Viet Anh Do

Higher Degree by Research Candidate

School of Computer and Mathematical Sciences

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
2023	Do, A. V., Guo, M., Neumann, A., & Neumann, F. (2023). Diverse Approximations for Monotone Submodular Maximization Problems with a Matroid Constraint. IJCAI International Joint Conference on Artificial Intelligence, 2023-August, 5558-5566.
-	Do, A. V., Neumann, A., Neumann, F., & Sutton, A. M. (n.d.). Rigorous Runtime Analysis of MOEA/D for Solving Multi-Objective Minimum Weight Base Problems.

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 J. E. Fieldsend, & M. Wagner (Eds.), Proceedings of the Genetic and Evolutionary Computation Conference (GECCO'22) (pp. 684-693). Online: Association for Computing Machinery. DOI Scopus1
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 Scopus2

Year

Citation

2022

Do, A. V., Guo, M., Neumann, A., & Neumann, F. (2022). Niching-based evolutionary diversity optimization for the traveling salesperson problem. In J. E. Fieldsend, & M. Wagner (Eds.), Proceedings of the Genetic and Evolutionary Computation Conference (GECCO'22) (pp. 684-693). Online: Association for Computing Machinery.
DOI Scopus1

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 Scopus2

Email: vietanh.do@adelaide.edu.au

Viet Anh Do

Language Competencies

Education

Research Interests

Journals

Conference Papers

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