Philip Brown, Ph.D.

Associate Professor

Email: [email protected]

Phone: 719-255-3332

Address: Department of Electrical and Computer Engineering
University of Colorado at Colorado Springs
1420 Austin Bluffs Parkway, Colorado Springs, CO 80918, USA

Office: ENGR 176

About Dr. Philip Brown

Philip Brown is an Associate Professor in the department of Computer Science at the University of Colorado, Colorado Springs. He received the PhD in Electrical and Computer Engineering in 2018 under the supervision of Jason R. Marden in the Center for Control, Dynamical-Systems, and Computation (CCDC) at the University of California, Santa Barbara.

He is a native of Southern Colorado, and enjoys anything that gets him outdoors on a regular basis: hiking, mountain biking, camping, trail running, and 14er bagging.

Research Interests

He is interested in developing fundamental theory to describe the interaction between technology and society. To study this, he uses tools from game theory, optimization, control theory, and various multi-agent systems concepts.

Influencing Behavior in Cyber-Social Systems: He is generally interested in the effect of financial and informational incentives on crowd behavior, particularly with an eye to complex, interconnected systems. This has many applications in infrastructure optimization: you can build a “smart city,” but it only really works if the people use it well.

Strategic Aspects of Security: One high-level way to understand cyber-security problems is to envision them as a “game” between a defender and an attacker. In this paradigm, the defender attempts to design a security system as a function of some model of the attacker’s strategy. Here, Dr. Brown seeks to understand how security vulnerabilities may arise as a result of mis-modeled attackers.

Robust Network Games: Recent years have witnessed great strides in the use of game theory as an overarching framework to inform the design of networked control systems. Dr. Brown has been a part of this with his foundational contributions to an understanding of how a game’s network structure contributes to its robustness and equilibrium selection properties.

Decision Science and Control (DeSCon) Lab

We study the fundamental mathematics of interactive decision-making, applied to a variety of contexts including infrastructure optimization, epidemiology, and the distributed control of multi-agent systems. Our research portfolio includes both basic and applied research.

Current Projects

  • CAREER: Endogenous Information Design: Influencing Behavior with Information when Behavior Changes the World. This project will pose, characterize, and apply a novel family of game-theoretic models called “endogenous Bayesian games.” These games substantially extend classical Bayesian game theory by letting the distribution of states-of-the-world be a function of agent behavior, concisely and cleanly capturing the circular informational dependencies inherent in many smart infrastructure systems. The project will apply a three-pronged approach to (1) develop analytical foundations for this new theory, (2) apply these novel tools to a problem of information design in smart and connected transportation networks, and (3) characterize and optimize the robustness of the policy recommendations generated by these models. This project’s findings will enable information design in important settings for which no tools currently exist, filling an important gap in the scientific literature and providing social planners with new analytical capabilities for conducting information design in these settings. Altogether, project results will strengthen scientific understanding of the process of influencing societal behavior and establish a foundation for future work on social-influence mechanisms. Supported by the National Science Foundation under award number ECCS-2440836.
  • Novel Metrics and Randomized Algorithms for Robust Networked Multiagent Coordination (AFOSR YIP). This project focuses on analytics and algorithms for identifying and mitigating network fragilities which result from individual agents’ inability to properly process the decisions of other agents. Whether this denial of capability is caused by adverse operational conditions or by a strategic adversary, our techniques will provide fundamental theory for designing and deploying robust networked interactive systems. A key tenet of this project is that recent results have shown that judicious use of randomized distributed algorithms can mitigate the harm of unplanned communication failures among agents; in this project we study how to optimize these algorithms to ensure robust coordination among agents. Supported by AFOSR Young Investigator Program under grant number FA9550-23-1-0171.
  • Deriving Satellite Maneuver Intent Using Game Theory. This project applies game-theoretic reasoning to infer the intent behind orbital maneuvers in an adversarial context. Supported by Phase I STTR Award from AFOSR under award number FA9550-25-P-B001; prime contractor: Astra Ultra, LLC.

Past Projects

  • Socially-Networked Autonomy: How Should Machines Interact With Society? This NSF-funded project studies decision design methodologies for autonomous agents that are networked with and interacting among human beings in societal systems. The core question is this: how should a system planner design the routing policies of autonomous vehicles to have the greatest positive impact on overall network traffic congestion, even if human drivers react in a self-interested way to the behavior of the autonomous vehicles? Supported by NSF ECCS 2013779.
  • Optimizing the Life-Cycle Impacts of COVID-19 Policy Interventions. This project asks how leaders can make public policy decisions regarding the COVID-19 pandemic in a scientific way that is locally appropriate and properly accounts for both near-term and longer-term costs of policy interventions. This project combines rigorous mathematical modeling, innovative approaches to data collection, and input from policymakers, to develop a decision aid framework that weighs the costs and benefits of various policy interventions at a local level and tailors interventions to the locale considering the effects of specific indicators such as urbanization, economic distress, and availability of regional healthcare. Supported by NSF DEB 2032465.
  • Value-based Access Control System using Path Security (with PI Dr. Gedare Bloom). This NSA-funded project investigates novel theories, policies, and mechanisms for access control that presumes client credentials are inherently risky. Our approach relies on state-of-the-art advances being made in path-based security for Internet routing. The focus of path-based mechanisms is to enable path selection by senders and path validation back to the sender (source) by intermediate routers and the destination. Our objective is to design, implement, and enforce higher-level access control decisions built upon this baseline to protect digital assets within the (destination) network from malicious source nodes that can pass traditional user authentication mechanisms due to stolen credentials.
  • Dynamic Weather-Aware Aviation Routing. This project uses graph-theoretic shortest path techniques to compute optimal paths for aircraft, accounting for transient effects such as weather. Supported by a Phase I SBIR grant from NASA; prime contractor: Sigmatech, Inc.

Current PhD Students

  • Pam Russell 2019-Present
  • Colton Hill 2021-Present
  • Will Wesley 2022-Present
  • Ken Lee 2023-Present
  • Guanchu He 2025-Present
  • Jason Liu 2026-Present

Past PhD Students

Past Postdocs

Past Master’s Thesis Students

  • Austin Weingart, 2025
  • Guanchu He, 2022-2024
  • Ryan Young, 2020
  • Joshua Seaton, 2021

Past Undergraduate Researchers

  • Naomi Rodriguez, 2024-2025
  • Kaylee Barcroft, 2024
  • Brendan Gould, 2021-2024
  • Sonia Karsanbhai, 2021-2023
  • Brandon Collins, 2018-2020
  • Joseph Mazzocco, 2019

Journal Papers

  • Brandon C. Collins, Shouhuai Xu, and Philip N. Brown, “A Coupling Approach to Analyzing Games with Dynamic Environments,” IEEE Transactions on Automatic Control, 2025. IEEEXplore | arXiv
  • Bryce Ferguson, Philip N. Brown, and Jason R. Marden, “Information Signalling with Concurrent Monetary Incentives in Bayesian Congestion Games,” IEEE Transactions on Intelligent Transportation Systems, 2024. IEEEXplore | NSF PAR
  • Brendan T. Gould and Philip N. Brown, “Information Design Under Uncertainty for Vehicle-to-Vehicle Communication,” in IEEE Letters of the Control Systems Society (L-CSS), 2023. IEEEXplore | NSF PAR
  • Joshua Seaton and Philip N. Brown, “On the Intrinsic Fragility of the Price of Anarchy,” in IEEE Letters of the Control Systems Society (L-CSS), 2023. IEEEXplore | NSF PAR
  • Brendan T. Gould and Philip N. Brown, “Information Design for Vehicle-to-Vehicle Communication,” in Transportation Research Part C: Emerging Technologies, 2023. ScienceDirect | NSF PAR
  • Bryce Ferguson, Philip N. Brown, and Jason R. Marden, “Value of Information in Incentive Design: A Case Study in Simple Congestion Networks,” IEEE Transactions on Computational Social Systems (TCSS), 2023. IEEEXplore | NSF PAR
  • Philip N. Brown, Joshua Seaton, and Jason R. Marden, “Robust Networked Multiagent Optimization: Designing Agents to Repair Their Own Utility Functions,” in Dynamic Games and Applications (DGAA), 2023. Springer | NSF PAR
  • Joshua Seaton and Philip N. Brown, “All Stable Equilibria Have Improved Performance Guarantees in Submodular Maximization With Communication-Denied Agents,” in IEEE Letters of the Control Systems Society (L-CSS), 2022. IEEEXplore | NSF PAR
  • Gia Barboza, Kate Angulski, Lisa Hines, and Philip N. Brown, “Variability in Opioid-Related Drug Overdoses, Social Distancing, and Area-Level Deprivation during the COVID-19 Pandemic: a Bayesian Spatiotemporal Analysis,” in Journal of Urban Health, 2022. Springer | NSF PAR
  • Bryce Ferguson, Philip N. Brown, and Jason R. Marden, “The Effectiveness of Subsidies and Tolls in Congestion Games,” in IEEE Transactions on Automatic Control, 2021. arXiv | IEEEXplore
  • Bryce Ferguson, Philip N. Brown, and Jason R. Marden, “The Effectiveness of Subsidies and Tolls in Atomic Congestion Games,” in IEEE Letters of the Control Systems Society (L-CSS), 2021. IEEEXplore
  • Philip N. Brown, Jason R. Marden, “Can Taxes Improve Congestion on all Networks?” in IEEE Transactions on the Control of Network Systems, 2020. arXiv | IEEEXplore
  • Keith Paarporn, Brian Canty, Philip N. Brown, Mahnoosh Alizadeh, Jason R. Marden, ” The Impact of Complex and Informed Adversarial Behavior in Graphical Coordination Games,” in IEEE Transactions on Control of Network Systems, 2020. arXiv | IEEEXplore
  • Philip N. Brown, Holly P. Borowski, and Jason R. Marden, “Security Against Impersonation Attacks in Multiagent Systems,” IEEE Transactions on Control of Network Systems, 2018. arXiv | IEEEXplore
  • Philip N. Brown, Jason R. Marden, “Optimal Mechanisms for Robust Coordination in Congestion Games,”  IEEE Transactions on Automatic Control, vol. 63, no. 8, August, 2018 pp. 2437-2448. 2018. PDF | IEEEXplore
  • Philip N. Brown, Jason R. Marden, “The Robustness of Marginal-Cost Taxes in Affine Congestion
    Games,” IEEE Transactions on Automatic Control, vol. 62, no. 8. August, 2017 pp. 3999-4004. PDF
  • Philip N. Brown, Jason R. Marden, “Studies on Robust Social Influence Mechanisms: Incentives for Efficient Network Routing in Uncertain Settings,” IEEE Control Systems Magazine, vol. 37, no. 1, pp. 98-115, 2017. PDF

