Congratulations to Dana Rubin of the Molecular Machines group, whose paper "RiboGen: RNA Sequence and Structure Co-Generation with Equivariant Multiflow" was awarded Best Paper as part of the AI for Nucleic Acids (AI4NA) workshop at this year's International Conference on Learning Representations (ICLR) in Singapore. Her research presents a groundbreaking approach to modeling RNA structures, offering a powerful new tool for understanding RNA's role in biology. RiboGen is the first ML model capable of jointly generating RNA sequences and their 3D all atom structures.

AI4NA brought together leading voices from machine learning and molecular biology to explore the next frontier in AI research: nucleic acids. The workshop focused on critical challenges such as predicting RNA tertiary structure, mapping nucleic acid interactions, and designing novel RNA/DNA molecules with therapeutic potential.

Rubin recently completed her master’s degree at MIT EECS and the Media Lab, where she focused on machine learning for structural biology. Rubin’s recognition at this intersection of disciplines highlights the accelerating role of AI in reshaping biological discovery.