Peter Neubauer
Papers
22
Total Citations
395
H-Index
10
About
Peter Neubauer is a pioneering researcher at the intersection of bioprocess engineering, automation, and digitalization, whose work has fundamentally advanced how microbial cultivation processes are developed and optimized. His research centers on high-throughput robotic cultivation platforms, optimal experimental design, and the application of advanced computational methods — including nonlinear state estimation and multivariate analysis — to accelerate biomanufacturing development. Neubauer's most influential contribution, his 2016 framework for online optimal experimental re-design in parallel fed-batch systems (104 citations), demonstrated how kinetic growth models could be precisely parameterized with minimal experimental effort, transforming bioprocess development efficiency. Building on this, his team developed integrated robotic mini-bioreactor platforms (59 citations) that combine automated parallel cultivation with sophisticated real-time data handling and process control. His 2019 and 2020 publications further established automated strain screening and adaptive feeding strategies as practical tools for early-stage process development. Through an editorial on digitalization in bioprocessing (2017), Neubauer has also shaped broader discourse in the field. Collectively, his contributions have established a rigorous, data-driven paradigm for modern bioprocess development, making him an essential reference for researchers working in industrial biotechnology and bioprocess automation.
Research Focus
Key Achievements
Top Papers
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- 4Adaptive optimal operation of a parallel robotic liquid handling station31 citations · 2018
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- 6Editorial: Bioprocess Development in the era of digitalization19 citations · 2017
- 7Monitoring Parallel Robotic Cultivations with Online Multivariate Analysis18 citations · 2020
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