
Lecturer
- About
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Biography
I joined Aberdeen in 2021. Prior to that, I was a member of the MLearn group at University of Lincoln, a programme lead of MSc Data Science and Applications, and carried out research in machine learning and big data analytics for optimal greenhouse climate control (energy, CO2 emssion and crop yield). I worked in the Interdisciplinary Computing and Complex BioSystems (ICOS) group, at Newcastle Univeristy, as a postdoc researcher on the giant Portabolomics project (£7.5m) from 2017 to 2019. My research interests include AI, machine learning, data science, decision making and optimisation. I have been actively in developing computational teachniques for interdisciplinary applications, e.g., systems metabolic engineering, biotechnology, greenhouse, etc. This includes Computational modelling of B. subtilis metabolism (BBSRC Mitigation Fund), Supply Chain Emissions Modelling and Optimisation (Scottish Food and Drink Net Zero Challenge Fund), MOCTE: An Investigation of Multi-Objective Optimisation in Constrained Time-varying Environments (Royal Society International Exchange), Agricultural Crop Carbon Fixation (Scottish Research Council via Interface), Pre-assembled natural stone cladding system with mechanical fixings (Innovate UK).
Resarch interests:
- Data-driven decision making
- Artificial intelligence and machine learning
- Nature-inspired (multi-objective) optimisation (theory and applications in planning, scheduling, logistics, etc.)
- Computational modelling (biosystems, controlled environment agriculture, etc.)
- Systems approaches to metablic engineering design, strain development and biotechnology
I am accepting PhD applications, please feel free to reach out for discussions.
Model-guided design of microbial systems
A piece of work focuses on the design of microbial cells through appropriate changes in their metabolic networks to enhance their production performance in producing molecules of interest.
External Memberships
HEA Fellow
Member of EPSRC Peer Review College
Latest Publications
Handling Dynamic Multiobjective Optimization Environments via Layered Prediction and Subspace-Based Diversity Maintenance
IEEE Transactions on Cybernetics, vol. 53, no. 4, pp. 2572 - 2585Contributions to Journals: ArticlesA Mahalanobis Distance-based Approach for Dynamic Multi-objective Optimization with Stochastic Changes
IEEE Transactions on Evolutionary Computation, pp. 1Contributions to Journals: Abstracts- [ONLINE] DOI: https://doi.org/10.1109/TEVC.2023.3253850
- [ONLINE] View publication in Scopus
Biological survival optimization algorithm with its engineering and neural network applications
Soft Computing, vol. 27, pp. 6437–6463Contributions to Journals: Articles- [ONLINE] DOI: https://doi.org/10.1007/s00500-023-07851-4
- [ONLINE] View publication in Scopus
CaR: A Cutting and Repulsion-Based Evolutionary Framework for Mixed-Integer Programming Problems
IEEE Transactions on Cybernetics, vol. 52, no. 12, pp. 13129 - 13141Contributions to Journals: Articles- [ONLINE] DOI: https://doi.org/10.1109/TCYB.2021.3103778
- [ONLINE] View publication in Scopus
Evolutionary Dynamic Multi-Objective Optimisation: A survey
ACM Computing Surveys, vol. 55, no. 4, 76Contributions to Journals: Articles
Prizes and Awards
Recipient of 2021 IEEE CIS Outstanding PhD Dissertation Award
- Research
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Research Overview
Dr Jiang’s research interests include modelling, decision making and optimization in complex systems, AI, machine learning, data science, and their applications to biological, agricultural and energy systems. Dr Jiang has extensive experience of AI and data science and has been actively involved in a number of funded projects. He worked on a giant EPSRC project (>£7M) for which he developed innovative AI-driven approaches to optimize microbial biosynthetic routes for the production of a number of bio-based products in collaboration with the Centre for Process Innovation, Wilton. He then later worked on another EU-Interreg SmartGreen project (€3.5M) where he developed bio-physical models of crop growth and climate models in glasshouse farming and applied AI and Big Data Analytics approaches to predict crop yield and optimize the yield, reduce CO2 usage and lower energy costs. His current projects includes computational modelling of B. subtilis metabolism (BBSRC Mitigation Fund), Supply chain emissions reduction in collaboration with Grown Agritechs (Scottish Food and Drink Net Zero Challenge Fund), Agricultural Crop Carbon Fixation (Scottish Research Council via Interface), Pre-assembled natural stone cladding system with mechanical fixings (Innovate UK), and Fish drying prediction in solar tent drier (in collaboration with African partners)
Research Areas
Accepting PhDs
I am currently accepting PhDs in Computing Science, Biological and Environmental Sciences.
