Integrated Sensing And Communication (ISAC) has been identified as a pillar usage scenario for the impending 6G era. Bi-static sensing, a major type of sensing in ISAC, is promising to expedite ISAC in the near future, as it requires minimal changes to the existing network infrastructure. However, a critical challenge for bi-static sensing is clock asynchronism due to the use of different clocks at far-separated transmitters and receivers.

By “social learning,” in this article we refer to mechanisms for opinion formation and decision making over graphs and the study of how agents’ decisions evolve dynamically through interactions with neighbors and the environment. The study of social learning strategies is critical for at least two reasons.

We opened the year with the theme of “embracing interdisciplinarity,” emphasizing the fact that signal processing naturally builds bridges across different domains and disciplines. The front cover image of an organic bridge across mature trees giving birth to a sapling helped convey our message. After two special issues (two parts of one special issue), we come back to you with an issue comprised of feature articles and columns, which all reinforce the message in our first issue of 2024.

Deep learning, in general, focuses on training a neural network from large labeled datasets. Yet, in many cases, there is value in training a network just from the input at hand. This is particularly relevant in many signal and image processing problems where training data are scarce and diversity is large on the one hand, and on the other, there is a lot of structure in the data that can be exploited.

As I take on the President of the Signal Processing Society (SPS) role, I am excited to connect with you through this column. I look forward to introducing myself and inviting you, the members, to join our volunteers in shaping our shared future.