Viet Anh Do

Higher Degree by Research Candidate

School of Computer Science

Faculty of Sciences, Engineering and Technology

I obtained the Master of Computer Science degree from University of Adelaide in 2020, and am currently a PhD candidate. My research focuses on optimisation and evolutionary computation. I am mainly interested in fundamental concepts and questions, as well as runtime analysis of algorithms.

Career
Publications
Contact

Language Competencies

Language Competency

English Can read, write, speak, understand spoken and peer review

Vietnamese Can read, write, speak, understand spoken and peer review
Education

Date Institution name Country Title

2018 - 2020 University of Adelaide Australia Master of Computer Science
Research Interests

Analysis of Algorithms and Complexity Neural, Evolutionary and Fuzzy Computation Optimisation

Language	Competency
English	Can read, write, speak, understand spoken and peer review
Vietnamese	Can read, write, speak, understand spoken and peer review

Date	Institution name	Country	Title
2018 - 2020	University of Adelaide	Australia	Master of Computer Science

Journals

Year	Citation
2022	Do, A., Guo, M., Neumann, A., & Neumann, F. (2022). Analysis of Evolutionary Diversity Optimization for Permutation Problems. ACM Transactions on Evolutionary Learning and Optimization, 2(3), 1-27. DOI

Conference Papers

Year	Citation
2022	Do, A. V., Guo, M., Neumann, A., & Neumann, F. (2022). Niching-based evolutionary diversity optimization for the traveling salesperson problem. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO'22) (pp. 684-693). virtual online: Association for Computing Machinery. DOI
2020	Do, V., & Neumann, F. (2020). Maximizing submodular or monotone functions under partition matroid constraints by multi-objective evolutionary algorithms. In T. Bäck, M. Preuss, A. H. Deutz, H. Wang, C. Doerr, M. T. M. Emmerich, & H. Trautmann (Eds.), Proceedings of the 16th International Conference on Parallel Problem Solving from Nature (PPSN XVI), as published in Parallel Problem Solving from Nature – PPSN XVI, Part II Vol. 12270 (pp. 588-603). Switzerland: Springer Nature. DOI Scopus1

Year

Citation

2022

Do, A. V., Guo, M., Neumann, A., & Neumann, F. (2022). Niching-based evolutionary diversity optimization for the traveling salesperson problem. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO'22) (pp. 684-693). virtual online: Association for Computing Machinery.
DOI

2020

Do, V., & Neumann, F. (2020). Maximizing submodular or monotone functions under partition matroid constraints by multi-objective evolutionary algorithms. In T. Bäck, M. Preuss, A. H. Deutz, H. Wang, C. Doerr, M. T. M. Emmerich, & H. Trautmann (Eds.), Proceedings of the 16th International Conference on Parallel Problem Solving from Nature (PPSN XVI), as published in Parallel Problem Solving from Nature – PPSN XVI, Part II Vol. 12270 (pp. 588-603). Switzerland: Springer Nature.
DOI Scopus1

Email: vietanh.do@adelaide.edu.au

Viet Anh Do

Language Competencies

Education

Research Interests

Journals

Conference Papers

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