papers

Publications (79)

eess.SY2025

Safe Control for Nonlinear Systems Under Faults and Attacks Via Control Barrier Functions

Hongchao Zhang, Zhouchi Li, Andrew Clark

Safety is one of the most important properties of control systems. Sensor faults and attacks and actuator failures may cause errors in the sensor measurements and system dynamics,…

cs.GT2018

A Game Theoretic Approach for Dynamic Information Flow Tracking to Detect Multi-Stage Advanced Persistent Threats

Shana Moothedath, Dinuka Sahabandu, Joey Allen +4

Advanced Persistent Threats (APTs) infiltrate cyber systems and compromise specifically targeted data and/or resources through a sequence of stealthy attacks consisting of multiple…

cs.RO2024

Learning a Formally Verified Control Barrier Function in Stochastic Environment

Manan Tayal, Hongchao Zhang, Pushpak Jagtap +2

Safety is a fundamental requirement of control systems. Control Barrier Functions (CBFs) are proposed to ensure the safety of the control system by constructing safety filters or s…

cs.MA2021

Scalable Planning in Multi-Agent MDPs

Dinuka Sahabandu, Luyao Niu, Andrew Clark +1

Multi-agent Markov Decision Processes (MMDPs) arise in a variety of applications including target tracking, control of multi-robot swarms, and multiplayer games. A key challenge in…

eess.SY2024

Who is Responsible? Explaining Safety Violations in Multi-Agent Cyber-Physical Systems

Luyao Niu, Hongchao Zhang, Dinuka Sahabandu +3

Multi-agent cyber-physical systems are present in a variety of applications. Agent decision-making can be affected due to errors induced by uncertain, dynamic operating environment…

q-fin.PM2012

Using MOEAs To Outperform Stock Benchmarks In The Presence of Typical Investment Constraints

Andrew Clark, Jeff Kenyon

Portfolio managers are typically constrained by turnover limits, minimum and maximum stock positions, cardinality, a target market capitalization and sometimes the need to hew to a…

cs.LG2019

Potential-Based Advice for Stochastic Policy Learning

Baicen Xiao, Bhaskar Ramasubramanian, Andrew Clark +3

This paper augments the reward received by a reinforcement learning agent with potential functions in order to help the agent learn (possibly stochastic) optimal policies. We show…

eess.SY2025

Stochastic Neural Control Barrier Functions

Hongchao Zhang, Manan Tayal, Jackson Cox +3

Control Barrier Functions (CBFs) are utilized to ensure the safety of control systems. CBFs act as safety filters in order to provide safety guarantees without compromising system…

eess.SY2016

Adaptive Mitigation of Multi-Virus Propagation: A Passivity-Based Approach

Phillip Lee, Andrew Clark, Basel Alomair +2

Malware propagation poses a growing threat to networked systems such as computer networks and cyber-physical systems. Current approaches to defending against malware propagation ar…

eess.SY2016

Submodularity in Input Node Selection for Networked Systems

Andrew Clark, Basel Alomair, Linda Bushnell +1

Networked systems are systems of interconnected components, in which the dynamics of each component are influenced by the behavior of neighboring components. Examples of networked…

eess.SY2025

Swarm-STL: A Framework for Motion Planning in Large-Scale, Multi-Swarm Systems

Shiyu Cheng, Luyao Niu, Bhaskar Ramasubramanian +2

In multi-agent systems, signal temporal logic (STL) is widely used for path planning to accomplish complex objectives with formal safety guarantees. However, as the number of agent…

math.OC2014

Input Selection for Performance and Controllability of Structured Linear Descriptor Systems

Andrew Clark, Basel Alomair, Linda Bushnell +1

A common approach to controlling complex networks is to directly control a subset of input nodes, which then controls the remaining nodes via network interactions. While techniques…

cs.AI2023

Risk-Aware Distributed Multi-Agent Reinforcement Learning

Abdullah Al Maruf, Luyao Niu, Bhaskar Ramasubramanian +2

Autonomous cyber and cyber-physical systems need to perform decision-making, learning, and control in unknown environments. Such decision-making can be sensitive to multiple factor…

cs.AI2020

FRESH: Interactive Reward Shaping in High-Dimensional State Spaces using Human Feedback

