DCL Student Symposium 2024

Thank you for your interest in the DCL Student Symposium! The Symposium is an annual event which brings together members of the Georgia Tech community working in the area of systems and controls to network and share their research. The Symposium is entirely organized by DCL students, and it is our hope that connections between students working in labs across the Institute will be forged at this event.

This year, we are honored to have Dr. Jorge Cortés and Dr. Quanyan Zhu as our plenary speakers. They will also join our new DCL faculty members Dr. Matthew Hale and Dr. Maegan Tucker later in the day for a panel discussing career paths in controls. Honoring the spirit of the Symposium, we will also have multiple sessions of student contributions throughout the day featuring both spotlight talks and posters. Of course, coffee and snacks will be provided along with a catered lunch.

In this rest of this document, you will find a schedule of the day along with details of the speakers and presentations. We look forward to seeing you this Friday, February 23rd at the Symposium!

• Agenda
• Keynote Talk I – Dr. Jorge Cortés
• Keynote Talk II – Dr. Quanyan Zhu
• Student Spotlight Talk List
• Student Poster List
• Location

Agenda

KEYNOTE TALK I – Dr. Jorge Cortés (11:00 – 12:00)

The safe gradient flow: a system-theoretic approach to anytime constrained optimization through control barrier functions

Abstract

This talk is motivated by problems where the solution to a constrained optimization problem is used to regulate a physical process modeled as a dynamically evolving plant (e.g., to provide setpoints, specify optimization-based controllers, or steer the system toward an optimal steady state). This type of problem arises in multiple application areas, including safety-critical control, power networks, traffic networks, and network congestion. A paradigmatic example would be the use of CBF-based quadratic programs for controller synthesis in robotics. We are interested in situations where the problem incorporates constraints which, when violated, threaten the safe operation of the physical system. In such cases, the algorithm that solves the optimization must be anytime, meaning that it is guaranteed to return a feasible point even when terminated before it has converged to a solution. We introduce a novel control-theoretic algorithm for solving constrained nonlinear programs that combines continuous-time gradient flows to optimize the objective function with techniques from control barrier functions to maintain forward invariance of the feasible set. We discuss the remarkable properties of the resulting closed-loop system, which we term safe gradient flow, regarding regularity, stability, convergence, and invariance. Comparisons with other continuous-time methods for optimization illustrate the advantages of the safe gradient flow.

Bio

Jorge Cortes is a Professor and Cymer Corporation Endowed Chair in High Performance Dynamic Systems Modeling and Control in the Department of Mechanical and Aerospace Engineering, University of California, San Diego. He is the author of “Geometric, Control and Numerical Aspects of Nonholonomic Systems” (New York: Springer-Verlag, 2002) and co-author of “Distributed Control of Robotic Networks” (Princeton: Princeton University Press, 2009). He is a Fellow of IEEE, SIAM, and IFAC. He has co-authored papers that have won the 2008 and the 2021 IEEE Control Systems Outstanding Paper Award, the 2009 SIAM Review SIGEST selection from the SIAM Journal on Control and Optimization, the 2012 O. Hugo Schuck Best Paper Award in the Theory category, and the 2019 and 2023 IEEE Transactions on Control of Network Systems Outstanding Paper Award. At the IEEE Control Systems Society, he has been a Distinguished Lecturer (2010-2014), an elected member (2018-2020) of the Board of Governors, and Director of Operations (2019-2022) of its Executive Committee. His research interests include distributed control and optimization, network science and complex systems, resource-aware control and coordination, distributed decision making and autonomy, network neuroscience, and multi-agent coordination in robotic, power, and transportation networks.

KEYNOTE TALK II – Dr. Quanyan Zhu (14:00 – 15:00)

Strategic Learning for Cyber-Physical Resilience: The Confluence of Games, Control, and Learning

Abstract

The rapid growth in the number of devices and their connectivity has enlarged the attack surface and made cyber systems more vulnerable. As attackers become increasingly sophisticated and resourceful, mere reliance on traditional cyber protection. Resilience provides a new security paradigm that complements inadequate protection with resilience mechanisms. A resilient mechanism adapts to the threats and uncertainties in real-time and strategically responds to them to maintain the critical functions of the systems. In this talk, we discuss several learning paradigms that enable resilience for both IT and OT systems, emphasizing their roles in defending against three primary types of vulnerabilities: posture-related, information-related, and human-related vulnerabilities. Within this framework, we explore three application domains—moving target defense, defensive cyber deception, and assistive human security technologies. The learning algorithms also have vulnerabilities themselves. We discuss the future challenges of strategic learning for cyber security and resilience.