Refereed Conference Proceedings

  • Vartika Singh, Will Wesley, and Philip N. Brown, “Optimal Utility Design with Arbitrary Information Networks,” in 2025 American Control Conference, 2025. arXiv
  • Vartika Singh and Philip N. Brown, “ABRA: An algorithm which cannot converge to low-quality Nash equilibria,” in 63rd IEEE Conference on Decision and Control, 2024. IEEEXplore | paperplaza
  • Colton Hill and Philip N. Brown, “Altruism Improves Congestion in Series-Parallel Nonatomic Congestion Games,” in 63rd IEEE Conference on Decision and Control, 2024. IEEEXplore | arXiv
  • Colton Hill and Philip N. Brown, “Incentivizing Behavior in Transportation Networks with Non-Rational Drivers and 3rd-party Economic Agents,” in 2024 European Control Conference, 2024. (invited paper) IEEEXplore | NSF PAR
  • Colton Hill and Philip N. Brown, “Conditions for Altruistic Perversity in two-Strategy Population Games,” in 2024 American Control Conference, 2024. IEEEXplore | arXiv
  • Keith Paarporn, Philip N. Brown, and Shouhuai Xu, “Analysis of Contagion Dynamics with Active Cyber Defenders,” in 62nd IEEE Conference on Decision and Control, 2023. (invited paper) IEEEXplore | arXiv
  • Brendan Gould and Philip N. Brown, “Rationality and Behavior Feedback in a Model of Vehicle-to-vehicle Communication,” in 62nd IEEE Conference on Decision and Control, 2023. (invited paper) IEEEXplore | arXiv
  • Colton Hill and Philip N. Brown, “The Tradeoff Between Altruism and Anarchy in Transportation Networks,” in IEEE Intelligent Transportation Systems Conference, 2023. IEEEXplore | NSF PAR
  • Keith Paarporn and Philip N. Brown, “Strategically revealing capabilities in General Lotto games,” in IFAC World Congress, 2023. ScienceDirect | arXiv
  • Joshua Seaton, Sena Hounsinou, Gedare Bloom, and Philip N. Brown, “Competitive Information Provision Among Internet Routing Nodes,” in 2023 American Control Conference, 2023. IEEEXplore | NSF PAR
  • Bryce Ferguson, Philip N. Brown, and Jason R. Marden, “Avoiding Unintended Consequences: How Incentives Aid Information Provisioning in Bayesian Congestion Games,” in 61st IEEE Conference on Decision and Control, 2022. IEEEXplore | arXiv
  • David Grimsman, Philip N. Brown, and Jason R. Marden, “Valid Utility Games with Information Sharing Constraints,” 61st IEEE Conference on Decision and Control, 2022. IEEEXplore | arXiv
  • Philip N. Brown, Brandon Collins, Colton Hill, Gia Barboza, and Lisa Hines, “Individual Altruism Cannot Overcome Congestion Effects in a Global Pandemic Game,” 58th Allerton Conference on Communication, Control, and Computing, 2022. IEEEXplore | arXiv
  • Pam Russell and Philip N. Brown, “The Philos Trust Algorithm: Preventing Exploitation of Distributed Trust,” in IEEE International Conference on Blockchain, 2022. IEEEXplore | arXiv
  • Brendan Gould and Philip N. Brown, “On Partial Adoption of Vehicle-To-Vehicle Communication: When Should Cars Warn Each Other of Hazards?” in 2022 American Control Conference, 2022. IEEEXplore | arXiv
  • Christopher Gorog, Pam Russell, Terrance E. Boult, and Philip N. Brown, “Carbon-Neutral Distributed Ledger,” in IEEE PES Transactive Energy Systems Conference, 2022. IEEEXplore | PDF
  • Vjiay Banerjee, Ryan Rabinowitz, Mark Stidd, Rory Lewis, Philip N. Brown, and Gedare Bloom, “The Tragedy of the Miners,” in IEEE 19th Annual Consumer Communications & Networking Conference (CCNC), 2022. IEEEXplore
  • Philip N. Brown, “Providing slowdown information to improve selfish routing,” in EAI GameNets 2021. [Best Paper Award]
  • Brandon Collins, Gia Barboza, Lisa Hines, and Philip N. Brown, “Robust Stochastic Stability in Dynamic and Reactive Environments,” in 60th IEEE Conference on Decision and Control, 2021. arXiv | IEEEXplore