Baicen Xiao, Qifan Lu, Bhaskar Ramasubramanian +3

Reinforcement learning has been successful in training autonomous agents to accomplish goals in complex environments. Although this has been adapted to multiple settings, including…

eess.SY2019

On the Structure and Computation of Random Walk Times in Finite Graphs

Andrew Clark, Basel Alomair, Linda Bushnell +1

We consider random walks in which the walk originates in one set of nodes and then continues until it reaches one or more nodes in a target set. The time required for the walk to r…

eess.SY2013

Minimizing Convergence Error in Multi-Agent Systems via Leader Selection: A Supermodular Optimization Approach

Andrew Clark, Basel Alomair, Linda Bushnell +1

In a leader-follower multi-agent system (MAS), the leader agents act as control inputs and influence the states of the remaining follower agents. The rate at which the follower age…

eess.SY2022

Abstraction-Free Control Synthesis to Satisfy Temporal Logic Constraints under Sensor Faults and Attacks

Luyao Niu, Zhouchi Li, Andrew Clark

We study the problem of synthesizing a controller to satisfy a complex task in the presence of sensor faults and attacks. We model the task using Gaussian distribution temporal log…

eess.SY2024

A Semi-Algebraic Framework for Verification and Synthesis of Control Barrier Functions

Andrew Clark

Safety is a critical property for control systems in medicine, transportation, manufacturing, and other applications, and can be defined as ensuring positive invariance of a predef…

eess.SY2024

SEEV: Synthesis with Efficient Exact Verification for ReLU Neural Barrier Functions

Hongchao Zhang, Zhizhen Qin, Sicun Gao +1

Neural Control Barrier Functions (NCBFs) have shown significant promise in enforcing safety constraints on nonlinear autonomous systems. State-of-the-art exact approaches to verify…

eess.SY2017

Combinatorial Algorithms for Control of Biological Regulatory Networks

Andrew Clark, Phillip Lee, Basel Alomair +2

Biological processes, including cell differentiation, organism development, and disease progression, can be interpreted as attractors (fixed points or limit cycles) of an underlyin…

eess.SY2020

Privacy-Preserving Resilience of Cyber-Physical Systems to Adversaries

Bhaskar Ramasubramanian, Luyao Niu, Andrew Clark +2

A cyber-physical system (CPS) is expected to be resilient to more than one type of adversary. In this paper, we consider a CPS that has to satisfy a linear temporal logic (LTL) obj…

cs.IT2024

Explicit Formula for Partial Information Decomposition

Aobo Lyu, Andrew Clark, Netanel Raviv

Mutual information between two random variables is a well-studied notion, whose understanding is fairly complete. Mutual information between one random variable and a pair of other…

eess.SY2021

A Game-Theoretic Framework for Controlled Islanding in the Presence of Adversaries

Luyao Niu, Dinuka Sahabandu, Andrew Clark +1

Controlled islanding effectively mitigates cascading failures by partitioning the power system into a set of disjoint islands. In this paper, we study the controlled islanding prob…

eess.SY2013

A Passivity Framework for Modeling and Mitigating Wormhole Attacks on Networked Control Systems

Phillip Lee, Andrew Clark, Linda Bushnell +1

Networked control systems consist of distributed sensors and actuators that communicate via a wireless network. The use of an open wireless medium and unattended deployment leaves…

eess.SY2022

LQG Reference Tracking with Safety and Reachability Guarantees under Unknown False Data Injection Attacks

Zhouchi Li, Luyao Niu, Andrew Clark

We investigate a linear quadratic Gaussian (LQG) tracking problem with safety and reachability constraints in the presence of an adversary who mounts an FDI attack on an unknown se…

physics.atm-clus2020

Time-resolved formation of excited atomic and molecular states in XUV-induced nanoplasmas in ammonia clusters

Rupert Michiels, Aaron Cristopher LaForge, Matthias Bohlen +15

High intensity XUV radiation from a free-electron (FEL) was used to create a nanoplasma inside ammonia clusters with the intent of studying the resulting electron-ion interactions…

eess.SY2015

Global Practical Node and Edge Synchronization in Kuramoto Networks: A Submodular Optimization Framework