Please get in touch if you would like to discuss your research ideas further.
Research Specialisms
- Artificial Intelligence
- Bioengineering
- Machine Learning
- Mathematical Modelling
- Operational Research
Our research specialisms are based on the Higher Education Classification of Subjects (HECoS) which is HESA open data, published under the Creative Commons Attribution 4.0 International licence.
Current Research
- Data-driven decision making
- Artificial intelligence and machine learning
- Nature-inspired, evolutionary, reinforcement learning, (multi-objective) optimisation (planning, scheduling, logistics, etc.)
- Computational modelling (biosystems, controlled environment agriculture, etc.)
- Systems approaches to metablic engineering design, strain development and biotechnology
Supervision
My current supervision areas are: Computing Science, Biological and Environmental Sciences.
I am supervising UG final-year projects, MSc projects and PhD students in the area of AI and machine learning. Feel free to contact me to discuss your project ideas.
Funding and Grants
Computational modelling of B. subtilis metabolism (BBSRC Mitigation Fund)
Supply Chain Emissions Modelling and Optimisation (Scottish Food and Drink Net Zero Challenge Fund)
MOCTE: An Investigation of Multi-Objective Optimisation in Constrained Time-varying Environments (Royal Society International Exchange)
Pre-assembled natural stone cladding system with mechanical fixings (Innovate UK)
- Teaching
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Courses
- Artificial Intelligence
- Object Orientated Programming
- Advanced Programming
- Applied Artificial Intelligence
Teaching Responsibilities
CS3033 - Artificial Intelligence
- Publications
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Page 1 of 5 Results 1 to 10 of 43
Handling Dynamic Multiobjective Optimization Environments via Layered Prediction and Subspace-Based Diversity Maintenance
IEEE Transactions on Cybernetics, vol. 53, no. 4, pp. 2572 - 2585Contributions to Journals: ArticlesA Mahalanobis Distance-based Approach for Dynamic Multi-objective Optimization with Stochastic Changes
IEEE Transactions on Evolutionary Computation, pp. 1Contributions to Journals: Abstracts- [ONLINE] DOI: https://doi.org/10.1109/TEVC.2023.3253850
- [ONLINE] View publication in Scopus
Biological survival optimization algorithm with its engineering and neural network applications
Soft Computing, vol. 27, pp. 6437–6463Contributions to Journals: Articles- [ONLINE] DOI: https://doi.org/10.1007/s00500-023-07851-4
- [ONLINE] View publication in Scopus
CaR: A Cutting and Repulsion-Based Evolutionary Framework for Mixed-Integer Programming Problems
IEEE Transactions on Cybernetics, vol. 52, no. 12, pp. 13129 - 13141Contributions to Journals: Articles- [ONLINE] DOI: https://doi.org/10.1109/TCYB.2021.3103778
- [ONLINE] View publication in Scopus
Evolutionary Dynamic Multi-Objective Optimisation: A survey
ACM Computing Surveys, vol. 55, no. 4, 76Contributions to Journals: ArticlesSolving dynamic multi-objective problems using polynomial fitting-based prediction algorithm
Information Sciences, vol. 610, pp. 868-886Contributions to Journals: Articles- [ONLINE] DOI: https://doi.org/10.1016/j.ins.2022.08.020
Enhanced Affinity Propagation Clustering on Heterogeneous Information Network
Contributions to Conferences: PapersOptDesign: Identifying Optimum Design Strategies in Strain Engineering for Biochemical Production
ACS Synthetic Biology, vol. 11, no. 4, pp. 1531–1541Contributions to Journals: ArticlesOptimizing the flight route of UAV using biology migration algorithm
Contributions to Journals: Conference ArticlesDynamic multi-objective optimization algorithm based decomposition and preference
Information Sciences, vol. 571, pp. 175-190Contributions to Journals: Articles- [ONLINE] DOI: https://doi.org/10.1016/j.ins.2021.04.055
- [ONLINE] View publication in Scopus