معرفی
Luisa Capannolo is a Research Scientist at Boston University working in the Department of Astronomy. She originally hails from L'Aquila, Italy, and moved to the United States in 2014 to pursue her PhD at Boston University after obtaining her Bachelor's and Master's degrees in Physics and Space Physics from the University of L'Aquila in Italy.
Education:
- PhD in Astronomy - Boston University - 2020
- Laurea Magistrale (Master's Degree) in Physics (Major: Space Physics & Astrophysics) - University of L'Aquila (Italy) - 2014
- Laurea Triennale (Bachelor's Degree) in Physics - University of L'Aquila (Italy) - 2011
Luisa's research focuses on Space Physics, specifically the precipitation of energetic particles into Earth's upper atmosphere driven by plasma waves in the magnetosphere. Her work involves analyzing data from various spacecraft including high-budget missions like Van Allen Probes and POES, as well as low-budget CubeSats like FIREBIRD and AC6. She has developed innovative machine learning techniques, particularly LSTM-based deep learning models, to automatically identify and classify electron precipitation events by their driving mechanisms (wave-driven vs. current sheet scattering). Her research has significant implications for understanding space weather effects and atmospheric chemistry.
Analysis of her publication record reveals a strong focus on relativistic electron precipitation phenomena, with a clear evolution toward incorporating machine learning techniques to solve complex classification problems in space physics. Her recent work demonstrates increasing sophistication in applying deep learning to analyze satellite data and categorize precipitation events by their underlying physical mechanisms.
Scientific Awards:
- AGU 2021 Fred L. Scarf Award for outstanding dissertation in solar-planetary science
- Young Scientist Award at URSI 2021
- Honorable Mention at URSI 2020 Student Paper Competition
- Outstanding Student Presentation Award at AGU 2018
- Best student poster award at GEM 2018
Luisa has secured significant research funding as PI and Co-PI on multiple NASA and NSF grants totaling over $1.5 million. She mentors both undergraduate and graduate students at Boston University, including primary supervision of Yi-Ting Chen and Andrew Staff, and co-supervision of Sheng Huang and Alec Daily with Prof. Wen Li. Her work bridges space physics with machine learning, creating novel approaches to analyze complex space environment data.
