Pharino ChumJuly 31, 2021 2021-10-08 9:35
Mr. Pharino Chum
Dean, Faculty of Engineering
Mr. Pharino Chum is the Dean of Faculty of Engineering of Cambodia University of Technology and Science in Kingdom of Cambodia. Trained in Information and Communications Engineering, he joint various universities in Cambodia and Ministry of Information successfully launched first ever Robocon Cambodia in 2014. He has engaging in developing academic program for engineering degree for top university and institutes in Cambodia as engineering professional. Mr. Pharino Chum, is completing his PhD in Human Centered Studies Major in Information and Communication Engineering from Tokyo Institute of Technology in Japan, thanked to kindness of scholarship program from people of Japan thought JICA program. He graduated master degree in Electrical and Electronics Engineering from Chung-Ang University from Republic of Korea through Chung-Ang University Young Scientist Scholarship program. With engineering expertise and enthusiastic in advance robotic and biomedical engineering, he received various grants inform of researches and scholarship, including grant for developing prototype mobile robot for disable patient using brain-computer interface technology. His research interests aim to promote sustainable development for developing countries through technology in the context of social and environmental impact. He is a member of Robocon Cambodia Committee and IEEE fellow.
Teaching and Supervision
- Brain-Computer Interface
- Machine Learning
- Artificial Intelligence
- Digital Entrepreneurship
- Ph.D in Information and Communications Engineering, Tokyo Institute of Technology, Japan (Expected 2021)
- M.A in Electrical Engineering, Chung-Ang University, South Korea
- BSc. in Electrical and Electronic Engineering, Institute of Technology of Cambodia
1. Park, S. M., Yu, X., Chum, P., Lee, W. Y., & Sim, K. B. (2017). Symmetrical feature for interpreting motor imagery EEG signals in the brain-computer interface. Optik, 129, 163–171. https://doi.org/10.1016/j.ijleo.2016.10.047
2. Yu, X., Chum, P., & Sim, K. B. (2014). Analysis the effect of PCA for feature reduction in non-stationary EEG based motor imagery of BCI system. Optik, 125(3), 1498–1502. https://doi.org/10.1016/j.ijleo.2013.09.013
3. Pharino, C. (2015). A Comparison Study for an Optimal Common Spatial Pattern Algorithm for EEG Signal Classification applicable to BCI Systems. 8TH AUN/SEED-NET INT’L CONFERENCE ON EEE 2014, 1–14.
4. Yu, X., Park, S. M., Ko, K.-E., Chum, P., & Sim, K. (2013). A study on STFT Feature Extraction of Motor Imagery Brain-Computer Interface. Proceedings of KIIS Spring Conference, 23(1), 8726.
5. Pharino Chum, Park, S.-M., & Kwang-Eun Ko and Kwee-Bo Sim. (2013). VCSP Method for EEG Feature Extraction of Motor Imagery Brain-Computer Interface. Proceedings of KIIS Spring Conference, 23(1), 115–116.
6. Yu, X., Park, S., Ko, K., Pharino, C., & Sim, K. (2012). Discriminative Power Band Feature Selection using PCA for Motor Imagery Classification in EEG-based BCI System. Proceedings of KIIS Fall Conference, 37–38.
7. Chum, P., Park, S.-M., Ko, K.-E., & Sim, K.-B. (2012). Particle swarm optimization based optimal spatial-spectral-temporal component search in motor imagery brain-computer interface. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics): Vol. 7425 LNCS. https://doi.org/10.1007/978-3-642-32645-5_59
8. Chum, P., Park, S. M., Ko, K. E., & Sim, K. B. (2012). Particle swarm optimization based optimal spatial-spectral-temporal component search in motor imagery brain-computer interface. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7425 LNCS, 469–476. https://doi.org/10.1007/978-3-642-32645-5_59
9. Chum, P., Park, S., Ko, K., & Sim, K. (2012). Improved Method for Extracting Optimal Time-Frequency EEG Signal Feature. Proceedings of KIIS Spring Conference 2012, 22(1), 143–144.
10. Chum, P., Park, S., Ko, K., & Sim, K. (2012). Orthonormal Polynomial based Optimal EEG Feature Extraction for Motor Imagery Brain-Computer Interface. Journal of Korean Institute of Intelligent Systems, 22(6), 793–798.
11. Chum, P., Park, S., Ko, K., & Sim, K. (2012). Orthonormal Polynomial based Optimal EEG Feature Extraction for Motor Imagery Brain-Computer Interface. Proceedings of KIIS Fall Conference 2012, 22(2), 19–20.
12. Chum, P., Park, S. M., Ko, K. E., & Sim, K. B. (2012). Optimal EEG feature selection by genetic algorithm for classification of imagination of hand movement. IECON Proceedings (Industrial Electronics Conference), 1561–1566. https://doi.org/10.110/IECON.2012.6388508
13. Chum, P., Kim, J., Park, S., Ko, K., & Sim, K. (2012). Particle Swarm Optimization based Automatic Feature Selection for Spatio-Spectral- Temporal Filtering in Brain Computer Interface. International Conference on Smart Convergence Technologies and Applications 2012, 2(3), 2012.
14. Chum, P., Park, S.-M. M., & Sim, K. B. (2013). Parallel model feature extraction to improve performance of a BCI system. Journal of Institute of Control, Robotics and Systems, 19(2012), 1022–1028. https://doi.org/10.5302/J.ICROS.2013.13.1930.
Service and Leadership:
• Cambodia Robocon Committee
• Email: email@example.com
• Tel: (855) 89-910-904
• Linkedin: www.linkedin.com/in/pharino-chum-446b5a85