Research Interests
Further Information
The publications page outlines several of my works aligned with this broader mission connecting game theory to control theory.
TALKS: I have given a number of talks pertaining to the importance of game theory to the field of engineering. The most accessible talk was given at the UCSB GRIT series entitled "The Challenges that Society Brings to Engineering Designs." [Presentation] [Slides]
CLASS: I have developed both an undergraduate class and graduate class at UCSB on game theory from an engineering perspective. The goal of the undergraduate class is to expose our engineeing students to a variety of problems studied in game theory and highlight their application to engineering problmes (e.g., social choice, matching, cost sharing, etc.). The graduate class takes a move in depth look into auction theory and mechanism design which are of pivotal importance to the emerging socio-technical systems. Information can be found here: [Teaching]
Current Lab Members
Bryce Ferguson: Graduating PhD student who is working on the derivation of robust mechanisms for social influence.
Rohit Konda: Graduating PhD student who is working on the design of network coordination algorithms for operation in uncertain environments. More recently focusing on intelligent control in industrial refrigeration.
Gilberto Diaz-Garcia: Third year PhD student who is working on robotic surveillance problems as well as alliance strategies in networked contest games.
Vade Shah: Second year PhD student who is working on Coalitional Blotto games and online matching problems.
Yilan Chan: Current PhD student at the University of Colorado.
Former Lab Members
Ms. Rey Yue (MS, UCSB 2023): Completed her MS here at UCSB in the area of social influence. Great Job Rey!
Dr. Adel Aghajan (Postdoc, UCSB 2022): Postdoctoral Scholar, UCSD under Prof. Jorge Poveda.
Prof. Keith Paarporn (Postdoc, UCSB 2022): Assistant Professor, University of Colorado, Colorado Springs.
Dr. Rahul Chandan (PhD, UCSB 2022): Research scientist at Amazon Robotics. Thesis: Strategic Mechanisms for Multiagent Coordination
Prof. David Grimsman (PhD, UCSB 2021): Assistant Professor, Computer Science, BYU. Thesis: The Impact of Information in Cooperative and Non-Cooperative Systems
Prof. Jorge Poveda (PhD, UCSB 2018): Assistant Professor, University of Colorado, Boulder. The primary advisor to Jorge was Prof. Andrew Teel.
Prof. Philip N. Brown (PhD, UCSB 2018): Assistant Professor, University of Colorado, Colorado Springs. Thesis: Robust Methods for Influencing Strategic Behavior
Dr. Holly Borowski (PhD, University of Colorado 2016): Research Sceintist, Numerica Corporation, Fort Collins, Coloardo.
Prof. Shalom D. Ruben: Instructor, Department of Mechanical Engineering, University of Colorado. Shalom was a postdoctoral scholar under myself at Prof. Lucy Pao at the University of Colorado.
Prof. Na Li: Associate Professor, Electrical Engineering, Harvard. I was a secondary advisor of Lina during her PhD studies at Caltech.
Prof. Ragavendran Gopalakrishnan -- Assistant Professor of Operations Management at Queens University. Raga was a postdoctoral scholar under my supervision at the University of Colorado.
Dr. Vinod Ramaswamy: Postdoctoral scholar at the University of Colorado.
Mr. Matthew Philips (M.S., University of Colorado 2015)
Prof. Matthew Kirchner (M.S., University of Colorado 2015) - Assistant Professor, Auburn.
Mrs. Yasamin Shalaby (M.S., University of Colorado 2013)
Projects
The following highlights the projects currently going on in my lab.
Harnessing the Potential of AI in Industrial Refrigeration Systems
The focus of this proposal is to demonstrate and deploy scalable and rapidly adoptable advanced energy efficiency and load reduction solutions as well as thermal load shifting technologies in industrial refrigerated warehouses by deploying and demonstrating AI-based control solutions. This project is supported by the California Energy Commission [Announcement]. This is a joint project with co-PI Prof. Mahnoosh Alizadeh, as well as the CrossnoKaye and Lineage.
Resource Allocation in Complex Adversarial Environments
The focus of this proposal is on the design and analysis of control strategies for resource allocation problmes in complex adversail environment. Representative example of such resource allocation problmes include persistent monitoring and detection, supply chain management, task allocation and mission decomposition, among other. This is a joint project with co-PI Prof. Francesco Bullo and is supported by the Air Force Office of Scientific Research (AFOSR).
My general area of interest is systems and control. The overarching goal of my research plan is to develop game theory as a design tool for networked systems. Game theory is a well-established discipline in the social sciences that provides a rich framework for analyzing behavior in networked systems. However, developing game theory as a design tool for networked systems represents a significant departure from the traditional role of game theory in the social science as a modeling tool.
The control challenges associated with the following three classes of networked systems serve as the pillars of my research mission and highlight the importance of developing foundational tools for the design and control of networked systems.
Multiagent Engineered Systems: An unmanned system consists of a group of autonomous engineered decisionmakers, or agents, that are designed to achieve a collective objective without the need for global intervention. Here, the central question involves how to effectively coordinate the behavior of autonomous agents through a distributed decision making architecture with limitations on information, communication and processing.
Networked Social Systems: Developing the infrastructure necessary to serve the needs of our community is a dominant engineering principle. A crucial design challenge associated with this task is ensuring that this infrastructure is utilized in an efficient manner. This challenge arises from the well-known fact that uninfluenced social systems can lead to highly inefficient system behavior, e.g., transportation systems. Accordingly, the influence and coordination of social behavior is a fundamental challenge that engineers must account for. With the emergence of social media, the mechanisms available for influencing social behavior are at an unprecedented level; however, how to efficiently utilize these mechanisms is very much unclear. This represents a new paradigm for control theory as it transitions from a tool for physical systems to a tool for information-based systems.
Human Agent Collaborative Systems: A prevalent theme in current and future system designs is the integration of both human and engineered decision makers. This integration brings a host of new control challenges that are not sufficiently addressed in the existing literature. For example, the use of both manned and unmanned aircrafts in military surveillance missions would provide strategic advantages over purely manned systems; however, current control strategies are not sufficient to deal with the substantial concerns of risk, safety, and coordination. Alternatively, a motivating facet of the smart grid is the opportunity to shift peak power demands through real-time pricing mechanisms and the establishment of a distributed power network with both social and engineering sources; however, there are currently no control strategies that can preserve the reliability of such a network. Furthermore, the integration of humans in engineering systems introduces privacy issues which further complicate the underlying design.