Resource-efficient Bayesian optimization for self-calibrating liquid handling

Enrui Lin, Yimu Zhao, Owen Melville, Ilya Yakavets

Submission Type: I want my submission to be considered for both oral and poster presentation.

Keywords: liquid handling, lab automation, Bayesian optimization, self-driving laboratory

TL;DR: This work presents a data-efficient, closed-loop Bayesian optimization framework that automatically calibrates liquid-handling robots, improving accuracy and repeatability across liquids and volumes while eliminating manual, non-scalable tuning.

Confirmation Of Submission Requirements: I submit an abstract. It uses the template provided on the submission page and is no longer than 2 pages.

Submission Number: 269