Answering an unanswered research question is a struggle. You do not know what the solution is, what it might look like, or if it even exists.
In Chapter 1 of Not My Thesis, Tal Einav talks about his particular version of this struggle, when building mathematical models to predict the unpredictable behavior of antibodies binding viruses or of enzymes binding DNA. Building a model that predicts complex data is easy; rather, the challenge is finding a model that uses a few simple ideas to (mostly) predict complex data. He explains how he unexpectedly finds the struggle to be the most productive part of discovery and how that informs his approach to teaching.
Find us on Caltech Letters, SoundCloud, Apple Podcasts, and Spotify. You can contact us by emailing [email protected]. Music for this episode was provided by Blue Dot Sessions, and our artwork is by Usha Lingappa.