Alexis Pascual

Picture of Alexis Pascual

Thesis Topic

Machine Learning and AI in Planetary Exploration Applications

Current Degree

Ph.D. Candidate in Electrical and Computer Engineering with Collaborative Specialization in Planetary Science and Exploration

Past Degrees

  • 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

Publications

  1. B. Stefanuk et al., “Detecting Novelties in Planetary Surfaces with Autoencoders,” International Symposium on Artificial Intelligence, Robotics, and Automation in Space, Pasadena, CA, 2020.
  2. 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.
  3. J. D. Newman et al., “Planning Team Operations For The Canmoon Lunar Sample Return Analogue Mission,” LPI, no. 2326, p. 2196,2020.
  4. A. Pascual, K. McIsaac, and G. Osinski, “Natural Scene Rock Image Classification with Combinational Fully Connected Networks,” AGUFM, vol. 2019, pp. P43E-3515, 2019.
  5. 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
  6. G. R. Osinski et al., “The CanMars Mars Sample Return analogue mission,” Planet. Space Sci., vol. 166, pp. 110–130, 2019.