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Recurrent Neural Networks for Real-Time Bioprocess State Estimation

Ai Bioprocess Optimization

Neural Network Surrogate Models for Bioprocesses

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Ai Bioprocess Optimization › Neural Network Surrogate Models for Bioprocesses

Recurrent Neural Networks for Real-Time Bioprocess State Estimation

This investigation develops LSTM and GRU-based surrogates to estimate unmeasured bioprocess states, intracellular metabolites, viability, stress markers, from sparse online sensor data. The scientific contribution enables soft-sensing capabilities that support real-time monitoring and model predictive control in biomanufacturing.

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📚 Academic: Thesis & PPT assistance included🧪 Tech: Master the protocols hands-on📝 Research > 3 months: Publication co-authorship in a Scopus-indexed journal

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