Dr Dongda Zhang Cantab, DIC, AMIChemE, AMRSC

Lecturer in Process Systems Engineering and Machine Learning

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Publications

  1. 2021
  2. Published

    Using process data to generate an optimal control policy via apprenticeship and reinforcement learning

    Mowbray, M., Smith, R., Rio‐Chanona, E. A. D. & Zhang, D., 15 Sep 2021, In: AIChE Journal. 67, 9, e17306.

    Research output: Contribution to journalArticlepeer-review

  3. Published

    Synergising biomass growth kinetics and transport mechanisms to simulate light/dark cycle effects on photo‐production systems

    Cho, B. A., Servia, M. Á. D. C., Chanona, E. A. D. R., Smith, R. & Zhang, D., 6 Feb 2021, In: Biotechnology and Bioengineering.

    Research output: Contribution to journalArticlepeer-review

  4. 2020
  5. Published

    Combining model structure identification and hybrid modelling for photo‐production process predictive simulation and optimisation

    Zhang, D., Savage, T. R. & Cho, B. A., 30 Nov 2020, In: Biotechnology and Bioengineering.

    Research output: Contribution to journalArticlepeer-review

  6. E-pub ahead of print

    Combining model structure identification and hybrid modelling for photo‐production process predictive simulation and optimisation

    Zhang, D., Savage, T. R. & Cho, B. A., 23 Jul 2020, (E-pub ahead of print) In: Biotechnology and Bioengineering.

    Research output: Contribution to journalArticlepeer-review

  7. Published

    Superstructure Reaction Network Design for the Synthesis of Biobased Sustainable Nitrogen-Containing Polymers

    Savage, T. R. & Zhang, D., 11 Mar 2020, In: Industrial & Engineering Chemistry Research.

    Research output: Contribution to journalArticlepeer-review

  8. 2019
  9. Published

    Reinforcement learning for batch bioprocess optimization

    Zhang, D., 18 Nov 2019, In: COMPUTERS & CHEMICAL ENGINEERING. 133, 106649.

    Research output: Contribution to journalArticlepeer-review

  10. Published

    Comparison of physics‐based and data‐driven modelling techniques for dynamic optimisation of fed‐batch bioprocesses

    Rio‐Chanona, E. A. D., Ahmed, N. R., Wagner, J., Lu, Y., Zhang, D. & Jing, K., 8 Nov 2019, In: Biotechnology and Bioengineering.

    Research output: Contribution to journalArticlepeer-review

  11. Published

    Review of advanced physical and data‐driven models for dynamic bioprocess simulation: Case study of algae–bacteria consortium wastewater treatment

    Rio‐Chanona, E. A. D., Cong, X., Bradford, E., Zhang, D. & Jing, K., 14 Feb 2019, In: Biotechnology and Bioengineering. 116, 2, p. 342-353 12 p.

    Research output: Contribution to journalArticlepeer-review

  12. Published

    CFD and kinetic‐based modeling to optimize the sparger design of a large‐scale photobioreactor for scaling up of biofuel production

    Ali, H., Solsvik, J., Wagner, J. L., Zhang, D., Hellgardt, K. & Park, C. W., 2019, In: Biotechnology and Bioengineering.

    Research output: Contribution to journalArticlepeer-review

  13. Published

    Hybrid physics‐based and data‐driven modeling for bioprocess online simulation and optimization

    Zhang, D., Rio‐Chanona, E. A. D., Petsagkourakis, P. & Wagner, J., 2019, In: Biotechnology and Bioengineering.

    Research output: Contribution to journalArticlepeer-review

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