Selected work

Representative Papers

Multi-Pair Fidelity-Aware Rate Allocation in a Quantum Network: Approximation Schemes

Aug 11, 2026

This work addresses the rate allocation problem for multiple user pairs in quantum networks under practical constraints, including limited link capacities, probabilistic entanglement swapping, and heterogeneous end-to-end fidelities. The study investigates three optimization objectives: maximizing total throughput, maximizing total throughput subject to minimum rate guarantees, and achieving max-min fairness. It establishes, for the first time, that all three fidelity-aware rate allocation problems are NP-hard. To tackle these challenges, the authors propose a unified fully polynomial-time approximation scheme (FPTAS) based on dynamic programming that jointly optimizes transmission rates and end-to-end fidelity. Extensive experiments on random quantum network topologies demonstrate the efficiency and practicality of the proposed algorithm.

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Resource-Aware Intrusion Detection in Infrastructure Networks: A Game-Theoretic Approach

Aug 06, 2026

This study addresses the challenge posed by intelligent, path-adaptive attackers in resource-constrained infrastructure by modeling attacker-defender interactions as a graph-based security game subject to resource and false alarm constraints. Through rigorous analysis of the existence, structure, and computational complexity of Nash and Stackelberg equilibria under varying information structures, the work reveals how the attacker’s observational capability regarding defense strategies critically shapes equilibrium behavior. The paper introduces scalable solution algorithms tailored for both pure- and mixed-strategy settings and characterizes the ordinal relationship and coincidence conditions between the two equilibrium payoff profiles. Experimental results demonstrate that the proposed algorithms closely approximate full enumeration baselines on tractable instances while efficiently scaling to large, non-enumerable scenarios.

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A Tutorial on Symbolic Structural Identifiability Analysis of ODE Models in Julia

May 17, 2026

This work addresses the structural identifiability of ordinary differential equation (ODE)-based mechanistic models—specifically, whether model parameters can be uniquely determined from ideal observational data—and proposes a unified symbolic analysis framework implemented in Julia. Built upon the StructuralIdentifiability.jl package, the framework integrates symbolic computation with parameter-output mapping analysis to support assessments of local and global identifiability, observability, and extraction of identifiable parameter combinations. As the first fully reproducible tutorial within the SciML ecosystem, it not only enables model reparameterization and informs experimental design but also demonstrates its efficacy across seven representative case studies spanning epidemiology, pharmacokinetics, and other domains, thereby offering both a practical workflow and theoretical foundation for modeling complex dynamical systems.

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Recent publications

Latest Papers

Multi-Pair Fidelity-Aware Rate Allocation in a Quantum Network: Approximation Schemes

Aug 11, 2026

This work addresses the rate allocation problem for multiple user pairs in quantum networks under practical constraints, including limited link capacities, probabilistic entanglement swapping, and heterogeneous end-to-end fidelities. The study investigates three optimization objectives: maximizing total throughput, maximizing total throughput subject to minimum rate guarantees, and achieving max-min fairness. It establishes, for the first time, that all three fidelity-aware rate allocation problems are NP-hard. To tackle these challenges, the authors propose a unified fully polynomial-time approximation scheme (FPTAS) based on dynamic programming that jointly optimizes transmission rates and end-to-end fidelity. Extensive experiments on random quantum network topologies demonstrate the efficiency and practicality of the proposed algorithm.

0 citationsRead paper

Resource-Aware Intrusion Detection in Infrastructure Networks: A Game-Theoretic Approach

Aug 06, 2026

This study addresses the challenge posed by intelligent, path-adaptive attackers in resource-constrained infrastructure by modeling attacker-defender interactions as a graph-based security game subject to resource and false alarm constraints. Through rigorous analysis of the existence, structure, and computational complexity of Nash and Stackelberg equilibria under varying information structures, the work reveals how the attacker’s observational capability regarding defense strategies critically shapes equilibrium behavior. The paper introduces scalable solution algorithms tailored for both pure- and mixed-strategy settings and characterizes the ordinal relationship and coincidence conditions between the two equilibrium payoff profiles. Experimental results demonstrate that the proposed algorithms closely approximate full enumeration baselines on tractable instances while efficiently scaling to large, non-enumerable scenarios.

0 citationsRead paper

A Tutorial on Symbolic Structural Identifiability Analysis of ODE Models in Julia

May 17, 2026

This work addresses the structural identifiability of ordinary differential equation (ODE)-based mechanistic models—specifically, whether model parameters can be uniquely determined from ideal observational data—and proposes a unified symbolic analysis framework implemented in Julia. Built upon the StructuralIdentifiability.jl package, the framework integrates symbolic computation with parameter-output mapping analysis to support assessments of local and global identifiability, observability, and extraction of identifiable parameter combinations. As the first fully reproducible tutorial within the SciML ecosystem, it not only enables model reparameterization and informs experimental design but also demonstrates its efficacy across seven representative case studies spanning epidemiology, pharmacokinetics, and other domains, thereby offering both a practical workflow and theoretical foundation for modeling complex dynamical systems.

0 citationsRead paper