Embedded Web Application
Advisor(s)
Dr.Kropp
Confirmation
1
Document Type
Poster
Location
ONU McIntosh Center; Activities Room
Start Date
11-4-2025 12:00 PM
End Date
11-4-2025 12:50 PM
Abstract
Due to their interactive and user-friendly interface, jupyter notebooks have become a cornerstone tool for scientists, particularly those without a computer science background. This project explores the feasibility of integrating the pymoo dashboard into Jupyter notebooks, enhancing the accessibility and usability of optimization tools for a broader audience. Key research questions guiding this investigation include: the possibility of embedding websites directly into Jupyter notebooks without the need for an external web browser, the impact on user experience when running the pymoo dashboard within a Jupyter environment, and the potential for creating a dual-mode functionality that allows the pymoo dashboard to operate seamlessly in both web-browser and Jupyter notebook modes. By addressing these questions, this research seeks to bridge the gap between advanced optimization tools and their practical application in scientific research, ultimately fostering a more inclusive and efficient computational environment.
Recommended Citation
McCluskey, Chase D., "Embedded Web Application" (2025). ONU Student Research Colloquium. 58.
https://digitalcommons.onu.edu/student_research_colloquium/2025/Posters/58
Open Access
Available to all.
Embedded Web Application
ONU McIntosh Center; Activities Room
Due to their interactive and user-friendly interface, jupyter notebooks have become a cornerstone tool for scientists, particularly those without a computer science background. This project explores the feasibility of integrating the pymoo dashboard into Jupyter notebooks, enhancing the accessibility and usability of optimization tools for a broader audience. Key research questions guiding this investigation include: the possibility of embedding websites directly into Jupyter notebooks without the need for an external web browser, the impact on user experience when running the pymoo dashboard within a Jupyter environment, and the potential for creating a dual-mode functionality that allows the pymoo dashboard to operate seamlessly in both web-browser and Jupyter notebook modes. By addressing these questions, this research seeks to bridge the gap between advanced optimization tools and their practical application in scientific research, ultimately fostering a more inclusive and efficient computational environment.