He graduated with honors from MIPT in 2016. He defended his Ph.D. dissertation on methods of deep learning model selection in 2020, candidate of physical and mathematical sciences. He is an author of more than 29 scientific papers on model selection and natural language processing.

Professional interests: model selection, deep learning, neural networks, Bayesian inference, natural language processing.

Main publications

1. Yakovel K., Grebenkova O., Bakhteev O., Strijov V. Neural architecture search with structure complexity control (2021). Proceedings of the 10th International Conference on Analysis of Images, Social Networks and Texts.
2. Bakhteev, O. Y., & Strijov, V. V. (2020). Comprehensive analysis of gradient-based hyperparameter optimization algorithms. Annals of Operations Research, 289(1), 51-65.
3. Bakhteev, O. Y., & Strijov, V. V. (2018). Deep learning model selection of suboptimal complexity. Automation and remote control, 79(8), 1474-1488.

Full list of publications

Conferences and workshops

1. Bakhteev O., Ogaltsov A., Khazov A., Safin K., Kuznetsova R. CrossLang: The System of Cross-lingual Plagiarism Detection. NeurIPS, Workshop on Systems for ML. 2019.
2. Kuznetosva R., Bakhteev O. Variational Bi-domain Triplet Autoencoder. NeurIPS, Visually Grounded Interaction and Language workshop. 2018.
3. Bakhteev O., Khazov A. Author Masking using Sequence-to-Sequence Models. CLEF. 2017.

Full list of talks at conferences and workshops

Teaches: