Rodrigo Castro
About Rodrigo Castro
Rodrigo Castro is an Affiliated Postdoctoral Scholar who has worked at The Jackson Laboratory and the Broad Institute of MIT and Harvard since 2020. He holds a PhD from Georgia State University and specializes in developing generative algorithms and neural-network models for synthetic cis-regulatory elements.
Work at Broad
Rodrigo Castro has been serving as an Affiliated Postdoctoral Scholar at the Broad Institute of MIT and Harvard since 2020. In this role, he engages in advanced research focused on synthetic biology and computational biology. His work involves the implementation of generative algorithms to design synthetic cis-regulatory elements, which are crucial for understanding gene regulation. Castro's position at Broad Institute allows him to collaborate with leading scientists and contribute to innovative projects in the field.
Current Position at The Jackson Laboratory
Since 2020, Rodrigo Castro has also held the position of Postdoctoral Associate at The Jackson Laboratory in Maine, United States. In this capacity, he focuses on developing neural-network models that predict the functional activity of cis-regulatory elements. His research contributes to the understanding of genetic regulation and has implications for various applications in genetics and genomics.
Education and Expertise
Rodrigo Castro earned his Doctor of Philosophy (PhD) from Georgia State University, where he studied from 2014 to 2020. Prior to this, he completed a Master of Science (MS) at Universidad de Guadalajara from 2006 to 2008 and obtained a Bachelor of Science (BS) from the same institution from 2000 to 2004. His educational background provides a strong foundation in biological sciences, computational methods, and synthetic biology.
Research Contributions
Rodrigo Castro's research includes the adaptation of attribution methods for discrete-space inputs, which aids in interpreting features and motifs of DNA sequences. His work on generative algorithms and neural-network models highlights his expertise in computational approaches to biological problems. These contributions are significant for advancing the understanding of gene regulation and synthetic biology.