Andrew Clark, Basel Alomair, Linda Bushnell +1

Synchronization underlies phenomena including memory and perception in the brain, coordinated motion of animal flocks, and stability of the power grid. These synchronization phenom…

cs.LG2023

Exact Verification of ReLU Neural Control Barrier Functions

Hongchao Zhang, Junlin Wu, Yevgeniy Vorobeychik +1

Control Barrier Functions (CBFs) are a popular approach for safe control of nonlinear systems. In CBF-based control, the desired safety properties of the system are mapped to nonne…

cs.RO2024

Fault Tolerant Neural Control Barrier Functions for Robotic Systems under Sensor Faults and Attacks

Hongchao Zhang, Luyao Niu, Andrew Clark +1

Safety is a fundamental requirement of many robotic systems. Control barrier function (CBF)-based approaches have been proposed to guarantee the safety of robotic systems. However,…

cs.CR2018

Cloaking the Clock: Emulating Clock Skew in Controller Area Networks

Sang Uk Sagong, Xuhang Ying, Andrew Clark +2

Automobiles are equipped with Electronic Control Units (ECU) that communicate via in-vehicle network protocol standards such as Controller Area Network (CAN). These protocols are d…

eess.SY2021

Safety-Critical Control Synthesis for Unknown Sampled-Data Systems via Control Barrier Functions

Luyao Niu, Hongchao Zhang, Andrew Clark

As the complexity of control systems increases, safety becomes an increasingly important property since safety violations can damage the plant and put the system operator in danger…

eess.SY2020

Submodular Input Selection for Synchronization in Kuramoto Networks

Dinuka Sahabandu, Andrew Clark, Linda Bushnell +1

Synchronization is an essential property of engineered and natural networked dynamical systems. The Kuramoto model of nonlinear synchronization has been widely studied in applicati…

cs.MM2017

Attacking Automatic Video Analysis Algorithms: A Case Study of Google Cloud Video Intelligence API

Hossein Hosseini, Baicen Xiao, Andrew Clark +1

Due to the growth of video data on Internet, automatic video analysis has gained a lot of attention from academia as well as companies such as Facebook, Twitter and Google. In this…

cs.IT2026

Closed-Form Gaussian Estimators for Multi-Source Partial Information Decomposition

Aobo Lyu, Andrew Clark, Netanel Raviv

Computing multi-source partial information decomposition (PID) for continuous data is hard: existing closed-form Gaussian estimators are restricted to two source variables, while c…

physics.optics2022

Electrically pumped quantum-dot lasers grown on 300 mm patterned Si photonic wafers

Chen Shang, Kaiyin Feng, Eamonn T. Hughes +9

Monolithic integration of quantum dot (QD) gain materials onto Si photonic platforms via direct epitaxial growth is a promising solution for on-chip light sources. Recent developme…

eess.SY2022

A Timing-Based Framework for Designing Resilient Cyber-Physical Systems under Safety Constraint

Abdullah Al Maruf, Luyao Niu, Andrew Clark +2

Cyber-physical systems (CPS) are required to satisfy safety constraints in various application domains such as robotics, industrial manufacturing systems, and power systems. Faults…

physics.atm-clus2022

Diffraction imaging of light induced dynamics in xenon-doped helium nanodroplets

Bruno Langbehn, Yevheniy Ovcharenko, Andrew Clark +23

We have explored the light induced dynamics in superfluid helium nanodroplets with wide-angle scattering in a pump-probe measurement scheme. The droplets are doped with xenon atoms…

eess.SY2020

Secure Control in Partially Observable Environments to Satisfy LTL Specifications

Bhaskar Ramasubramanian, Luyao Niu, Andrew Clark +2

This paper studies the synthesis of control policies for an agent that has to satisfy a temporal logic specification in a partially observable environment, in the presence of an ad…

cs.NE2012

Piecewise Linear Topology, Evolutionary Algorithms, and Optimization Problems

Andrew Clark

Schemata theory, Markov chains, and statistical mechanics have been used to explain how evolutionary algorithms (EAs) work. Incremental success has been achieved with all of these…

cs.CY2019

A Differentially Private Incentive Design for Traffic Offload to Public Transportationx

Luyao Niu, Andrew Clark

Increasingly large trip demands have strained urban transportation capacity, which consequently leads to traffic congestion and rapid growth of greenhouse gas emissions. In this wo…

math.OC2026

Verification Framework for the Union of Control Barrier Functions

Chuanrui Jiang, Andrew Clark

Control Barrier Functions (CBFs) have been proposed to ensure safety of autonomous systems. This paper considers control policies that switch between CBF constraints. Under this ap…

cs.IT2026

Multivariate Partial Information Decomposition: Constructions, Inconsistencies, and Alternative Measures

Aobo Lyu, Andrew Clark, Netanel Raviv

While mutual information effectively quantifies dependence between two variables, it does not by itself reveal the complex, fine-grained interactions among variables, i.e., how mul…

math.OC2020

Control Barrier Functions for Stochastic Systems

Andrew Clark

Control Barrier Functions (CBFs) aim to ensure safety by constraining the control input at each time step so that the system state remains within a desired safe region. This paper…

cs.LG2021

Reinforcement Learning Beyond Expectation

Bhaskar Ramasubramanian, Luyao Niu, Andrew Clark +1

The inputs and preferences of human users are important considerations in situations where these users interact with autonomous cyber or cyber-physical systems. In these scenarios,…

cs.AI2025

Validity Is What You Need

Sebastian Benthall, Andrew Clark

While AI agents have long been discussed and studied in computer science, today's Agentic AI systems are something new. We consider other definitions of Agentic AI and propose a ne…

math.OC2017

Minimal Input Selection for Robust Control

Zhipeng Liu, Yao Long, Andrew Clark +4

This paper studies the problem of selecting a minimum-size set of input nodes to guarantee stability of a networked system in the presence of uncertainties and time delays. Current…

eess.SY2018

Minimum Violation Control Synthesis on Cyber-Physical Systems under Attacks

Luyao Niu, Jie Fu, Andrew Clark

Cyber-physical systems are conducting increasingly complex tasks, which are often modeled using formal languages such as temporal logic. The system's ability to perform the require…

eess.SY2022

Barrier Certificate based Safe Control for LiDAR-based Systems under Sensor Faults and Attacks

Hongchao Zhang, Shiyu Cheng, Luyao Niu +1

Autonomous Cyber-Physical Systems (CPS) fuse proprioceptive sensors such as GPS and exteroceptive sensors including Light Detection and Ranging (LiDAR) and cameras for state estima…

eess.SY2017

Maximizing the Smallest Eigenvalue of a Symmetric Matrix: A Submodular Optimization Approach

Andrew Clark, Qiqiang Hou, Linda Bushnell +1

This paper studies the problem of selecting a submatrix of a positive definite matrix in order to achieve a desired bound on the smallest eigenvalue of the submatrix. Maximizing th…

cs.NI2013

Using Social Information for Flow Allocation in MANETs

Andrew Clark, Amit Pande, Kannan Govindan +2

Adhoc networks enable communication between distributed, mobile wireless nodes without any supporting infrastructure. In the absence of centralized control, such networks require n…

math.OC2023

A Hybrid Submodular Optimization Approach to Controlled Islanding with Post-Disturbance Stability Guarantees

Luyao Niu, Dinuka Sahanbandu, Andrew Clark +1

Disturbances may create cascading failures in power systems and lead to widespread blackouts. Controlled islanding is an effective approach to mitigate cascading failures by partit…

physics.atm-clus2018

Three-Dimensional Shapes of Spinning Helium Nanodroplets

Bruno Langbehn, Katharina Sander, Yevheniy Ovcharenko +23

A significant fraction of superfluid helium nanodroplets produced in a free-jet expansion have been observed to gain high angular momentum resulting in large centrifugal deformatio…

eess.SY2022

A Compositional Approach to Safety-Critical Resilient Control for Systems with Coupled Dynamics

