Viet Anh Do

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
2024	Do, A. V., Guo, M., Neumann, A., & Neumann, F. (2024). Evolutionary Multi-objective Diversity Optimization. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 15151 LNCS, 117-134. DOI
2023	Neumann, F., Neumann, A., Qian, C., Do, A. V., Nobel, J. D., Vermetten, D., . . . Bäck, T. (2023). Benchmarking Algorithms for Submodular Optimization Problems Using IOHProfiler. CoRR, abs/2302.01464, 1-9. DOI
2022	Do, A. V., Guo, M., Neumann, A., & Neumann, F. (2022). Analysis of Evolutionary Diversity Optimization for Permutation Problems.. ACM Trans. Evol. Learn. Optim., 2, 11:1.
2022	Do, A. V., Guo, M., Neumann, A., & Neumann, F. (2022). Niching-based Evolutionary Diversity Optimization for the Traveling Salesperson Problem.. CoRR, abs/2201.10316.

Book Chapters

Year	Citation
2023	Yan, X., Do, A. V., Shi, F., Qin, X., & Neumann, F. (2023). Optimizing Chance-Constrained Submodular Problems with Variable Uncertainties. In H. Fujita, H. Perez-Meana, & A. Hernandez-Matamoros (Eds.), Frontiers in Artificial Intelligence and Applications (Vol. 372, pp. 2826-2833). IOS Press. DOI Scopus4

Conference Papers

Year	Citation
2024	Do, A. V., Guo, M., Neumann, A., & Neumann, F. (2024). Evolutionary Multi-objective Diversity Optimization.. In M. Affenzeller, S. M. Winkler, A. V. Kononova, H. Trautmann, T. Tusar, P. Machado, & T. Bäck (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)Volume 15151 LNCS Vol. 15151 (pp. 117-134). Hagenberg: Springer.
2023	Neumann, F., Neumann, A., Qian, C., Do, A., De Nobel, J., Vermetten, D., . . . Back, T. (2023). Benchmarking Algorithms for Submodular Optimization Problems Using IOHProfiler. In 2023 IEEE Congress on Evolutionary Computation, CEC 2023 Vol. abs/2302.01464 (pp. 1-9). Online: IEEE. DOI Scopus2
2023	Yan, X., Do, A. V., Shi, F., Qin, X., & Neumann, F. (2023). Optimizing Chance-Constrained Submodular Problems with Variable Uncertainties.. In K. Gal, A. Nowé, G. J. Nalepa, R. Fairstein, & R. Radulescu (Eds.), ECAI Vol. 372 (pp. 2826-2833). Online: IOS Press.
2023	Do, A. V., Neumann, A., Neumann, F., & Sutton, A. M. (2023). Rigorous Runtime Analysis of MOEA/D for Solving Multi-Objective Minimum Weight Base Problems. In A. Oh, T. Naumann, A. Globerson, K. Saenko, M. Hardt, & S. Levine (Eds.), Abstracts of the 37th Annual Conference on Neural Information Processing Systems (NeurIPS, 2023) as published in Advances in Neural Information Processing Systems Vol. 36 (pp. 15 pages). Online: Neural information processing systems foundation. Scopus7
2023	Do, A. V., Guo, M., Neumann, A., & Neumann, F. (2023). Diverse approximations for monotone submodular maximization problems with a matroid constraint. In E. Elkind (Ed.), Proceedings of the 32nd International Joint Conference on Artificial Intelligence (IJCAI 2023) Vol. 2023-August (pp. 5558-5566). Macao, S.A.R: IJCAI. DOI Scopus6
2022	Nikfarjam, A., Do, A. V., & Neumann, F. (2022). Analysis of Quality Diversity Algorithms for the Knapsack Problem.. In G. Rudolph, A. V. Kononova, H. E. Aguirre, P. Kerschke, G. Ochoa, & T. Tusar (Eds.), PPSN (2) Vol. 13399 (pp. 413-427). Springer.
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 Scopus3
2020	Do, A. V., Bossek, J., Neumann, A., & Neumann, F. (2020). Evolving diverse sets of tours for the Travelling Salesperson Problem. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO'20) (pp. 681-689). New York, NY, USA: Association for Computing Machinery. DOI Scopus27 WoS20
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 Scopus8

Preprint

Year	Citation
2024	Do, A. V., Guo, M., Neumann, A., & Neumann, F. (2024). Evolutionary Multi-Objective Diversity Optimization.
2023	Do, A. V., Neumann, A., Neumann, F., & Sutton, A. M. (2023). Rigorous Runtime Analysis of MOEA/D for Solving Multi-Objective Minimum Weight Base Problems..
2023	Do, A. V., Guo, M., Neumann, A., & Neumann, F. (2023). Diverse Approximations for Monotone Submodular Maximization Problems with a Matroid Constraint..

Email: vietanh.do@adelaide.edu.au

Viet Anh Do

Language Competencies

Education

Research Interests

Journals

Book Chapters

Conference Papers

Preprint

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