Bayesian Multiobjective Optimisation With Mixed Analytical and Black-Box Functions: Application to Tissue Engineering
- Submitting institution
-
Imperial College of Science, Technology and Medicine
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 2158
- Type
- D - Journal article
- DOI
-
10.1109/TBME.2018.2855404
- Title of journal
- IEEE Transactions on Biomedical Engineering
- Article number
- 3
- First page
- 727
- Volume
- 66
- Issue
- 3
- ISSN
- 0018-9294
- Open access status
- Compliant
- Month of publication
- July
- Year of publication
- 2018
- URL
-
-
- Supplementary information
-
10.1109/TBME.2018.2855404
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
5
- Research group(s)
-
-
- Citation count
- 8
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This optimisation method is used by our tissue engineering collaborators at the Universite de Liege (group of Professor Geris), which led to a paper in Biotechnology & Bioengineering (https://onlinelibrary.wiley.com/doi/abs/10.1002/bit.26500) that addresses the biological implications of the algorithm developed in this work. The work also resulted in a keynote speech at the Royal Academy of Engineering, the Mellichamp Distinguished Lecture at Georgia Tech, and a plenary presentation at ESCAPE 2020 in Milan (https://www.aidic.it/escape30/index.html). Through this work, PhD student Simon Olofsson received an internship at Facebook.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
