Research output per year
Research output per year
Personal profile
Biography
I am a Senior Lecturer at the Optimisation research group of the Faculty of Information Technology of Monash University.
Currently, my research is mainly focused on the development and improvement of highly efficient SAT- and SMT-based (satisfiability modulo theories) decision and optimization procedures targeting a variety of important practical applications in AI: from software package upgradability and Boolean formula minimization to model-based diagnosis (MBD), software fault localization and eXplainable AI (XAI).
Education/Academic qualification
Computer Science, Doctor of Philosophy, Irkutsk State University (ISU)
Award Date: 19 Nov 2010
Applied Mathematics, Diploma (Honours Degree), Irkutsk State University (ISU)
Award Date: 15 Jun 2006
Research area keywords
- Satisfiability
- Computational Logic
- Knowledge Representation and Reasoning
- Automated Reasoning
- Artificial Intelligence
- Combinatorial Optimisation
Network
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
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Constraint-driven explanations for black box ML models
Shrotri, A. A., Narodytska, N., Ignatiev, A., Meel, K. S., Marques-Silva, J. & Vardi, M. Y., 2022, 36th AAAI Conference on Artificial Intelligence (AAAI-22). Honavar, V. & Spaan, M. (eds.). Palo Alto CA USA: Association for the Advancement of Artificial Intelligence (AAAI), p. 8304-8314 11 p. (Proceedings of the 36th AAAI Conference on Artificial Intelligence, AAAI 2022; vol. 36).Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
Open AccessFile3 Citations (Scopus) -
Delivering trustworthy AI through formal XAI
Marques-Silva, J. & Ignatiev, A., 2022, 36th AAAI Conference on Artificial Intelligence (AAAI-22). Honavar, V. & Spaan, M. (eds.). Palo Alto CA USA: Association for the Advancement of Artificial Intelligence (AAAI), p. 12342-12350 9 p. (Proceedings of the 36th AAAI Conference on Artificial Intelligence, AAAI 2022; vol. 36).Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
Open AccessFile6 Citations (Scopus) -
On tackling explanation redundancy in decision trees
Izza, Y., Ignatiev, A. & Marques-Silva, J., 29 Sep 2022, In: Journal of Artificial Intelligence Research. 75, p. 261-321 61 p.Research output: Contribution to journal › Article › Research › peer-review
1 Citation (Scopus) -
Tractable explanations for d-DNNF classifiers
Huang, X., Izza, Y., Ignatiev, A., Cooper, M., Asher, N. & Marques-Silva, J., 2022, 36th AAAI Conference on Artificial Intelligence (AAAI-22). Honavar, V. & Spaan, M. (eds.). Palo Alto CA USA: Association for the Advancement of Artificial Intelligence (AAAI), p. 5719-5728 10 p. (Proceedings of the 36th AAAI Conference on Artificial Intelligence, AAAI 2022; vol. 36).Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
Open AccessFile8 Citations (Scopus) -
Using MaxSAT for efficient explanations of tree ensembles
Ignatiev, A., Izza, Y., Stuckey, P. J. & Marques-Silva, J., 2022, 36th AAAI Conference on Artificial Intelligence (AAAI-22). Honavar, V. & Spaan, M. (eds.). Palo Alto CA USA: Association for the Advancement of Artificial Intelligence (AAAI), p. 3776-3785 10 p. (Proceedings of the 36th AAAI Conference on Artificial Intelligence, AAAI 2022; vol. 36).Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
Open AccessFile5 Citations (Scopus)