Dr Nguyen Dang

Dr Nguyen Dang

Lecturer

Researcher profile

Phone
+44 (0)1334 46 3690
Email
nttd@st-andrews.ac.uk

 

Research areas

Personal homepage: https://ndangtt.github.io/

Broadly speaking, my research interests lie in the intersection between machine learning and optimisation. I am particularly interested in automated algorithm configuration/design, where the aim is to leverage machine learning to automate the development of optimisation algorithms. One of my current research focuses is deep reinforcement learning for Dynamic Algorithm Configuration.

I am also interested and have been working intensively on constraint modelling and solving, where I focus on integrating machine learning and automated algorithm configuration techniques into constraint programming.

PhD supervision

  • Duong Phuc Tai Nguyen
  • Tianchen Wu

Selected publications

  • Open access

    Athanor: Local search over abstract constraint specifications

    Attieh, S., Dang, N., Jefferson, C., Miguel, I. J. & Nightingale, P., Mar 2025, In: Artificial Intelligence. 340, 39 p., 104277.

    Research output: Contribution to journal › Article › peer-review

  • Open access

    Constraint models for Klondike

    Dang, N., Gent, I. P., Nightingale, P., Ulrich-Oltean, F. & Waller, J., 8 Aug 2025, 31st international conference on principles and practice of constraint programming, CP 2025. de la Banda, M. G. (ed.). Saarbrücken/Wadern: Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing, p. 1-20 20 p. 9. (Leibniz international proceedings in informatics (LIPIcs); vol. 340).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Open access

    Multi-parameter control for the (1+(λ,λ))-GA on OneMax via deep reinforcement learning

    Nguyen, T., Le, P., Doerr, C. & Dang, N., Aug 2025, Proceedings of the 18th ACM/SIGEVO Conference on Foundations of Genetic Algorithms. ACM

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • On the importance of reward design in reinforcement learning-based dynamic algorithm configuration: a case study on OneMax with (1+(λ,λ))-GA

    Nguyen, T., Le, P., Biedenkapp, A., Doerr, C. & Dang, N., Jul 2025, Proceedings of the genetic and evolutionary computation conference 2025 (GECCO '25). New York: ACM, p. 1162 - 1171

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Open access

    Transformer-based feature learning for algorithm selection in combinatorial optimisation

    Pellegrino, A., Akgün, Ö., Dang, N., Kiziltan, Z. & Miguel, I., 8 Aug 2025, 31st international conference on principles and practice of constraint programming, CP 2025. de la Banda, M. G. (ed.). Saarbrücken/Wadern: Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing, p. 1-22 22 p. 31. (Leibniz international proceedings in informatics, LIPIcs; vol. 340).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Open access

    Automatic feature learning for Essence: a case study on car sequencing

    Pellegrino, A., Akgün, Ö., Dang, N., Kiziltan, Z. & Miguel, I., 23 Sept 2024, ModRef 2024 - The 23rd workshop on Constraint Modelling and Reformulation (ModRef). 17 p.

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Open access

    Cost-efficient training for automated algorithm selection

    Kus, E., Akgun, O., Dang, N. & Miguel, I. J., 9 Sept 2024, p. 1-17. 17 p.

    Research output: Contribution to conference › Paper › peer-review

  • Open access

    Frugal algorithm selection

    Kus, E., Akgun, O., Dang, N. & Miguel, I., 29 Aug 2024, 30th International Conference on Principles and Practice of Constraint Programming. Shaw, P. (ed.). Saarbrücken, Germany: Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing, 16 p. 38. (Leibniz International Proceedings in Informatics (LIPIcs); vol. 307).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Open access

    Automated streamliner portfolios for constraint satisfaction problems

    Spracklen, J. L. P. J., Dang, N., Akgun, O. & Miguel, I. J., 1 Jun 2023, In: Artificial Intelligence. 319, 24 p., 103915.

    Research output: Contribution to journal › Article › peer-review

  • Using automated algorithm configuration for parameter control

    Chen, D., Buzdalov, M., Doerr, C. & Dang, N., 30 Aug 2023, FOGA'23: proceedings of the 17th ACM/SIGEVO conference on Foundations of Genetic Algorithms. Chicano, F., Friedrich, T., Kötzing, T. & Rothlauf, F. (eds.). New York, NY: ACM, p. 38-49 12 p.

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

 

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