IAC 2024: Implementing Low-Cost ADCS for 1U CubeSat: Insights from ALEASAT

I am happy to announce that as part of the UBC Orbit ALEASAT team, I will be co-authoring a paper for the International Astronautical Congress (IAC) 2024. The paper, titled “Implementing Low-Cost ADCS for 1U CubeSat: Insights from ALEASAT,” will be presented at the conference in Milan, Italy, from October 14-18, 2024.

Deep Learning at TRIUMF

Summary Particle reconstruction in the ATLAS detector is the practice of associating calorimeter and tracker signals particle and determining which particles caused them, with how much energy, and through what process. One crucial step in reconstruction is cell segmentation where we determine which calorimeter signals belong to which tracks from the inner tracker. Current methods to perform segmentation rely on algorithms that grow with quadratic complexity, posing a challenge for segmentation after the High-Luminosity LHC (HL-LHC) upgrade, which promises a significant increase in the number of collisions per event and, therefore, the complexity of each event. [Read More]