Sharad Ramanathan

The paper develops a platform for high-throughput CRISPRi screening in hPSC-derived organoids to identify genetic drivers of human anterior neural tube closure, finding ZIC2, SOX11, and ZNF521 as key regulators.

This paper demonstrates that neural networks can exhibit reward-seeking behavior through local predictive updates and internal noise, enabling autonomous and adaptable interaction with environments.

The paper identifies modular neural circuits in C. elegans that drive learned pathogen avoidance using compressed sensing and optogenetic methods.

This study uses machine learning to optimize organoid morphogenesis, revealing an excitable system driven by WNT and FGF signaling that governs human axial elongation.

This paper demonstrates a hybrid system combining optogenetics and deep reinforcement learning to enhance nematode navigation and food search performance.

The paper constructs a single-cell atlas of the frontal cortex in early-onset monogenic Alzheimer's disease to identify cellular and molecular changes in disease mechanisms.

This study shows that mesendoderm competence in differentiating human pluripotent stem cells can be modulated by genetic perturbations and tracked using a low-dimensional reaction coordinate.

The paper shows that BMP receptor localization and embryo geometry create a robust signaling gradient in the mouse embryo.