Prof Ian Miguel

Head of School

Professor

Researcher profile

Phone

+44 (0)1334 46 3248

Email

ijm@st-andrews.ac.uk

Office

C0.13

Location

Jack Cole Building (Computer Science )

 

Biography

I am a Professor and Head of School of the School of Computer Science at St Andrews, which I joined in 2004.

I have worked in Artificial Intelligence for over 25 years, specialising in solving combinatorial optimisation problems through Constraint Programming and related technologies.

Teaching

I presently teach on:

• CS4402: Constraint Programming
• CS4303: Video Games

Research areas

I work in Artificial Intelligence, specifically in solving complex combinatorial optimisation problems, such as planning, scheduling, or routing with technologies such as Constraint Programming or Propositional Satisfiability (SAT).

Much of our work in St Andrews has focused on the important problem of modelling. A model in this sense is the description of the problem we wish to solve suitable for input to an automated solver - the quality of the model has a very significant impact on solving performance. We have developed a Constraint Modelling Pipeline to automate this modelling process, compiling a high-level description of a problem down to a variety of powerful solving technologies.

PhD supervision

• Erdem Kus
• Yigit Yazicilar
• Carla Davesa Sureda

Selected publications

• An Evaluation of Domain-Agnostic Representations to Enable Multi-task Learning in Combinatorial Optimisation

  Stone, C., Renau, Q., Miguel, I. & Hart, E., 3 Jan 2025, International Conference on Learning and Intelligent Optimization. Springer Nature, p. 399-414 16 p.

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

• 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

  TabID: automatic identification and tabulation of subproblems in constraint models

  Akgun, O., Gent, I. P., Jefferson, C. A., Kiziltan, Z., Miguel, I. J., Nightingale, P., Salamon, A. Z. & Ulrich-Oltean, F., 30 Mar 2025, In: Journal of Artificial Intelligence Research. 82, p. 1999-2056 58 p.

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

• Learning When to Use Automatic Tabulation in Constraint Model Reformulation

  Cena, C., Akgün, Ö., Kiziltan, Z., Miguel, I., Nightingale, P. & Ulrich-Oltean, F., 2023, Proceedings of the 32nd International Joint Conference on Artificial Intelligence, IJCAI 2023. Elkind, E. (ed.). International Joint Conferences on Artificial Intelligence, p. 1902-1910 9 p. (IJCAI International Joint Conference on Artificial Intelligence; vol. 2023-August).

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

• A Graph Transformation-Based Engine for the Automated Exploration of Constraint Models

  Stone, C., Salamon, A. Z. & Miguel, I., 2024, International Conference on Graph Transformation. Springer, Vol. 14774. p. 223 238 p. (LNCS).

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

• Open access

  Automated nogood-filtered fine-grained streamlining: a case study on covering arrays

  Yazicilar, O. Y., Akgun, O. & Miguel, I. J., 2 Sept 2024, ModRef 2024 - The 23rd workshop on Constraint Modelling and Reformulation (ModRef). 18 p.

  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

• Automating Reformulation of Essence Specifications via Graph Rewriting

  Miguel, I., Salamon, A. Z. & Stone, C., 2 Sept 2024, (arXiv preprint arXiv:2411.09576).

  Research output: Working paper › Preprint

• Open access

  Cost-Efficient Training for Automated Algorithm Selection

  Kus, E., Miguel, I. J., Akgun, O. & Dang, N., 12 Jul 2024, (Accepted/In press) Cost-Efficient Training for Automated Algorithm Selection. PMLR

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

• CONJURE: Automatic generation of constraint models from problem specifications (extended abstract)

  Akgün, Ö., Frisch, A. M., Gent, I. P., Jefferson, C., Miguel, I. & Nightingale, P., 19 Aug 2023, Proceedings of the 32nd International Joint Conference on Artificial Intelligence (IJCAI 2023). Elkind, E. (ed.). International Joint Conferences on Artificial Intelligence, p. 6833-6838 6 p. (IJCAI International Joint Conference on Artificial Intelligence; vol. 2023-August).

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

 

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