  • Brandon Collins, Shouhuai Xu, and Philip N. Brown, ” Paying Firms to Share Cyber Threat Intelligence,” in GameSec 2021. Springer
  • Ruolin Li, Philip N. Brown, and Roberto Horowitz, “A Highway Toll Lane Framework that Unites Autonomous Vehicles and High-occupancy Vehicles,” in 2021 IEEE International Intelligent Transportation Systems Conference (ITSC), 2021. arXiv | IEEEXplore
  • Philip N. Brown, “When Altruism Is Worse Than Anarchy in Nonatomic Congestion Games,” in proceedings of 2021 American Control Conference, 2021. arXiv
  • Ruolin Li, Philip N. Brown, and Roberto Horowitz, “Employing Altruistic Vehicles at On-Ramps to Improve the Social Traffic Conditions,” in proceedings of 2021 American Control Conference, 2021.
  • David Grimsman, Joshua Seaton, Jason R. Marden, and Philip N. Brown, “The Cost of Denied Observation in Multiagent Submodular Optimization,” in proceedings of 59th IEEE Conference on Decision and Control, 2020. arXiv | IEEEXplore
  • Brandon Collins and Philip N. Brown, “Exploiting an Adversary’s Intentions in Graphical Coordination Games,” in proceedings of 2020 American Control Conference, 2020. arXiv | IEEEXplore
  • Bryce Ferguson, Philip N. Brown, and Jason R. Marden, “Carrots or Sticks? The Effectiveness of Subsidies and Tolls in Congestion Games,” in proceedings of 2020 American Control Conference, 2020. arXiv | IEEEXplore [Best student paper award finalist]
  • Philip N. Brown, “Designing for Emergent Security in Heterogeneous Human-Machine Teams,” in Proceedings of 58th IEEE Conference on Decision and Control, 2019. arXiv | IEEEXplore
  • Bryce Ferguson, Philip N. Brown, and Jason R. Marden, “Utilizing Information Optimally to Influence Distributed Network Routing,” in proceedings of 58th IEEE Conference on Decision and Control, 2019.
  • Philip N. Brown, “A Tragedy of Autonomy: Self-Driving Cars and Urban Congestion Externalities,” in proceedings of 57th Annual Allerton Conference on Communication, Control, and Computing, 2019.
  • Philip N. Brown, Jason R. Marden, “On the feasibility of local utility redesign for multiagent optimization,” in Proceedings of European Control Conference, 2019.
  • Brian Canty, Philip N. Brown, Mahnoosh Alizadeh, and Jason R. Marden, “The Impact of Informed Adversarial Behavior in Graphical Coordination Games,” in Proceedings of 57th IEEE Conference on Decision and Control, 2018.
  • Philip N. Brown, Jason R. Marden, “The Benefit of Perversity in Taxation Mechanisms for Distributed Routing,” in Proceedings of 56th IEEE Conference on Decision and Control, 2017.
  • Jorge I. Poveda, Philip N. Brown, Jason R. Marden, and Andrew R. Teel, “A Class of Distributed Adaptive Pricing Mechanisms for Societal Systems with Limited Information,” in Proceedings of 56th IEEE Conference on Decision and Control, 2017. [Best student paper award finalist]
  • Philip N. Brown, Jason R. Marden, “Fundamental Limits of Locally-Computed Incentives in Network Routing,” in Proceedings of American Control Conference. 2017. PDF
  • Philip N. Brown, Jason R. Marden, “Avoiding Perverse Incentives in Affine Congestion Games,” in Proceedings of 55th IEEE Conference on Decision and Control. 2016. PDF [Best student paper award finalist]
  • Philip N. Brown, Jason R. Marden, “A Study on Price Discrimination for Robust Social Coordination,” in Proceedings of American Control Conference. 2016. PDF
  • Philip N. Brown, Jason R. Marden, “Optimal Mechanisms for Robust Coordination in Congestion Games,” in Proceedings of 54th IEEE Conference on Decision and Control. 2015. PDF
  • Philip N. Brown, Jason R. Marden, “Social Coordination in Unknown Price-Sensitive Populations,” in Proceedings of 52th IEEE Conference on Decision and Control. 2013. PDF

