pascal Redou.

A model of fish population dynamics based on spatially explicit trophic relationships.

In the proceedings of the ECEM'07, The 6th European Conference on Ecological Modelling, Italy, November 27-30 2007.

Stéphane Bonneaud, Pascal Redou, Damien Thébault, Pierre Chevaillier.

Multi-modélisation agent orientée patterns : Application aux écosystèmes exploités.

In the proceedings of the Journées Francophones sur les Systèmes Multi-Agents JFSMA'07, France, 17-19 octobre 2007, 119-128.
*Best Paper Award*.

2005

Stéphane Bonneaud, Gabriel Ripoche, Jean-Paul Sansonnet.

Toward an Empirical Schema-Based Model of Interaction for Embedded Conversational Agents.

In the proceedings of the Joint Symposium on Virtual Social Agents AISB 2005, UK, april 2005.

Jean-Paul Sansonnet, Stéphane Bonneaud, Gabriel Ripoche.

Modélisation et extraction de schémas dialogiques dans les traces d’interactions langagières des forges logicielles.

Workshop JSM'05, Journées Sémantique et Modélisation, Paris, march 2005.

2004

Stéphane Bonneaud, Gabriel Ripoche, Jean-Paul Sansonnet.

A Socio-Cognitive Model for the characterization of schemes of Interaction in Distributed Collectives.

In "Distributed Collective Practice : Building new Directions for Infrastructural Studies", Workshop of the CSCW 2004 conference, Chicago, nov 2004.

Daisuke Torii, Toru Ishida, Stéphane Bonneaud, Alexis Drogoul.

Layering Social Interaction Scenarios on Environmental Simulation.

78-88, Joint Workshop on Multi-Agent and Multi-Agent-Based Simulation MABS 2004, New York, USA, 2004.

Resume

Introduction

Throughout my academic and professional experience, I focused on modeling the interactions in the agent-environment and agent-agent systems. Computer scientist, specialized in artificial intelligence and multi-agent simulation, I have a multi-disciplinary training in cognitive science where I found helpful material to model behavior and societies of artificial agents.

In Ph.D., I applied my background in distributed artificial intelligence to the modeling of complex systems, such as large ecosystems with many interacting species in changing environments. I built a society of model-agents for modelers to interact with --build, analyze, and experiment-- their models in an intelligent virtual modeling environment [Bonneaud and Chevaillier 2007] and I implemented it in a multi-model multi-scale simulator.

At Brown, I focused on crowd dynamics and how interacting pedestrians build up collective self-organized phenomena [Bonneaud and Warren 2012]. I developed a multi-agent simulator that researchers now use to prototype human experiments and investigate through simulation various locomotor scenarios. I also designed and conducted experiments with human participants and investigated experimental questions [Bonneaud et al. 2011].

In 2012, I joined Serre Lab to pursue on expliciting the modeling of the visual experience of an artificial pedestrian [Bonneaud et al. 2013]. I investigated the human locomotor perception-action loop with Serre lab's vision model which accounts for the neural mechanisms responsible for extracting visual information from various visual cues coupled to the VENLab's locomotion model. The system was run in artificial worlds ~real time with GPU acceleration. And we trained the large-scale (108 units) neural network vision model on large artificial datasets. We then experimented with the system on robotic platforms using turtlebots and a PR-2.

Appointments

Sep 2012 (present)

Postdoctoral research associate

Serre Laboratory, Department of Cognitive, Linguistic and Psychological Sciences, Brown University, USA

Towards a biologically-inspired vision system for the control of locomotion in complex environments.

2009 - 2012

Postdoctoral research associate

Department of Cognitive, Linguistic and Psychological Sciences, Brown University, Providence RI 02906, USA

Pedestrian behavior and crowd dynamics, action selection, multiagent simulation.

Nov 2008 – Apr 2009

Postdoctoral research associate

Biodiversity project ANR-IFB 2005, European Center for Virtual Reality, France

2005 – 2009

Graduate student

Biodiversity project ANR-IFB 2005, European Center for Virtual Reality , France

Multi-modeling of complex ecological/economical systems in dynamical environments (PhD).

Apr – Sep 2004

Internship

Paris XI ORSAY, supervisor : J.P. Sansonnet

Modeling and extraction of action patterns in linguistic interactions.

Dec 2003

Part of the thinktank ”Participatory design of agent oriented simulations”

Apr - Nov 2003

Internship

Paris VI (France) / Kyoto University (Japan), supervisor : A. Drogoul

Integration of the Q language to the multiagent platforms CORMAS and SWARM, dev of a multiagent simulator for crisis scenarios.

