Dr Maxim Buzdalov
Lecturer in Computer Science
Department of Computer Science
Contact Details
- Email: mab168@aber.ac.uk
- ORCID: 0000-0002-7120-8824
- Phone: +44 (0) 1970 622420
- Research Portal Profile
Teaching
Module Coordinator
Lecturer
- CSM9060 - Dissertation
- CS39440 - Major Project
- CS10220 - Introduction to Computer Infrastructure
- CHM9360 - MSC Project
Tutor
Moderator
Coordinator
Research Groups
Publications
Antipov, D, Buzdalov, M & Doerr, B 2025, 'First Steps Toward a Runtime Analysis When Starting With a Good Solution', ACM Transactions on Evolutionary Learning and Optimization, vol. 5, no. 2, 14. 10.1145/3675783
Antipov, D, Buzdalov, M & Doerr, B 2025, Hot off the Press: First Steps Towards a Runtime Analysis When Starting With a Good Solution. in G Ochoa (ed.), GECCO '25 Companion: Proceedings of the Genetic and Evolutionary Computation Conference Companion. Proceedings of the Genetic and Evolutionary Computation Conference, Association for Computing Machinery, pp. 11-12, GECCO 2025, Málaga, Spain, 14 Jul 2025. 10.1145/3712255.3734241
Martynov, P, Buzdalov, M, Pankratov, S, Aksenov, V & Schmid, S 2025, In the Search of Optimal Tree Networks: Hardness and Heuristics. in G Ochoa (ed.), GECCO 2025 - Proceedings of the 2025 Genetic and Evolutionary Computation Conference. GECCO 2025 - Proceedings of the 2025 Genetic and Evolutionary Computation Conference, Association for Computing Machinery, pp. 249-257, 2025 Genetic and Evolutionary Computation Conference, GECCO 2025, Malaga, Spain, 14 Jul 2025. 10.1145/3712256.3726425
Walden, A & Buzdalov, M 2024, A Simple Statistical Test Against Origin-Biased Metaheuristics. in S Smith, J Correia & C Cintrano (eds), Applications of Evolutionary Computation - 27th European Conference, EvoApplications 2024, Held as Part of EvoStar 2024, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 14634 LNCS, Springer Nature, pp. 322-337, 27th European Conference on Applications of Evolutionary Computation, EvoApplications 2024, Aberystwyth, United Kingdom of Great Britain and Northern Ireland, 03 Apr 2024. 10.1007/978-3-031-56852-7_21
Antipov, D, Buzdalov, M & Doerr, B 2024, 'Lazy Parameter Tuning and Control: Choosing All Parameters Randomly from a Power-Law Distribution', Algorithmica, vol. 86, no. 2, pp. 442-484. 10.1007/s00453-023-01098-z
More publications on the Research Portal