telegram: https://t.me/pozdnyakov_vitaliy
email: pozdnyakov.vitaliy@yandex.ru
scholar: https://scholar.google.com/citations?user=PfOZ7HgAAAAJ

Experience

2021 – now, AIRI (Moscow, research), Junior research scientist
Research and development of industrial artificial intelligence methods

2020 – now, HSE (Moscow, education), Instructor
Conducting lectures and practical classes on Network Science, Introduction to Neural Networks and Machine Translation

2022 – 2023, ISP RAS (Moscow, research), Junior research scientist
Research and development of industrial artificial intelligence methods

LAMBDA at HSE (Moscow, research)
2022 – 2023, Junior research scientist
2020 - 2022, Research intern
Research and development of industrial artificial intelligence methods

2020 – 2022, MADE (Moscow, education), Instructor
Conducting practical classes on Machine Learning on Graphs

2016 – 2019, 1С (Moscow, software), Backend developer
Design and development of the 1C:ERP system

2014 – 2016, Wikimart (Moscow, e-commerce), Backend developer
Design and development of ERP systems

2012 – 2014, Partner LLC (Lipetsk, consulting), Programmer
Customer support, helpdesk

Education

2019 – 2021, Moscow, Higher School of Economics
Data Science, Master’s degree

2007 – 2012, Lipetsk State Pedagogical University
Information Systems and Technologies, Specialist’s degree

Publications

D. Fomin, I. Makarov, M. Voronina, A. Strimovskaya and V. Pozdnyakov, “Heterogeneous Graph Attention Networks for Scheduling in Cloud Manufacturing and Logistics,” in IEEE Access, doi: 10.1109/ACCESS.2024.3522020.

Kazadaev, Maksim, Vitaliy Pozdnyakov, and Ilya Makarov. “Time Series Generation with GANs for Momentum Effect Simulation on Moscow Stock Exchange.” 2024 IEEE Symposium on Computational Intelligence for Financial Engineering and Economics (CIFEr). IEEE, 2024.

Pozdnyakov, Vitaliy, et al. “Adversarial Attacks and Defenses in Fault Detection and Diagnosis: A Comprehensive Benchmark on the Tennessee Eastman Process.” IEEE Open Journal of the Industrial Electronics Society (2024).

Golyadkin, Maksim, et al. “SensorSCAN: Self-supervised learning and deep clustering for fault diagnosis in chemical processes.” Artificial Intelligence 324 (2023): 104012.

Kovalenko, Aleksandr, Vitaliy Pozdnyakov, and Ilya Makarov. “Graph neural networks with trainable adjacency matrices for fault diagnosis on multivariate sensor data.” IEEE Access (2024).

Pozdnyakov, Vitaliy, et al. ‘AADMIP: Adversarial Attacks and Defenses Modeling in Industrial Processes’. Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, IJCAI-24.

Public talks

2024, Time Series Generation with GANs for Momentum Effect Simulation on Moscow Stock Exchange, Symposium on Computational Intelligence for Financial Engineering and Economics, Hoboken, USA

2024, AADMIP: Adversarial Attacks and Defenses Modeling in Industrial Processes, International Joint Conference on Artificial Intelligence, Jeju, South Korea

2024, Digital twins and adversarial attacks on industrial monitoring systems, Yandex Studcamp on Maths in AI 2024, Innopolis

2023, A tutorial on model validation using deep generation of stress data, Data Science Conference 2023, Belgrade, Serbia

2023, A tutorial on model validation using deep generation of stress data, ACM conference on Economics and Computation 2023, Online

2023, Model validation using deep generation of stress data, AI Journey 2023, Online

2023, Introduction to ML on graphs, AIRI Summer School, Innopolis

2022, Self-supervised learning for fault diagnosis in industrial processes on sensor data, “Science of the future” forum, Novosibirsk

2022, Graph methods in social models: from viral marketing to epidemics, “I love economics” summer school, Moscow

2022, AI for industrial internet of things, “Future expo” festival, Online

2021, Community detection in social networks, “ODS: ML in marketing” meetup, Online

Hard Skills

Graph Neural Networks, Deep Generative Models, Time Series Forecasting, Python (numpy, pandas, scikit-learn, pytorch, networkx, DGL), SQL, Git