Faculty Candidate Seminar

Presenter Christian Cuba-Samaniego, PhD

University of California Los Angeles

Talk Title: Adapting feedback control and pattern recognition paradigms for biotechnological applications

Engineering synthetic networks with desired behavior for robust adaptation or complex decision-making is challenging. Current approaches rely on different negative regulation techniques or logic-based operators, which suffer from suboptimal performance. To address this limitation, we introduce two design principles: (1) ultrasensitive input-output behavior and (2) tunable thresholds. Here, we engineer ultrasensitive-based networks to both achieve adaptive behavior through feedback control and build synthetic programs for molecular pattern recognition by implementing neural computing networks in living cells.