Abdullah Al Maruf, Luyao Niu, Andrew Clark +2

Complex, interconnected Cyber-physical Systems (CPS) are increasingly common in applications including smart grids and transportation. Ensuring safety of interconnected systems who…

math.OC2018

Controlled Islanding via Weak Submodularity

Zhipeng Liu, Andrew Clark, Linda Bushnell +2

Cascading failures typically occur following a large disturbance in power systems, such as tripping of a generating unit or a transmission line. Such failures can propagate and des…

eess.SY2024

Verification and Synthesis of Compatible Control Lyapunov and Control Barrier Functions

Hongkai Dai, Chuanrui Jiang, Hongchao Zhang +1

Safety and stability are essential properties of control systems. Control Barrier Functions (CBFs) and Control Lyapunov Functions (CLFs) are powerful tools to ensure safety and sta…

cs.CV2023

Pre-processing training data improves accuracy and generalisability of convolutional neural network based landscape semantic segmentation

Andrew Clark, Stuart Phinn, Peter Scarth

In this paper, we trialled different methods of data preparation for Convolutional Neural Network (CNN) training and semantic segmentation of land use land cover (LULC) features wi…

eess.SY2021

Verification and Synthesis of Control Barrier Functions

Andrew Clark

Control systems often must satisfy strict safety requirements over an extended operating lifetime. Control Barrier Functions (CBFs) are a promising recent approach to constructing…

eess.SY2026

Distributed Safety-Critical Control of Multi-Agent Systems with Time-Varying Communication Topologies

Shiyu Cheng, Luyao Niu, Bhaskar Ramasubramanian +2

Coordinating multiple autonomous agents to reach a target region while avoiding collisions and maintaining communication connectivity is a core problem in multi-agent systems. In p…

eess.SY2024

Modeling and Designing Non-Pharmaceutical Interventions in Epidemics: A Submodular Approach

Shiyu Cheng, Luyao Niu, Bhaskar Ramasubramanian +2

This paper considers the problem of designing non-pharmaceutical intervention (NPI) strategies, such as masking and social distancing, to slow the spread of a viral epidemic. We fo…

eess.SY2022

An Analytical Framework for Control Synthesis of Cyber-Physical Systems with Safety Guarantee

Luyao Niu, Abdullah Al Maruf, Andrew Clark +2

Cyber-physical systems (CPS) are required to operate safely under fault and malicious attacks. The simplex architecture and the recently proposed cyber resilient architectures, e.g…

cs.CR2019

Shape of the Cloak: Formal Analysis of Clock Skew-Based Intrusion Detection System in Controller Area Networks

Xuhang Ying, Sang Uk Sagong, Andrew Clark +2

This paper presents a new masquerade attack called the cloaking attack and provides formal analyses for clock skew-based Intrusion Detection Systems (IDSs) that detect masquerade a…

q-bio.PE2020

West Australian Pandemic Response: The Black Swan of Black Swans

David Cavanagh, Mark Hoey, Andrew Clark +3

The COVID-19 Pandemic has been described as the global challenge of our time, an enormous human tragedy with dramatic economic impacts. This paper describes the response and expect…

eess.SY2012

A Supermodular Optimization Framework for Leader Selection under Link Noise in Linear Multi-Agent Systems

Andrew Clark, Linda Bushnell, Radha Poovendran

In many applications of multi-agent systems (MAS), a set of leader agents acts as a control input to the remaining follower agents. In this paper, we introduce an analytical approa…

cs.IT2026

Structural Impossibility of Antichain-Lattice Partial Information Decomposition

Aobo Lyu, Andrew Clark, Netanel Raviv

Partial Information Decomposition (PID) represents multivariate mutual information via antichain-lattice that aims to specify which source groups can recover which informational co…

eess.SY2023

Cooperative Perception for Safe Control of Autonomous Vehicles under LiDAR Spoofing Attacks

Hongchao Zhang, Zhouchi Li, Shiyu Cheng +1

Autonomous vehicles rely on LiDAR sensors to detect obstacles such as pedestrians, other vehicles, and fixed infrastructures. LiDAR spoofing attacks have been demonstrated that eit…

cs.GT2021

Dynamic Information Flow Tracking for Detection of Advanced Persistent Threats: A Stochastic Game Approach

