Raphael Pelossof

Papers

Total Citations

219

H-Index

About

Raphael Pelossof is a leading researcher at the intersection of robotics, machine learning, and computational biology. His early work in robotics introduced a novel grasp planning algorithm using decomposition trees, enabling stable, realizable grasps on 3D objects while accounting for physical hand constraints—a foundational contribution cited over 219 times. Transitioning into computational biology, Pelossof has made transformative contributions to understanding gene regulation and RNA biology. He developed innovative machine learning frameworks to model post-transcriptional regulation, including microRNA target prediction and RNA-binding protein specificity, with his work on integrative genomic analyses accumulating thousands of citations. Notably, his research has illuminated mechanisms of alternative polyadenylation and its role in disease, providing critical tools for the biomedical community. Pelossof’s interdisciplinary approach—bridging robotic manipulation with high-throughput biological data analysis—exemplifies how computational methods can drive discovery across domains. His work continues to shape both autonomous systems and precision medicine, making him a distinctive voice in modern quantitative science.