Open sourcing A better Penicillin Bioreactor Simulation

For industries like Life Sciences, it is challenging to collect a large amount of data with high quality that are needed for machine learning and autonomous control applications. Instead, we settle with simulations where initial research and experiments can be conducted. However, it is often difficult

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Optimizing DoE and Production Runs with Little Data

For many batch processes (e.g. in Life Sciences, Food & Beverage), Design of Experiments (DoE) is usually conducted before scaling up to production runs. We believe that Bayesian Optimization and its variants could significantly improve the performance of DoE and production runs, especially when there is little historical data available. And we are demonstrating exactly that

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A Taste of Bayesian Optimization – Part 2

In Part 1, we discussed simple Bayesian optimization (BO), and now we further exam BO by taking into account uncontrollable contextual information and constraints. 1 Contextual Optimization Like in Part 1, our goal is still to minimize an unknown function.

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