Prof Tossapon Boongoen

Profile

Prior the current appointment, he worked for Mae Fah Luang University (MFU, Thailand) between 2017-2022, as an Assoc Prof in the School of Information Technology, and the Director of MFU Research and Innovation Institute. His research areas include AI, machine learning, uncertainty and fuzzy system, data science and engineering. He has also served as associate editors of international journals like IEEE Access, PeerJ Computer Science, ICT Express, and International Journal of Artificial Intelligence.

Research

Experiences in developing machine learning (ML) and deep learning (DL) models for remote sensing and wide-area sky survey data. The former is part of Newton Institutional Link project 2020-21 (funded by British Council) that aims to detect burnt scar from satellite images and risk modelling for its future expansion, while the latter has been implemented in both previous Newton 2017-19 and GCRF 2017-19 projects with UK STFC, National Astronomical Research Institute of Thailand, University of Sheffield and GOTO project (https://goto-observatory.org). 
 

One of the major contributions is the extension of ensemble clustering methodology, especially the optimised selection of ensemble members and approximated framework for big data clustering. This also leads to the hybridisation of multiple clusterings with fundamental problems in data quality, e.g., missing values and imbalanced classes. The resulting techniques have been successfully applied to a variety of scientific problems, including detection of astronomical transient events from sky images, classification of tumour samples on gene expression data, adversarial attacks to ML-based network security systems. The last application has been investigated in contexts of ransomware and intrusion detection, as part of another Newton IAPP project funded by Royal Academy of Engineering. 

In 2023-24, he leads the project funded by Foreign, Commonwealth & Development Office: Research and Innovation for Development in ASEAN (RIDA). This is the collaboration between Aberystwyth University, MFU, Department of Forestry, Geo-Informatics and Space Technology Development Agency (Thailand).

Research Groups

Publications

Kane, K, Kirimasthong, K & Boongoen, T 2024, Available Website Names Classification Using Naive Baye. in P Jenkins, P Grace, L Yang, S Prajapat & N Naik (eds), ADVANCES IN COMPUTATIONAL INTELLIGENCE SYSTEMS, UKCI 2023. vol. 1453, Advances in Intelligent Systems and Computing, Springer Nature, GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND, pp. 259-269. 10.1007/978-3-031-47508-521
Chongwarin, J, Manorom, P, Chaichuay, V, Boongoen, T, Li, C & Chansanam, W 2024, 'Enhancing Book Recommendation Accuracy through User Rating Analysis and Collaborative Filtering Techniques', Journal of Telecommunications and the Digital Economy, vol. 12, no. 3, pp. 51-72. 10.18080/jtde.v12n3.976
Detthamrong, U, Chansanam, W, Boongoen, T & Iam-On, N 2024, 'Enhancing Fraud Detection in Banking using Advanced Machine Learning Techniques', International Journal of Economics and Financial Issues, vol. 14, no. 5, pp. 177-184. 10.32479/ijefi.16613
Cortez, T, Boongoen, T, Iam-On, N, Kirimasthong, K & Mullaney, J 2024, Image-Based Transient Detection Algorithm for Gravitational-Wave Optical Transient Observer (GOTO) Sky Survey. in N Naik, P Jenkins, P Grace, L Yang & S Prajapat (eds), UKCI 2023: Advances in Computational Intelligence Systems: Contributions Presented at the 22nd UK Workshop on Computational Intelligence (UKCI 2023), September 6–8, 2023, Birmingham, UK. Advances in Intelligent Systems and Computing, vol. 1453, Springer Nature, pp. 459-470, The 22nd UK Workshop on Computational Intelligence, Birmingham, United Kingdom of Great Britain and Northern Ireland, 06 Sept 2023. 10.1007/978-3-031-47508-5_36
Iam-On, N, Boongoen, T, Naik, N & Yang, L 2025, 'Leveraging ensemble clustering for privacy-preserving data fusion: Analysis of big social-media data in tourism', Information Sciences, vol. 686, 121336. 10.1016/j.ins.2024.121336
More publications on the Research Portal