1 citations · 1 across the 5 of their papers we have counts for
6 papers
NeuralBES: A Differentiable, Control-Aware Emulator for Scalable Building Energy Modeling
Ting-Yu Dai, Takuya Kurihana, Wing Yee Au +1
Demand-side flexibility i.e. forecasting, shifting, and curtailing residential energy loads, depends on thermal models trusted across millions of heterogeneous buildings. Existing…
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…
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…
Harnessing Rich Multi-Modal Data for Spatial-Temporal Homophily-Embedded Graph Learning Across Domains and Localities
Takuya Kurihana, Xiaojian Zhang, Wing Yee Au +1
Modern cities are increasingly reliant on data-driven insights to support decision making in areas such as transportation, public safety and environmental impact. However, city-lev…
Breaking the Curse of Knowledge: Designing Personalized Jargon Support for Real-Time Online Meetings
Yifan Song, Yijun Liu, Wing Yee Au +3
Cross-disciplinary communication is often hindered by specialized language (i.e., jargon) and uneven background knowledge. Recent advances in speech-to-text and large language mode…