82 citations · 118 across the 15 of their papers we have counts for
16 papers
Control Systems with Model Hierarchies: A Category-Theoretic Framework
Baike She, Tyler Hanks, James Fairbanks +1
Storage functions are widely used to relate a control system to a simpler model for analysis and controller design, and to quantify model mismatch when a controller is designed on…
A Physics-Informed Neural Networks-Based Model Predictive Control Framework for Epidemics
Aiping Zhong, Baike She, Philip E. Paré
This work introduces a physics-informed neural networks (PINNs)-based model predictive control (MPC) framework for susceptible-infected-recovered () spreading models. Existing…
Learning Linearized Models from Nonlinear Systems under Initialization Constraints with Finite Data
Lei Xin, Baike She, Qi Dou +2
The identification of a linear system model from data has wide applications in control theory. The existing work that provides finite sample guarantees for linear system identifica…
Scalable Distributed Reproduction Numbers of Network Epidemics with Differential Privacy
Bo Chen, Baike She, Calvin Hawkins +2
Reproduction numbers are widely used for the estimation and prediction of epidemic spreading processes over networks. However, conventional reproduction numbers of an overall netwo…
A Dissipativity Approach to Analyzing Composite Spreading Networks
Baike She, Matthew Hale
The study of spreading processes often analyzes networks at different resolutions, e.g., at the level of individuals or countries, but it is not always clear how properties at one…
Control of SIR Epidemics: Sacrificing Optimality for Feasibility
Baike She, Lei Xin, Shreyas Sundaram +1
We study the impact of parameter estimation and state measurement errors on a control framework for optimally mitigating the spread of epidemics. We capture the epidemic spreading…
Modeling Epidemic Spread: A Gaussian Process Regression Approach
Baike She, Lei Xin, Philip E. Paré +1
Modeling epidemic spread is critical for informing policy decisions aimed at mitigation. Accordingly, in this work we present a new data-driven method based on Gaussian process reg…
Reverse Engineering the Reproduction Number: A Framework for Data-Driven Counterfactual Analysis, Strategy Evaluation, and Feedback Control of Epidemics
Baike She, Rebecca Lee Smith, Ian Pytlarz +2
During the COVID-19 pandemic, different countries, regions, and communities constructed various epidemic models to evaluate spreading behaviors and assist in making mitigation poli…
Differentially Private Computation of Basic Reproduction Numbers in Networked Epidemic Models
Bo Chen, Baike She, Calvin Hawkins +4
The basic reproduction number of a networked epidemic model, denoted , can be computed from a network's topology to quantify epidemic spread. However, disclosure of risk…
Characterizing Compositionality of LQR from the Categorical Perspective
Baike She, Tyler Hanks, James Fairbanks +1
Composing systems is a fundamental concept in modern control systems, yet it remains challenging to formally analyze how controllers designed for individual subsystems can differ f…
Modeling Model Predictive Control: A Category Theoretic Framework for Multistage Control Problems
Tyler Hanks, Baike She, Matthew Hale +3
Model predictive control (MPC) is an optimal control technique which involves solving a sequence of constrained optimization problems across a given time horizon. In this paper, we…
Leveraging Opinions and Vaccination to Eradicate Networked Epidemics
Humphrey Leung, Zhuocong Li, Baike She +1
We introduce a multi-layer networked compartmental model that captures opinion dynamics, disease spread, risk perception, and self-interest vaccine-uptake behavior in an…
Distributed Reproduction Numbers of Networked Epidemics
Baike She, Philip E. Paré, Matthew Hale
Reproduction numbers are widely used for the estimation and prediction of epidemic spreading processes over networks. However, reproduction numbers do not enable estimation and pre…
Optimal Mitigation of SIR Epidemics Under Model Uncertainty
Baike She, Shreyas Sundaram, Philip E. Paré
We study the impact of model parameter uncertainty on optimally mitigating the spread of epidemics. We capture the epidemic spreading process using a susceptible-infected-removed (…
Peak Infection Time for a Networked SIR Epidemic with Opinion Dynamics
Baike She, Humphrey C. H. Leung, Shreyas Sundaram +1
We propose an SIR epidemic model coupled with opinion dynamics to study an epidemic and opinions spreading in a network of communities. Our model couples networked SIR epidemic dyn…
On a Network SIS Epidemic Model with Cooperative and Antagonistic Opinion Dynamics
Baike She, Ji Liu, Shreyas Sundaram +1
We propose a mathematical model to study coupled epidemic and opinion dynamics in a network of communities. Our model captures SIS epidemic dynamics whose evolution is dependent on…