Juhee Bae
Senior Lecturer in Informatics
School of Informatics
Room PA520J
Phone 0500-448910
Back 5/4/2025 11:30 PM
Juhee Bae is a Senior Lecturer (Assistant Professor) in the Department of Information Technology at the University of Skövde, Sweden, where she is part of the AI research group, focusing on machine learning, visual analytics, and explainable AI.
She received her Ph.D. in Computer Science from North Carolina State University. She has been awarded a merited teaching award (2023) and a mobility grant for collaborating at a Belgian university (2020). Actively involved in professional activities, she serves on editorial boards and organizes conferences. It is her passion to connect research and education and regularly presented talks on predictive machine learning and explainable AI. She is also course co-ordinator for Explainable AI.
- Google Scholar publications
- OrcID: 0000-0002-2415-7243
Research
Publications
Projects
2024
Operations Research Forum
2024. Article. https://doi.org/10.1007/s43069-023-00271-y
3rd International Conference on Water Management in Changing Conditions: Book of abstracts
2024. Conference paper, oral presentation with abstract.
Sustainable Production through Advanced Manufacturing, Intelligent Automation and Work Integrated Learning: Proceedings of the 11th Swedish Production Symposium (SPS2024)
2024. Conference paper.
https://doi.org/10.3233/ATDE240202
2022
Distributed Computing and Artificial Intelligence, Volume 1: 18th International Conference
2022. Conference paper. https://doi.org/10.1007/978-3-030-86261-9_7
2021
IEIM 2021: The 2nd International Conference on Industrial Engineering and Industrial Management
2021. Conference paper. https://doi.org/10.1145/3447432.3447435
2020
ICVISP 2020: Proceedings of the 2020 4th International Conference on Vision, Image and Signal Processing
2020. Conference paper. https://doi.org/10.1145/3448823.3448883
ACM Computing Surveys
2020. Article.
https://doi.org/10.1145/3340960
Metallurgical and materials transactions. B, process metallurgy and materials processing science
2020. Article.
https://doi.org/10.1007/s11663-020-01853-5
2019
Data science in Practice
2019. Chapter in book. https://doi.org/10.1007/978-3-319-97556-6_8
Proceedings - 6th International Symposium on Computational and Business Intelligence, ISCBI 2018
2019. Conference paper. https://doi.org/10.1109/ISCBI.2018.00027
2018
2017
Finished projects
Can AI streamline the iron and steel industry?
The iron and steel industry needs to be streamlined and the amount of scrap reduced to increase returns. What is required is a faster and more reliable production with stricter tolerances – then better products are created that reach the customer faster. This project, INSITE-X, will develop an AI-based prototype for detailed simulation of dynamic production-behaviour of critical machines, to increase process understanding and control.
March 2021 - February 2024 InformaticsSTRATUS – AI for climate adaption
This project aims to identify, adjust and implement AI methods to improve and create a more resilient drinking water production and distribution, where the operators at the drinking water plants are supported in their decision making processes.
November 2021 - November 2023 InformaticsSwedish Metal
The project will create new values for the Swedish metal industry. This will be done through the use and development of recent data analysis techniques. By doing so, one will find currently hidden relationships between known and unknown process parameters and the resulting product quality.
October 2018 - October 2021 InformaticsUnderstanding Human Migration
The complex interactions among socio-demographic, climatic, economic environments, and possibly legal/institutional situations involve many factors that can influence patterns of population dynamics. In this project, we plan to resolve the limitation of machine learning by providing an explainable predictive model that allows users to try out ‘what-if’ scenarios by adding interactive input at a specific point in the time-series.
October 2019 - October 2020 InformaticsA smarter society through Big Data analytics
An unprecedented growth of data, fed by novel technologies, user behaviour and business models, is one of the most dramatic and important developments in both ICT and society at large. Most of this is Big Data, characterised by vast volume, high velocity, large variety and unknown veracity. These properties pose significant challenges when collecting, managing and processing data.
January 2015 - January 2020 Informatics