TAP Computational Training
Deep Learning for Astrophysics Hackathons
Organized under the TAP Computation and Data Initiative, Chi-Kwan Chan ran weekly hackathons (11 sessions) open to all TAP members in FY24. 18 participants from Astronomy, Physics, and Computer Science joined the hackathons. The sessions were designed to teach a variety of applications for deep learning in science, train on neural network learning, and provide hands-on experience working through challenging projects and solutions.
Overview doc of all the sessions
Links used for Hackathon Teaching Concepts:
Global Engagement
TAP, a partner for the IAU 2024 General Assembly held in Capetown, South Africa, was featured in the event’s poster sessions and event website. This was an exceptional opportunity to be in front of a large global audience of potential faculty, postdocs, and graduate students. TAP Faculty Member Chi-Kwan Chan represented TAP with a project poster submission and Q&A.