Sep 2002

Internship

IRD, Dakar, Sénégal, supervisor : C. Cambier

Dev and network distribution of an agent simulator for biological populations.

Summer 2000

Internship

Stanford Linear Accelerator Center, CA, USA, supervisor : P. Kunz

C/C++ developer, GLAST project, DOE/NASA.

Summer 1998

Internship

Stanford Linear Accelerator Center, CA, USA, supervisor : T. Glantzman

Java developer, ”BABAR” project, publication in an international congress of physics (Chicago).

Professional preparation

2008

Ph.D. Computer Science, Université de Bretagne Occidentale, France

Dissertation : Model-agents for modelling and simulating complex systems : application to the ecosystemic of fisheries.

2004

M.Sc., Cognitive Science, Université ORSAY, Paris Sud XI, France

Courses: Neurobiology of cognitive functions; Cognitive psychology; Mental images and representations (M.Sc Psychology, Paris V); Distributed systems; Virtual reality and advanced interfaces; Multi agent systems; Learning and memory (M.Sc Neurosciences, Paris VII).

2003

M.Sc., Artificial Intelligence, Université Pierre et Marie Curie, Paris VI, France

Courses: Multi agents systems; Simulation of natural and artificial adaptive behaviors; Evolutionist methods; Tools and methods for image processing; Knowledge representation and processing; Neural networks; Learning, discovery and creativity; Cognitive sciences and design of intelligent agents; Systems and networks; Mathematics for computer science; Distributed systems; Deep databases; Computer networks.

2002

B.Sc., Computer Science, Université Pierre et Marie Curie, Paris VI, France

Courses: Artificial intelligence and databases; Graphical algorithmic; Logical programming and deductive databases; Expert systems and heuristics; Object modeling; Algorithmic; Computer science and society; Interfaces and application architectures; Problem resolution in AI and operational research; Software intelligence.

Synergistic Activities

Design and development of research tools

2012–2013

Perception-action architecture (C++/Python), coupling of a biologically valid vision model (Hmax neural net) to a cognitively grounded behavioral model (dynamical model), Brown University.

2009–2013

Multiagent/VR simulator (C++), pedestrian behavior and crowd dynamics, Brown University.

2004–2008

Multiagent simulator for ecologists and economists, impact of global warming and fishing activities on fish populations (research presented at EuroSim'07, ECEM'07, JFSMA'07).

2003

Multiagent simulator, evacuation scenarios, Q/CORMAS/SWARM, Paris VI and Kyoto University.

2002

Multiagent biological population simulator, Paris VI and IRD Dakar.

Other projects

2002-2003

Server admin, French litterature webserver, Artificial Intelligence project, Paris VI.

Teaching activities

2005 - 2008

(National School of Engineers, Brest, France) UML (Unified Modeling Language), C language, Algorithmic + Python language, Object Oriented programing + Java language, Shell

2004 - 2005

(Saint Cyr special military school, France) Artificial intelligence

Supervision activities

Brown University 2012 – 2013

Co-supervising undergraduate students – SERRE’S LAB.

Brown University 2010 – 2013

Supervising developer team (2 in 2010-2011, 4 in 2011-2012, 4 in 2012-2013) simulation and collaborative tools (VENLAB), managing the hiring process of new developers.

Computer Science Laboratory for Complex Systems 2007

Supervising a master student, agent modeling.

Collaborators & other affiliations

Collaborators

(2012-2013) Pr. William H. Warren, Primary Investigator of the Virtual Environment and Navigation Laboratory, Brown University : Perception and action, visual control of locomotion.

(2010-2011) Dr. Pierre Chevaillier, head of the European Center for Virtual Reality (France), Computer Science Laboratory for Complex Systems: multiagent modeling of collective behavior and action selection.

Graduate and Postdoctoral Advisors

Pr. Thomas Serre, Brown University ; Pr. William H. Warren, Brown University; Dr. Pierre Chevaillier (thesis advisor), Brest National School of Engineering, France, Head of the European Center for Virtual Reality; Dr. Pascal Redou (thesis co-advisor), Brest National School of Engineering, France; Pr. Jacques Tisseau, Head of the National School of Engineering of Brest, France.

Sponsors

Postdoc sponsor: ONR ; Postdoc sponsor: NIH R01 EY010923 ; Postdoc sponsor: ANR (Nationaly agency for research, France) ; Ph.D. sponsor: Brest National School of Engineering, France ; Ph.D. sponsor: région Bretagne, France.