Mojmir Mutny

Machine learning scienstist currently a postdoct at Broad Institute of MIT and Harvard. In the past I was at ETH Zurich working in Learning and Adaptive Systems group. My current research focuses on active learning and efficient fine-tuning, aiming to identify the most informative data to improve machine learning models. I work on improving the reliability of LLMs in generation and exploring new enzymes. I have a background in Bayesian optimization, kernel methods, sensor selection, control, and optimization. My algorithms have been applied to machine calibration, laboratory automation, spatial analysis, and enzyme and antibody design.