Evolutionary Multi-objective Learning and its Application to Metabolic Engineering Design

All members of the department are welcome: undergraduates, postgraduates, postdocs, teaching staff, technical staff - anyone who would like to attend and learn a little bit about what our speakers do in their research career. Members from other disciplines within the School, and the wider University community, are also welcome to attend.

All PhD students in Chemistry are expected to attend as part of their PhD training.

Evolutionary Multi-objective Learning and its Application to Metabolic Engineering Design
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This is a past event

Many real-world applications involve optimisation of multiple conflicting objectives simultaneously. Examples include maximizing comfort and minimizing cost while buying or rent a home, minimizing the cost and maximizing the durability of constructed structures, and minimizing the traveling cost and maximum cover of distance.  Such multi-objective optimisation problems require solutions that are capable of trading off objectives. In this talk, I will discuss evolutionary multi-objective learning, a popular approach for solving such problems and show how it can be adapted to various problem properties and dynamic scenarios. I will also talk about our recent work on using evolutionary multi-objective learning for the design of microbial systems for the production of biochemicals.

Speaker
Shouyang Jiang
Venue
Meston 2 and MS Teams
Contact

Contact Ehud Reiter for more information