Brief Papers

  • Philip N. Brown, “An Upper Bound on the Cardinality of a Minimum Feedback Vertex Set for Directed Graphs,” 2020. PDF
  • Philip N. Brown, “Incentives for Crypto-Collateralized Digital Assets,” in proceedings of 3rd Annual Decentralized Conference on Blockchain and Cryptocurrency, 2019. MDPI
  • Philip N. Brown, Holly P. Borowski, and Jason R. Marden, “Projecting Network Games onto Sparse Graphs,” invited paper, Asilomar Conference on Signals, Systems, and Computers, 2018. IEEEXplore
  • Philip N. Brown, Jason R. Marden, “Studies on mechanisms for robust social influence,” in proceedings of 2017 IEEE Conference on Control Technology and Applications (CCTA), 2017. IEEEXplore
  • “Optimal Utility Design with Arbitrary Information Networks,” at 2025 American Control Conference, Denver, Colorado, July 2025.
  • “Where we’ve been and where we’re going: Game Theory and CAV,” at 1st Workshop on Mixed Autonomy in Transportation: Emerging Challenges and Opportunities, ACC, Denver, CO, July 2025.
  • “A Little Anarchy Never Hurt Anyone: Beyond Worst-Case Equilibria in Games,” Eindhoven Artificial Intelligence Systems Institute, Eindhoven University of Technology, the Netherlands, June 2024.
  • “A Little Anarchy Never Hurt Anyone: Beyond Worst-Case Equilibria in Games,” Center for Control, Dynamical-Systems, and Computation Seminar Series, University of California, Santa Barbara, May 2024.
  • “Can Simple Behavior Models Optimize Complex Connected Vehicles?” 5th Workshop on Autonomous, Connected, and Electrified Mobility Systems, Bilbao, Spain, September 2023.
  • “The Paradox of Harmful Altruism In Mixed Autonomous Traffic,” 3rd Symposium on Interdisciplinarity, Complexity, and Complex Systems, University of Colorado Colorado Springs, July 2023.
  • “When is ‘Altruism’ Good in Distributed Decision-Making?” IEEE Computer Society — Pikes Peak Chapter, Colorado Springs, April 2023.
  • “Selfish Self-Driving Cars: The Emerging Ethics of Socio-Technical Systems,” Cool Science: Science on Tap Lecture Series, Colorado Springs, CO. November 2022.
  • “Selfish Self-Driving Cars: An Adventure in Algorithmic Game Theory,” Colorado College, May 2022.
  • “When is Altruism Good in Distributed Decision-Making?” Decision and Control Laboratory Seminar, Georgia Institute of Technology, February 2022.
  • “Providing slowdown information to improve selfish routing,” EAI GameNets 2021, December 2021. [Best Community-voted presentation award] YouTube
  • “Engineers who Make Selfish Machines,” Philosophy in the City lecture series, UCCS Downtown, Colorado Springs, USA, September 2021.
  • “On the feasibility of local utility redesign for multiagent optimization,” 6th World Congress of the Game Theory Society, Budapest, Hungary, July 2021.
  • “When Altruism Is Worse Than Anarchy in Nonatomic Congestion Games,” 2021 American Control Conference, New Orleans, LA, May 2021. YouTube
  • “Engineers who Make Selfish Machines: The Ethics of Socio-Technical Systems,” Ethics Roundtable for the Daniels Fund Ethics Initiative at the UCCS College of Business, April 2021.
  • “Altruism Paradoxes and Emergent Security in Distributed Decision-Making,” Seminar talk at the Center for Controls, Dynamical Systems, and Computation, UCSB, February 2020.
  • “Designing for Emergent Security in Heterogeneous Human-Machine Teams,” 58th IEEE Conference on Decision and Control, Nice, France, December 2019.
