Prospero Naval, Jr., Ph.D.

Member of the Innovatus Editorial Board

Education

  1. Post-doctoral Studies (Swarm Robotics), Université Libre de Bruxelles
  2. Doctor of Philosophy (Electrical Engineering), University of the Philippines
  3. Master of Engineering (Computer Science), Kyoto University
  4. Master of Science in Electrical Engineering, University of the Philippines
  5. Bachelor of Science (Electrical Engineering), University of the Philippines

Research Interest

  • Deep Learning, Reinforcement Learning
  • Applications of AI to Health, Environment, and Education
  • Probabilistic Machine Learning and Decision Making
  • Swarm Robotics and Evolutionary Computation

Innovation

  • Leaders in Innovation Fellow, UK Royal Academy of Engineering / Asian Institute of Management
  • Founder, Fish-i Analytics, Inc. (a university spin-off)

Publication Highlights

  1. A.A.E. Ambita, E.N.V. Boquio, and P.C. Naval, Jr., COViT-GAN: Vision Transformer for COVID-19 Detection in CT Scan Images with Self-Attention GAN for Data Augmentation, 30th International Conference on Artificial Neural Networks (ICANN2021), September 14-17, 2021
  2. L.G.C Bautista and P.C. Naval, Jr., CLRGaze: Contrastive Learning of Representations for Eye Movement Signals, 29th European Signal Processing Conference, Dublin, Ireland, August 23-27, 2021
  3. A.B. Labao, M.A.M Martija, and P.C. Naval, Jr., A3C-GS: Adaptive Moment Gradient Sharing with Locks for Asynchronous Actor-Critic Agents., IEEE Transactions on Neural Networks and Learning Systems, Vol. 32, No. 3, March 2021.
  4. L.G.C Bautista and P.C. Naval, Jr., CLRGaze: Contrastive Learning of Representations for Eye Movement Signals, International Conference on Pattern Recognition, Milan, Italy, Jan 10-15, 2021
  5. M.A.M Martija and P.C. Naval, Jr., SynDHN: Multi-Object Fish Tracker Trained on Synthetic Underwater Videos, International Conference on Pattern Recognition, Milan, Italy, Jan 10-15, 2021
  6. J.P.T. Yusiong and P.C. Naval, Jr., A Semi-supervised Approach to Monocular Depth Estimation, Depth Refinement, and Semantic Segmentation of Driving Scenes using a Siamese Triple Decoder Architecture, Informatica 44 (2020) pp.437-445
  7. K.D delas Penas, E.A. Villacorte, P.T. Rivera, and P.C. Naval, Jr., Automated Detection of Helminth Eggs in Stool Samples using Convolutional Neural Networks, Proc. of 2020 IEEE Region 10 Conference (TENCON 2020), Osaka, Japan, November 16-19, 2020. [Online]
  8. L.G.C. Bautista and P.C. Naval, Jr., Towards Learning to Read Like Humans, 12th International Conference on Computational Collective Intelligence
  9. J.A.R. Sarmiento and P.C. Naval, Jr., Behavioral Phenotyping for Autism Spectrum Disorder Biomarkers using Computer Vision., Journal of Image and Graphics, Vol. 8, No. 2, June 2020.
  10. A.B. Labao, P.C. Naval, Jr., D.L.T. Yap, and H.T. Yap, Using Deep Belief Networks to Understand Propensity for Livelihood Change in Rural Coastal Community to Further Enhance Conservation, Conservation Biology, 34(4) 2020 pp. 1008-1016.
  11. J.P. Yusiong and P.C. Naval, Jr., Unsupervised Monocular Depth Estimation of Driving Scenes Using a Siamese Convolutional LSTM Networks., International Journal of Innovative Computing, Information and Control 16(1):2020
  12. J.P. Yusiong and P.C. Naval, Jr., DFRNets: Unsupervised Monocular Depth Estimation Using a Siamese Architecture for Disparity Refinements., Pertanika Journal of Science and Technology 28(1):163-177 (2020)
  13. D. Valerio and P.C. Naval, Jr., PRTNets: Cold-Start Recommendations Using Pairwise Ranking and Transfer Networks, LNAI 12033, pp. 416 - 430, Springer-Verlag, 2020.
  14. A.A.E. Ambita, E.N.V. Boquio, and P.C. Naval, Jr., Locally Adaptive Regression Kernels and Support Vector MAchines for the Detection of Pneumonia in Chest X-Ray Images, LNAI 12034, pp. 129 - 140, Springer-Verlag, 2020.
  15. M.A. Martija, J.I. Dumbrique, and P.C. Naval, Jr., Underwater Gesture Recognition using Classical Computer Vision and Deep Learning Techniques, Journal of Image and Graphics, Vol. 8, No. 1, March 2020.
  16. E.A.G Abad, J.R.A. Ferrer, and P.C. Naval Jr, Phishing Website Classification using Features of Web Addresses and Web Pages, Proc. 20th Philippine Computing Science Conference, Baguio City, Philippines, March 18-21, 2020.
  17. R.R.A. Pineda, and P.C. Naval, Jr., A Comparison of SVM and kNN on the Classification of Jewel Damselfish Activity , 12th Regional Conference on Computer Information and Engineering 2019, Vientiane, Laos, November 25-26, 2019.
  18. M.A. Martija, Jansen Domoguen, and P.C. Naval, Jr., How Deep is Your Law: Predicting Associations between Cases in Philippine Jurisprudence, Proc. of 2019 IEEE Region 10 Conference (TENCON 2019), Kerala, India, October 17-20, 2019.
