Bayesian Multiobjective Optimisation With Mixed Analytical and Black-Box Functions: Application to Tissue Engineering
- Submitting institution
-
University College London
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 14715
- Type
- D - Journal article
- DOI
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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
-
-
- 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
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5
- Research group(s)
-
-
- Citation count
- 8
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper develops an optimization method that is now used by our tissue engineering collaborators at the University of Liege (Prof Liesbet Geris). This collaboration with Professor Geris also led to a follow-up publication in Biotechnology & Bioengineering (https://onlinelibrary.wiley.com/doi/abs/10.1002/bit.26500) that addresses the biological implications of the algorithm developed in this paper. This work led to: a keynote speech at the Royal Academy of Engineering, the Mellichamp Distinguished Lecture at Georgia Tech, and plenary presentation at ESCAPE 2020 in Milan (https://www.aidic.it/escape30/index.html). This paper opened the door to my co-supervised PhD student Simon Olofsson’s employment at Facebeook.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -