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Summer School Participant
About the placement/internship

Why did you decide to do a placement/internship?

Within my PhD work on constrained stochastic multi objective optimisation the summer school introduced a good opportunity for me to learn and apply new knowledge on my own and other real world optimisation problems. I am aiming to determine more efficient ways to performing the optimization for highly expensive problems. While I have researched surrogate modelling before there is a large variety of work present within the field. This summer school that focuses on the synergy between parallel optimization and surrogate based methodologies seemed like a good opportunity to consider new methods that are related with my research.

How did you find your placement/internship?

Department email

Application process

I had to fill a form with details about my background and my research topic. Then I had the option of proposing a problem (can be real world optimization problem but not only) that could be use to work in group stage of the summer school.

Main responsibilities

By attending, I needed to ensure that I came to all sessions and fully participated with the group work.

Typical day

The summer school lasted 5 days, during the first 3 days all the sessions focused on presentations from leading researchers in the optimization field. They presented the state of the art methodologies in addition to their personal projects and future work. At the end of third day we have started to work in groups on real world applications. During the last 2 days we worked in groups of up to 7-8 on the proposed problems. At the end of the summer school we have presented a short presentation about how we went about tackling the problems and what might the optimal solutions for that particular problem.

What did I enjoy about my placement/internship?

I enjoyed getting to know other researchers within the field as well as the challenge of applying multi-objective optimization methods to real world applications. The presentations gave a clear understanding of the topics as well as some innovative applications.

Challenging aspects

The main challenges were during the group work. They mostly started from the lack of problem being described in an optimization language. Due to this it was necessary to first redefine the optimization problem before it was possible to go start applying optimization and get the optimal solution. The other challenge was the time allocated to solve the problem, real world applications take more than 2 days to be solve, within this time we only can indicate a possible path which can be followed in order to solve it.

Did you use any skills learned from your course?

The knowledge of different ways to approach multi objective problems has been very useful. While I have not yet had the chance to fully utilise the HPC (high performance computing) in order to incorporate parallelization.

Advice to students

My piece of advice to students

I would recommend going to a summer school, it can be beneficial to ensure first that you have a basic understanding of the field before hand as even though they are likely to go through the main topics it can be a lot of information to take in. It is important that you also try to be sociable with other researchers and ask about their research in order to expand you network and gain the most out of this experience.

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Form completed: 09 Oct 2018

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