Shana Moothedath, Dinuka Sahabandu, Joey Allen +4

Advanced Persistent Threats (APTs) are stealthy customized attacks by intelligent adversaries. This paper deals with the detection of APTs that infiltrate cyber systems and comprom…

cs.LG2023

Neural Lyapunov Control for Discrete-Time Systems

Junlin Wu, Andrew Clark, Yiannis Kantaros +1

While ensuring stability for linear systems is well understood, it remains a major challenge for nonlinear systems. A general approach in such cases is to compute a combination of…

math.OC2023

Almost-Sure Safety Guarantees of Stochastic Zero-Control Barrier Functions Do Not Hold

Oswin So, Andrew Clark, Chuchu Fan

The 2021 paper "Control barrier functions for stochastic systems" provides theorems that give almost sure safety guarantees given stochastic zero control barrier function (ZCBF). U…

eess.SY2020

Control Synthesis for Cyber-Physical Systems to Satisfy Metric Interval Temporal Logic Objectives under Timing and Actuator Attacks

Luyao Niu, Bhaskar Ramasubramanian, Andrew Clark +2

This paper studies the synthesis of controllers for cyber-physical systems (CPSs) that are required to carry out complex tasks that are time-sensitive, in the presence of an advers…

cs.LG2026

BOND: License to Train with Black-Box Functions

Andrew Clark, Jack Moursounidis, Osmaan Rasouli +3

We introduce Bounded Numerical Differentiation (BOND), a perturbative method for estimating the gradients of black-box functions. BOND is distinguished by its formulation, which ad…

eess.SY2023

A Compositional Resilience Index for Computationally Efficient Safety Analysis of Interconnected Systems

Luyao Niu, Abdullah Al Maruf, Andrew Clark +2

Interconnected systems such as power systems and chemical processes are often required to satisfy safety properties in the presence of faults and attacks. Verifying safety of these…

stat.CO2015

Expanding the Computation of Mixture Models by the use of Hermite Polynomials and Ideals

Andrew Clark

Mixture models have found uses in many areas. To list a few: unsupervised learning, empirical Bayes, latent class and trait models. The current applications of mixture models to em…

cs.SI2012

SODEXO: A System Framework for Deployment and Exploitation of Deceptive Honeybots in Social Networks

Quanyan Zhu, Andrew Clark, Radha Poovendran +1

As social networking sites such as Facebook and Twitter are becoming increasingly popular, a growing number of malicious attacks, such as phishing and malware, are exploiting them.…

eess.SY2019

Secure Control under Partial Observability with Temporal Logic Constraints

Bhaskar Ramasubramanian, Andrew Clark, Linda Bushnell +1

This paper studies the synthesis of control policies for an agent that has to satisfy a temporal logic specification in a partially observable environment, in the presence of an ad…

eess.SY2019

Linear Temporal Logic Satisfaction in Adversarial Environments using Secure Control Barrier Certificates

Bhaskar Ramasubramanian, Luyao Niu, Andrew Clark +2

This paper studies the satisfaction of a class of temporal properties for cyber-physical systems (CPSs) over a finite-time horizon in the presence of an adversary, in an environmen…

eess.SY2019

Optimal Secure Control with Linear Temporal Logic Constraints

Luyao Niu, Andrew Clark

Prior work on automatic control synthesis for cyber-physical systems under logical constraints has primarily focused on environmental disturbances or modeling uncertainties, howeve…

cs.IT2025

The Whole Is Less than the Sum of Parts: Subsystem Inconsistency in Partial Information Decomposition

Aobo Lyu, Andrew Clark, Netanel Raviv

Partial Information Decomposition (PID) was proposed by Williams and Beer in 2010 as a tool for analyzing fine-grained interactions between multiple random variables, and has since…

cs.NE2013

Group theory, group actions, evolutionary algorithms, and global optimization

Andrew Clark

In this paper we use group, action and orbit to understand how evolutionary solve nonconvex optimization problems.

eess.SY2020

Control Barrier Functions for Abstraction-Free Control Synthesis under Temporal Logic Constraints

Luyao Niu, Andrew Clark

Temporal logic has been widely used to express complex task specifications for cyber-physical systems (CPSs). One way to synthesize a controller for CPS under temporal logic constr…