Bio

Quanyan Zhu received B. Eng. in Honors Electrical Engineering from McGill University in 2006, M. A. Sc. from the University of Toronto in 2008, and Ph.D. from the University of Illinois at Urbana-Champaign (UIUC) in 2013. After stints at Princeton University, he is currently an associate professor at the Department of Electrical and Computer Engineering, New York University (NYU). He is an affiliated faculty member of the Center for Urban Science and Progress (CUSP) and Center for Cyber Security (CCS) at NYU. He is a recipient of several awards, including NSF CAREER Award and INFORMS Koopman Prize. He is an Associate Editor of IEEE Transactions on Aerospace and Electronic Systems. He currently serves as the technical committee chair on security and privacy for the IEEE Control Systems Society. His current research interests include game theory, machine learning, cyber deception, network optimization and control, cyber and physical system resilience. His research has been funded by DARPA, IARPA, ARO, NSF, DHS, and DOE. He is a co-author of several recent books: Cognitive Security: A System Scientific Approach (with L. Huang), Cyber-Security in Critical Infrastructures: A Game-Theoretic Approach (with S. Rass, S. Schauer, and S. König), Game Theory for Cyber Deception (with J. Pawlick), and Cybersecurity in Robotics (with S. Rass, B. Dieber, V. M. Vilches).

STUDENT SPOTLIGHT TALK LIST

• Jason Ye: “Improving the Efficiency of Branch-and-Bound for Global Dynamic Optimization”
• Mohannad Alkhraijah: “Detecting Shared Data Manipulation in Distributed Optimization Algorithms”
• Biswadeep Chakraborty: “Leveraging Evolution Strategies in Heterogeneous Recurrent Spiking Neural Networks for Dynamic Control”
• Trent Schreiber: “Finite Element Model Updating using Primal-Relaxed Dual Global Optimization Algorithm”
• Nejat Tukenmez: “Intermittent Learning Framework on Micro drones”
• William Warke: “Computation-Aware Bearings-Only Target Localization and Circumnavigation in 2D”
• Nguyen Hoang: “Stochastic Approximation for Nonlinear Discrete Stochastic Control: Finite-Sample Bounds”
• Shaan Haque: “Tight Finite Time Bounds of Two-Time-Scale Linear Stochastic Approximation with Markovian Noise”

STUDENT POSTER LIST

• Bo Chen : “Differential Privacy in Cooperative Multiagent Planning”
• Evanns G. Morales-Cuadrado: “Newton-Raphson Flow for Aggressive Quadrotor Tracking Control”
• Nejat Tukenmez: “Intermittent Reinforcement Learning Framework for Agile Unmanned Aerial Vehicles”
• Young In Kim: “A Streamlined Heuristic for The Problem of Min-Time Coverage in Constricted Environments”
• Biswadeep Chakraborty: “Evolution Strategies in Heterogenous Recurrent Spiking Neural Network for Dynamical Control”
• Zishun Liu: “Data-Driven Online Optimal Control with Nonstochastic Disturbance”
• Luke Baird: “Runtime Assurance from Signal Temporal Logic Safety Specifications on a Miniature Autonomous Blimp”
• Calvin Hawkins: “Multistream Anomaly Detection”
• Trent Schreiber: “Finite Element Model Updating using Primal-Relaxed Dual Global Optimization Algorithm”
• Tyler Rome: “Manual and Automated Obstacle Field Navigation of System with Changing Oscillatory Modes”
• Steven Crouse: “Dual Kalman Filter for Detecting Mixing Faults in Nuclear Waste Processing”
• Alison Jenkins: “Input Shaping for Motor Control for Haptics and Human Perception”

LOCATION

The Symposium will take place in the Tech Square Research Building 1st floor auditorium area, on the right as you enter the building. The plenary sessions, student spotlight talks, and panel will take place in the auditorium. The poster session, lunch, and snack breaks will be located in the foyer directly outside the auditorium.

For questions regarding Symposium details, please contact Akash Harapanahalli at aharapan [at] gatech.edu.