Machine Learning and AI in Planetary Exploration Applications
Ph.D. Candidate in Electrical and Computer Engineering with Collaborative Specialization in Planetary Science and Exploration
- BS in Physics, Ateneo de Manila University (2015)
- BS in Materials Science and Engineering, Ateneo de Manila University (2015)
- MESc in Electrical and Computer Engineering with Collaborative Specialization in Planetary Science and Exploration
- B. Stefanuk et al., “Detecting Novelties in Planetary Surfaces with Autoencoders,” International Symposium on Artificial Intelligence, Robotics, and Automation in Space, Pasadena, CA, 2020.
- A. D. Pascual, J. Kissi-Ameyaw, G. R. Osinski, and K. Mcisaac, “Pixel-wise Classification And Autonomous Image Analysis In A Real-time Rover Operations Scenario: Lessons Learned From The Canmoon Analogue Mission,” LPI, no. 2326, p. 1351, 2020.
- J. D. Newman et al., “Planning Team Operations For The Canmoon Lunar Sample Return Analogue Mission,” LPI, no. 2326, p. 2196,2020.
- A. Pascual, K. McIsaac, and G. Osinski, “Natural Scene Rock Image Classification with Combinational Fully Connected Networks,” AGUFM, vol. 2019, pp. P43E-3515, 2019.
- A. D. P. Pascual, J. M. Szoke-Sieswerda, L. Shu, K. McIsaac, G. R. Osinski, “Towards Natural Scene Rock Image Classification with Convolutional Neural Networks”, presented at the IEEE CCECE 2019, Edmonton, AB, Canada, 2019
- G. R. Osinski et al., “The CanMars Mars Sample Return analogue mission,” Planet. Space Sci., vol. 166, pp. 110–130, 2019.