Many networks and platforms centered around online populations have flourished in the last few decades, riding on the rapid proliferation of web technologies. These, collectively known as human-centric networks, have various objectives like social interaction, commerce, content sharing, and advertising. Among them, online social networks have unleashed the potential of the web as a medium for information sharing and have had significant social and economic impact. Crowdsourcing systems, which are another emerging and popular kind of online platform, are giving a new perspective on the web as a huge work force of diversely-skilled people. Particularly, non-profit impact sourcing platforms which train and employ underprivileged people to do computationally intractable tasks like speech transcription and handwriting recognition are of high relevance to countries like India that are rich in human resources. I shall discuss mathematical problems motivated by practice, including on opinion dynamics in social networks, task allocation in crowdsourcing, and overloading of human workers. Reliable computation using unreliable units is a big challenge in crowdsourcing because people make errors; this is also a major challenge in emerging nanoscale circuits made of spin devices and carbon nanotubes, and also in cyber-physical systems, internet of things, and infrastructure networks. I shall discuss applications of information network-based theories in nanoscale circuits. I shall conclude my talk with some discussion on future research directions in social networks, crowdsourcing, and nanoscale circuits, as well as their connections.