  19. J.A.R. Sarmiento, and P.C. Naval, Jr., Behavioral Phenotyping for Autism Spectrum Disorder Biomarkers using Computer Vision , Journal of Image and Graphics.
  20. C.T. Tolentino, A. Uy, and P.C. Naval, Jr., Air Drums: Playing Drums Using Computer Vision, International Symposium on Multimedia and Communication Technology 2019, Quezon City, Philippines, August 19-21, 2019.
  21. J.K.L. Domoguen, J.J.P. Suarez, and P.C. Naval, Jr., TAG: Nucleus Detection in Colorectal Adenocarcinomas Histology Images using Local Texture, Appearance, and Gradient Features, 3rd IEEE International Conference on Imaging, Signal Processing, and Communications (ICISPC 2019) Singapore, July 27-29, 2019.
  22. A.B. Labao and P.C. Naval, Jr., Cascaded Deep Network Systems with Linked Ensemble Components for Underwater Fish Detection in the Wild, Ecological Informatics, Vol 52, July 2019, pp. 103-121. https://doi.org/10.1016/j.ecoinf.2019.05.004
  23. J.C. Beltran, P. Valdez, P.C. Naval, Jr., Predicting Protein-Protein Interactions based on Biological Information using Extreme Gradient Boosting, 16th IEEE International Conference on Computational Intelligence in Bioinformatics and Computational Biology, Siena, Italy, July
    24. 9-11, 2019.
  24. J.L.C. Capistrano, J.J.P Suarez, and P.C. Naval, Jr., SALSA: Detection of Cybertrolls using Sentiment, Aggression, Lexical and Syntactic Analysis of Tweets, Proc. of the 9th International Conference on Web Intelligence, Mining, and Semantics, June 24-26, 2019, Seoul,Korea.
  25. J.P. Yusiong and P.C. Naval, Jr., Multi-scale Autoencoders in Autoencoder for Semantic Image Segmentation, LNAI 11431 Part I, pp. 587-599, Springer-Verlag, 2019.
  26. A.B. Labao and P.C. Naval, Jr., Simultaneous Localization and Segmentation of Fish Objects using Multi-task CNN and Dense CRF, LNAI 11431 Part I, pp. 600-612, Springer-Verlag, 2019.
    27. J. Geronimo and P.C. Naval, Jr., Osteoporosis Detection from Bone Texture Radiograph Images using Convolutional Neural Network, ,Proc. 11th Asian Conference on Intelligent Information and Database Systems (ACIIDS 2019), Yogyakarta, Indonesia. J.R. San Gabriel, E. Tan and P.C. Naval, Jr., , Computer Vision-based Fall Detection using CNN-LSTM, Proc. 11th Asian Conference on Intelligent Information and Database Systems (ACIIDS 2019), Yogyakarta, Indonesia.
  27. J.P. Yusiong and P.C. Naval, Jr., AsiANet: Autoencoders in Autoencoder for Unsupervised Monocular Depth Estimation, Proc. 2019 IEEE Winter Conference on Applications of Computer Vision, Hawaii, USA, January 8-10, 2019.
  28. A.B. Labao, C.R. Raquel, and P.C. Naval, Jr., Induced Exploration on Policy Gradients by increasing Actor Entropy using Advantage Target Regions, Proc. 25th International Conference on Neural Information Processing, Siem Reap, Cambodia, December 13-16, 2018.
  29. R. Daroya, D. Peralta, and P.C. Naval, Jr., Alphabet Sign Language Image Classification using Deep Learning, Proc. of 2018 IEEE Region 10 Conference (TENCON 2018), Jeju, South Korea, October 28-31, 2018.
  30. A.B. Labao and P.C. Naval, Jr., Stabilizing Actor Policies by Approximating Advantage Distributions from K Critics, Proc. 2018 International Conference on Pattern Recognition, Beijing, August 20 to 24, 2018.
  31. A.B. Labao and P.C. Naval, Jr., AC2: A Policy Gradient Actor with Primary and Secondary Critics, Proc. International Joint Conference on Neural Networks, Rio de Janeiro, July 8 to 13, 2018.
  32. L.K. Cornelio, M.A. del Castillo, and P.C. Naval, Jr., U-ISLES: Ischemic Stroke Lesion Segmentation Using TensorFlow U-Net, Intelligent Systems and Applications, Springer, 2018.
  33. C.B. Antonio, L.G.C. Bautista, A.B. Labao, and P.C. Naval, Jr., Vertebra Fracture Classication from 3D CT Lumbar Spine Segmentation Masks using a Convolutional Neural Network, Intelligent Information and Database Systems. ACIIDS 2018. Lecture Notes in Artificial Intelligence, vol 10752, pp. 449-458, Springer.
  34. K. delas Penas, P.T. Rivera, and P.C. Naval, Jr., Analysis of Convolutional Neural Networks and Shape Features for Detection and Identification of Malaria Parasites on Thin Blood Smears, Intelligent Information and Database Systems. ACIIDS 2018. Lecture Notes in Artificial Intelligence, pp. 472-481, vol 10752, Springer.
  35. A.B. Labao, M.A. Clutario, and P.C. Naval, Jr., Classication of Bird Sounds using Codebook Features, Intelligent Information and Database Systems. ACIIDS 2018. Lecture Notes in Artificial Intelligence, vol 10751, pp. 223-233, Springer.
  36. J.E.Z. Sy, M.G.Q. Aydinan, and P.C. Naval Jr, Prediction of MRT-3 Passenger Entrance Volume using Support Vector Machines, Proc. 18th Philippine Computing Science Conference, Cagayan de Oro City, Philippines, March 15-17, 2018.

Back to editorial board
About Us
Contact Us

[innovatus@uap.asia] | [Pearl Dr, Ortigas Center, Pasig, 1605, Metro Manila]