Andreas Sommer

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About

Andreas Sommer is a leading researcher in process systems engineering, with a focus on the optimal operation and automation of robotic experimental platforms. His work bridges the gap between advanced numerical optimization and practical laboratory automation, particularly for high-throughput bioprocess development. Sommer’s major contribution lies in developing adaptive, iterative strategies for the optimal control of parallel robotic liquid handling stations. His highly cited 2018 paper, "Adaptive optimal operation of a parallel robotic liquid handling station" (31 citations), demonstrates a novel framework for robustly calibrating kinetic fermentation models by iteratively refining experimental conditions to compensate for parameter uncertainties. This work has been pivotal in enabling more reliable, data-efficient bioprocess characterization. By integrating real-time optimization with automated experimentation, Sommer’s research significantly reduces the time and resources needed for model-based bioprocess design. His achievements are notable for advancing the concept of "self-driving labs" in biotechnology, where autonomous systems can intelligently plan and execute complex experimental workflows, making him a key figure in the digital transformation of bioprocess engineering.