Biochemical sensors play an important role in protecting humans with applications ranging from routine health monitoring to detecting biothreats. The objective of this project is to create a materials innovation infrastructure that accelerates the discovery and optimization of biosensor materials through a closed-loop computational and experimental approach. This project builds on recent discoveries by the PIs at the Pennsylvania State University and the Rensselaer Polytechnic Institute to develop theory- informed intelligent models that guide the engineering of two-dimensional (2D) materials (specifically transition metal dichalcogenides, TMDs) as core biosensing films. Owing to high surface-to-volume ratio and tunable electronic properties, 2D materials have found unique electrochemical applications. However, sensing applications mainly rely on trial and error when making material choices. This project proposes to address this gap using a feedback loop of computational modeling, artificial intelligence (AI) modeling, scalable TMD synthesis methods, and sensor fabrication and testing. The proposed research is integrated with outreach and educational activities that target a broad range of age groups, with active participation from underrepresented minorities (URM). Networking with industry advisory board (IAB) members will provide students with internship and employment opportunities, strengthening the future interdisciplinary R&D workforce.