  • “Robust Methods for Influencing Strategic Behavior,” Seminar talk at the University of Colorado at Boulder, November 2019.
  • “Incentives for Crypto-Collateralized Digital Assets,” Decentralized 2019, Athens, Greece, October 2019.
  • “A Tragedy of Autonomy: Self-Driving Cars and Urban Congestion Externalities,” 57th Annual Allerton Conference on Communication, Control, and Computing, Allerton, Illinois, USA, September 2019.
  • “Robust Methods for Influencing Strategic Behavior,” ASU Network Science seminar series, March 2019.
  • “Projecting Network Games onto Sparse Graphs,” Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA, USA, October 2018.
  • I spoke in the Department of Industrial and Systems Engineering at Virginia Tech and the Department of Computer Science at the University of Colorado, Colorado Springs in March, 2018.
  • I spoke at the Department of Computer Science and Engineering at the University of Texas, Arlington in February 2018.
  • “The Benefit of Perversity in Taxation Mechanisms for Distributed Routing,” 56th IEEE Conference on Decision and Control, Melbourne, Australia, December 2017.
  • “Are Multiagent Systems Resilient to Communication Failures?” 33rd Southern California Controls Workshop, University of California, Santa Barbara, October 2017.
  • “The Perils of Ignoring Information in Distributed Learning,” ONR Science of Autonomy Program Review, Arlington, VA, USA, August 2017.
  • “Fundamental Limits of Locally-Computed Incentives in Network Routing,” 28th International Conference on Game Theory, Stony Brook University, USA, July 2017.
  • “Fundamental Limits of Locally-Computed Incentives in Network Routing,” 2017 American Control Conference, Seattle, USA, May 2017.
  • “Avoiding Perverse Incentives in Affine Congestion Games,” 55th IEEE Conference on Decision and Control, Las Vegas, USA, December 2016. [Best student paper award finalist]
  • “Optimal Mechanisms for Robust Coordination in Congestion Games,” 5th World Congress on Game Theory, Maastricht, The Netherlands, July 2016.
  • “A Study on Discrimination for Robust Social Coordination,” 2016 American Control Conference, Boston, USA, July 2016. [Best talk in session award]
  • “Can Price Discrimination Help Influence Social Behavior?” 30th Southern California Control Workshop, University of California, San Diego, USA, June 2016.
  • “Optimal Mechanisms for Robust Coordination in Congestion Games,” 54th IEEE Conference on Decision and Control, Osaka, Japan, December 2015.
  • “Influencing Social Behavior: A Robust Approach,” Robotics, Controls, and Dynamic Systems seminar series, University of Colorado at Boulder, USA, November 2015.
  • “Robust Mechanisms for Influencing Cyber-Social Systems,” Center for Unmanned Aircraft Systems Industry Advisory Board Meeting (poster session), University of Colorado at Boulder, USA, July 2015.
  • “Optimal Mechanisms for Robust Coordination in Congestion Games,” 26th International Conference on Game Theory, Stony Brook University, USA, July 2015.
  • “Robust Toll Design: Influencing Selfish Behavior in Unknown Price-Sensitive Users,” 3rd Midwest Workshop on Control and Game Theory, Ohio State University, USA. April 2014.
  • “Social Coordination in Unknown Price-Sensitive Populations,” 52nd IEEE Conference on Decision and Control, Florence, Italy. December 2013.
  • “Social Coordination in Unknown Price-Sensitive Populations,” 24th International Conference on Game Theory, Stony Brook University, USA, July 2013.