Dr Shouyong Jiang
Dr Shouyong Jiang

Dr Shouyong Jiang

Lecturer

Accepting PhDs

About

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.

External Memberships

HEA Fellow

Member of EPSRC Peer Review College

Latest Publications

View My Publications

Prizes and Awards

Recipient of 2021 IEEE CIS Outstanding PhD Dissertation Award

Research

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.

Computing Science

Supervising
Accepting PhDs

Biological and Environmental Sciences

Supervising
Accepting PhDs

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

Courses

  • Artificial Intelligence
  • Object Orientated Programming
  • Advanced Programming
  • Applied Artificial Intelligence

Teaching Responsibilities

CS3033 - Artificial Intelligence

Publications

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Chapters in Books, Reports and Conference Proceedings

Contributions to Conferences

Contributions to Journals

Working Papers