International Workshop on Automatic Software Optimisation

5th edition of GI @ GECCO 2018 in Kyoto, Japan

Organizers


Brad Alexander

Brad Alexander is a member of the Optimisation and Logistics Group at the University of Adelaide. His research interests include program optimisation, rewriting, genetic-programming (GP) - especially the discovery of recurrences and search-based-software-engineering. He is currently supervising projects in evolutionary art and in applications of search based software engineering to energy conservation and monitoring in mobile platforms. He has also supervised successful projects in the evolution of control algorithms for robots, the evolution of three-dimensional geological models, and the synthesis and optimisation of artificial water distribution networks, and using background optimisation to improve the performance of instruction set simulators (ISS)'s.
brad [at] cs.adelaide.edu.au


Saemundur O. Haraldsson

Saemundur O. Haraldsson is a research fellow at the University of Stirling. He has multiple publications on Genetic Improvement, including two that have received best paper awards; in last year's GI and ICTS4eHealth workshops. Additionally, he coauthored the first comprehensive survey on GI which was published in 2017. He has been invited to give talks on the subject in two Crest Open Workshops and for an industrial audience in Iceland. His PhD thesis (submitted in May 2017) details his work on the world's first live GI integration in an industrial application.
soh [at] cs.stir.ac.uk


Markus Wagner

Markus Wagner is a Senior Lecturer at the School of Computer Science, University of Adelaide, Australia. He has done his PhD studies at the Max Planck Institute for Informatics in Saarbruecken, Germany and at the University of Adelaide, Australia. For the outcomes of his studies, he has received the university's Doctoral Research Medal - the first for this school. His research topics range from mathematical runtime analysis of heuristic optimisation algorithms and theory-guided algorithm design to applications of heuristic methods to renewable energy production, professional team cycling and software engineering. So far, he has been a program committee member 30 times, and he has written over 70 articles with over 70 different co-authors. He has contributed to GECCO as Workshop Chair in 2016 and 2017. He has chaired several education-related committees within the IEEE CIS, was Co-Chair of ACALCI 2017 and General Chair of ACALCI 2018.
markus.wagner [at] adelaide.edu.au


John R. Woodward

John R. Woodward s a lecturer at Queen Mary University of London, and for the previous five years was a lecturer with the University of Stirling. He holds a BSc in Theoretical Physics, an MSc in Cognitive Science and a PhD in Computer Science, all from the University of Birmingham. His research interests include Automated Software Engineering, particularly Search Based Software Engineering, Artificial Intelligence/Machine Learning and in particular Genetic Programming. He has over 50 publications in Computer Science, Operations Research and Engineering which include both theoretical and empirical contributions, and given over 100 talks at International Conferences and as an invited speaker at Universities. He has worked in industrial, military, educational and academic settings, and been employed by EDS, CERN and RAF and three UK Universities.
j.woodward [at] qmul.ac.uk


Shin Yoo

Shin Yoo is an assistant professor at Korea Advanced Institute of Science and Technology, South Korea. He has extensively published on applications of metaheuristic search and evolutionary computation on software engineering, with a strong focus on testing and debugging. He received the Silver HUMIE at GECCO 2017 for his work on human competitive automated fault localisation using genetic programming. He has been the program co-chair of International Symposium on Search Based Software Engineering in 2014, and is the program co-chair of IEEE International Conference on Software Testing, Verification and Validation.
shin.yoo [at] kaist.ac.kr