Headshot portrait of Stephan Eismann - Bio-X Bowes Fellow
Bio-X Graduate Student Fellow

Awarded in 2019
Home Department: Applied Physics
Faculty Advisors: Ron Dror (Computer Science) and Rhiju Das (Biochemistry)

Research Title: RNA Structure Prediction and Design Using Deep Neural Networks

Research Description: Fueled by algorithmic improvements, advances in parallel hardware, and the availability of large training datasets, artificial neural networks have revolutionized the field of image classification. In contrast, machine learning in structural biology has been hindered by the problem of how to better represent molecular structures for machine learning algorithms. Stephan will be developing a deep learning framework to approach RNA structure prediction and design in an entirely new form. Stephan’s goal is to have the ability to predict the nucleotide sequence for a desired structure and to open the door for designing a new array of sensor RNAs that target molecules ranging from neurotransmitters to immune system messengers.


Stephan is leading the machine learning team at Atomic AI, Inc. located in South San Francisco.