10 papers
Aerial Wildfire Suppression Planning with a Hybrid CNN-Cellular Automata Fire Model
Ion Matei, Maksym Zhenirovskyy, Takuya Kurihana +4
Aerial wildfire suppression requires decisions about when, where, and how to deploy limited aircraft. We present an intervention-design framework built on a frozen hybrid convoluti…
Neural-Parameterized Cellular Automata for Wildfire Spread
Maksym Zhenirovskyy, Ion Matei, Rohit Vuppala +2
Traditional wildfire models rely on rigid, low-dimensional parameters and static fuel maps, frequently underpredicting fire spread. To address this weakness, we introduce a hybrid…
Differentiable Parameter Optimization for DAEs with State-Dependent Events
Ion Matei, Maksym Zhenirovskyy, Anthony Wong
Differential-algebraic equations (DAEs) with state-dependent events arise in systems whose continuous dynamics are constrained by algebraic equations and interrupted by mode change…
Automated BPMN Model Generation from Textual Process Descriptions: A Multi-Stage LLM-Driven Approach
Ion Matei, Maksym Zhenirovskyy, Praveen Kumar Menaka Sekar +1
Automatically reconstructing BPMN models from unstructured natural-language descriptions remains challenging due to heterogeneous modeling conventions, multilingual sources, and th…
Resilience Quantification and its Support for Operational Resilience
Ion Matei, Maksym Zhenirovskyy
We present a method to quantify a system's resilience capacity, i.e., the set of degradation magnitudes for which all functional requirements remain satisfied. These requirements c…
Ambiguity Detection and Elimination in Automated Executable Process Modeling
Ion Matei, Praveen Kumar Menaka Sekar, Maksym Zhenirovskyy +4
Automated generation of executable Business Process Model and Notation (BPMN) models from natural-language specifications is increasingly enabled by large language models. However,…
Automatic Generation of Executable BPMN Models from Medical Guidelines
Praveen Kumar Menaka Sekar, Ion Matei, Maksym Zhenirovskyy +4
We present an end-to-end pipeline that converts healthcare policy documents into executable, data-aware Business Process Model and Notation (BPMN) models using large language model…
An optimization-based approach to automated design
Ion Matei, Maksym Zhenirovskyy, John Maxwell +1
We propose a model-based, automated, bottom-up approach for design, which is applicable to various physical domains, but in this work we focus on the electrical domain. This bottom…
2D Density Control of Micro-Particles using Kernel Density Estimation
Ion Matei, Johan de Kleer, Maksym Zhenirovskyy
We address the problem of 2D particle density control. The particles are immersed in dielectric fluid and acted upon by manipulating an electric field. The electric field is contro…
Improving the Efficiency of Gradient Descent Algorithms Applied to Optimization Problems with Dynamical Constraints
Ion Matei, Maksym Zhenirovskyy, Johan de Kleer +1
We introduce two block coordinate descent algorithms for solving optimization problems with ordinary differential equations (ODEs) as dynamical constraints. The algorithms do not n…