Yong Ann Voeurn
February 22, 2023 2024-02-22 15:52Yong Ann Voeurn
Mr. Voeurn Yong Ann is a lecturer of Computer Science at the Cambodia
University of Technology and Science. His area of research interest
lies at the intersection of Robotics, Industrial Management, and
Digital Transformation. He is particularly interested in developing a
digital transformation strategy for small/medium manufacturers with a
special emphasis on digital twin smart manufacturing. Apart from his
career in academia, Mr. Yong Ann is also a co-founder of ARM Robotics,
a company that provides industrial automation solutions to
manufacturing enterprises and SMEs in Cambodia. His company is
providing innovative and cost-effective automation solutions to
maximize manufacturing productivity and quality while lowering
production costs. He’s a member of World Robotics Olympiad as National
Committee.
Research Interests
Teaching and Supervision
Qualifications
- Applied Optimization: Convex Optimization, Nonlinear programming,
Mixed-integer programming - Robotics: Manipulation, Human-Robot Interaction, robot vision.
- Dynamics & Control: Dynamical Modeling, Limit Cycles, and Dynamics
with Constrained, Non-linear control, Adaptive control, Impedance
control, and Computational mechanics. - Industrial engineering: Digital Twin Smart Manufacturing, Industrial management, and process, Quantitative Tools for Quality and Productivity, Manufacturing Process Control, Product life cycle management.
- Basics Programming
- Advanced Mathematics for Engineering
- BSc. Mechatronics Engineering, Ufa State Aviation Technical
University, Russia, 2019 - Post Graduate Diploma, Industrial Manufacturing economics &
management, Ufa State Aviation Technical University - Master of Computer Science, Innopolis University, Russia 2021
Contact Details
- Email: yongann.voeurn@camtech.edu.kh
- Tel: 855 96 8111 007
- Linkedin: https://www.linkedin.com/in/
yong-ann-voeurn-a369341ba/
Publications
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
Contact Details:
• Email: pharino.chum@gmail.com
• Tel: (855) 89-910-904
• Linkedin: www.linkedin.com/in/pharino-chum-446b5a85
