This page is my interactive CV.

Education

[2022 - 2024] Master of Science in Math and Computer Science @ SPbU Thesis: Efficient neural architectures for NP-hard problems and recommender systems [2018 - 2022] Bachelor of Science in Math and Computer Science @ SPbU Thesis: A strengthening of the concurrent normals theorem for polytopes

Work Experience

Machine Learning Researcher @ PDMI AI lab, led by S. Nikolenko

• [2023] Researching DL-based simulators for learning recommendation systems @ SBER x PDMI
• [2022] Research DL-based heuristics for SAT-solvers @ HUAWEI x PDMI

Math Optimization Specialist

• [2023] Logistic optimization via Mixed-Integer Linear Programming @ Zyfra

CNC Integrator

• [2019-2022] Modernization, repairment & developing CNC machines

Teaching

• [2023] Teaching assistant on Deep Learning @ MCS SPbU
• [2023 - ongoing] Teaching assistant on Machine Learning @ DS HSE. Awarded Best Teacher 2024
• [2018–2020]Grading regional competitions in Math, teaching and preparing school students for math competitions

Publications

• Neural Click Models for Recommender Systems M. Shirokikh, I. Shenbin, A. Alekseev, A. Volodkevich, A. Vasilev, S. I. Nikolenko, ACM SIGIR, 2024.
• User Response Modelling In Recommender Systems: A Survey M. Shirokikh, I. Shenbin, A. Alekseev, A. Volodkevich, A. Vasilev, S. I. Nikolenko, accepted by the Journal of Mathematical Sciences, Springer.
• Machine Learning for SAT: Restricted Heuristics and New Graph Representations Mikhail Shirokikh, Ilya Shenbin, Anton Alekseev, Sergey Nikolenko, arXiv preprint, 2023.
• Nabla-DFT: A Universal Quantum Chemistry Dataset of Drug-Like Molecules and a Benchmark for Neural Network Potentials - Kuzma Khrabrov, Anton Ber, Artem Tsypin, Konstantin Ushenin, Egor Rumiantsev, Alexander Telepov, Dmitry Protasov, Ilya Shenbin, Anton Alekseev, Mikhail Shirokikh, Sergey I. Nikolenko, Elena Tutubalina, Artur Kadurin, NeurIPS, 2024.