Given the many disciplines that encompass ML/DL, it is important that we as researchers better understand academics with differing backgrounds than our own to produce valued contributions. In this in-person 2-hour social, we pair participants together based on differing levels of experience in related disciplines of ML/DL. These pairings would be determined by having participants write their domain of experience on a nametag, then asking participants to find and chat with another person with differing experience. For example, suppose Researcher A identifies as being highly experienced in Neuroscience but has little to no experience in Semi-Supervised Learning. Researcher A could then be paired with Researcher B, who has a great background in Semi-Supervised Learning but has had no exposure to Neuroscience. These interactions could allow us to form better connections across disciplines and build a better understanding of the vast landscape of ML/DL.

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