How do cells compute without electronic hardware and software? Drawing on statistical physics and machine learning theory, I explore how cells' intrinsic molecular processes can be thought of as software, executing biological algorithms for pattern recognition, error correction, and even learning. Because biology's approach to information processing differs fundamentally from silicon-based computing, this may offer new strategies for reprogramming cells or designing analog computers.
I am currently a graduate student in the Chemistry PhD program at the University of Chicago, where I am advised by Arvind Murugan and Suri Vaikuntanathan. Before graduate school, I earned my B.S. in Engineering Science and Chemistry from Emory University, where I was an undergraduate research assistant with Brian Dyer.
Contact:
Email - ktrifonova@uchicago.edu
