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

• Carla Davesa Sureda
• Erdem Kus
• Tianchen Wu
• Yigit Yazicilar

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, Learning and intelligent optimization: 18th international conference, LION 18, Ischia Island, Italy, June 9–13, 2024, revised selected papers. Festa, P., Ferone, D., Pastore, T. & Pisacane, O. (eds.). Cham: Springer Nature, p. 399-414 16 p. (Lecture notes in computer science; vol. 14990).

  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

  Cross-paradigm modelling: a study of Puzznic

  Espasa, J., Gent, I. P., Miguel, I., Nightingale, P., Salamon, A. Z. & Villaret, M., 28 Jan 2025, Proceedings - 2024 IEEE 36th international conference on tools with artificial intelligence (ICTAI 2024). Piscataway, NJ: IEEE Computer Society, p. 89-95 7 p. 10849509. (Proceedings - International conference on tools with artificial intelligence (ICTAI)).

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

• 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

• 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

• A graph transformation-based engine for the automated exploration of constraint models

  Stone, C., Salamon, A. Z. & Miguel, I., 2 Jul 2024, (E-pub ahead of print) Graph transformation: 17th international conference, ICGT 2024, held as part of STAF 2024, Enschede, The Netherlands, July 10–11, 2024, proceedings. Harmer, R. & Kosiol, J. (eds.). Cham: Springer, p. 223-238 (Lecture notes in computer science; vol. 14774 ).

  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

• Open access

  Automating reformulation of Essence specifications via graph rewriting

  Miguel, I., Salamon, A. Z. & Stone, C., 2 Sept 2024, p. 1-9. 9 p.

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

• 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

 

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