Contact

[email protected]

Curriculum Vitae
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Dr. Melvin Kong Cabatuan

Full Professor

Educational Background

PhD in Electronics and Communications Engineering
De La Salle University

Master of Engineering
Nara Institute of Science and Technology (NAIST), Japan
Division of Information Science – Media Informatics

BS in Electronics and Communications Engineering
CIT University, Cebu City

Dr. Melvin Kong Cabatuan is an Associate Professor at De La Salle University. His research focuses on artificial intelligence, computer vision, health informatics, and machine learning applications. Among his research works with students had garnered multiple best paper awards including, “Deep Learning-based Facial Expression Recognition and Analysis for Filipino Gamers”, best paper award  from the 1st Research Conference on Computer, Electronics and Control Engineering 2019, and “Autonomous Spherical Surveillance Robot with Vision-Based Human Recognition and Tracking”, award from the 5th International Conference on Computing, Engineering and Emerging Technologies in Singapore, World Academy of Research in Science and Engineering. He is an active member of the Institute of Electronics Engineers of the Philippines (IECEP) and the Institute of Electrical and Electronics Engineers  (IEEE).

Research Interest

  • Artificial Intelligence 
  • Computer Vision
  • Health Informatics
  • Machine Learning Applications

Selected Publications

  • Cabatuan, M. K., Dadios, E. J. P., Gan Lim, L. A., Carandang, J. S., Punzalan, E. C. R., Enriquez, M. L. D., … & Naguib, R. N. (2017). Feature driven development of a smartphone based vision-aware mhealth framework. Journal of Engineering and Applied Sciences, 12(10), 2762.
  • Sena, J. R., & Cabatuan, M. (2019). Deep Learning-based Facial Expression Recognition and Analysis for Filipino Gamers. International Journal of Recent Technology and Engineering, 8(2), 1822.
  • Galleto Jr, F. A., Cabatuan, M. K., Africa, A. D. M., Maniquiz-Redillas, M. C., Navaluna, J. M., Herrera, J. C. Q., … & Redillas, M. C. F. R. (2022). Bioretention systems optimization and design characterization model using fuzzy rough set theory. Water, 14(13), 2037.
  • Tupal, I., Cabatuan, M., & Manguerra, M. (2022, December). Recognizing Filipino Sign Language with InceptionV3, LSTM, and GRU. In 2022 IEEE 14th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM) (pp. 1-5). IEEE.
  • Rabano, S. L., Cabatuan, M. K., Sybingco, E., Dadios, E. P., & Calilung, E. J. (2018, November). Common garbage classification using mobilenet. In 2018 IEEE 10th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM) (pp. 1-4). IEEE. 
  • Hao, E. C. C., Lim, G. B. S., Cabatuan, M. K., Sybingco, E., & Dulay, A. (2022, November). CNN-based Baybayin Character Recognition on Android System. In TENCON 2022-2022 IEEE Region 10 Conference (TENCON) (pp. 1-6). IEEE.

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2401 Taft Avenue, Malate 1004, Manila, Philippines

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