As a potentially disruptive technology, neuromorphic computing breaks away from the conventional von Neumann paradigm by developing biologically-inspired devices as the basis of machines with artificial intelligence capabilities. Organic electronic materials have recently emerged as attractive alternatives to inorganic counterparts in neuromorphic computing owing to their low-energy switching, excellent tunability, low fabrication costs, and biocompatibility. In this project, we will establish a collaborative, multidisciplinary and data-centric research program to accelerate the discovery of novel conjugated polyelectrolytes (CPEs) with chemical structures tailored for the demands of neuromorphic engineering. It is worth noting that the high level of structure and property complexity in CPEs is a result of their electronically delocalized backbone structure and ionic functionalities with pronounced electrostatic effects. To address the challenge, our effort integrates high-throughput computation, machine learning, multiscale modeling, materials synthesis, and device characterization in a “closed loop” fashion. Inspired by the “Materials Genome Initiative (MGI)”, “Brain Initiative” and “A Nanotechnology- Inspired Grand Challenge for Future Computing” Initiative, the project strives to influence materials design strategies across a multitude of research fields.