Stack: Python & ML libs, Matlab
Industry: Information & measurement, Fintech, Computer science
Skills: ML, AI, Deep Learning, NN, Mathematic, Statistic, Data analysis, Data processing, Data preprocessing, Visualization, Algorithms
Dynamic Pricing for the Open Online Ticket System: A Surroga
11178025
Dynamic Pricing for the Open Online Ticket System: A Surroga
11178021
Forecasting railway ticket demand with search query open dat
11178017
Forecasting railway ticket demand with search query open dat
11178028
Dynamic Pricing for the Open Online Ticket System: A Surroga
11178025
Dynamic Pricing for the Open Online Ticket System: A Surroga
11178021
Forecasting railway ticket demand with search query open dat
11178017
Forecasting railway ticket demand with search query open dat
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Esperienza
Scientific Researcher
ITMO University
dic 2021 - dic 2022 (1 anno)
Stack: Python and Data Science libraries (Numpy, Pandas, SciPy, TensorFlow, SciKit-Learn, Seaborn et al.), LaTeX.
Industry: FinTech, Computer science
Skills: Machine Learning · Deep Learning · Python (Programming Language) · Data Analysis · Optimization Algorithms
Assistant of the Department of Information and Measuring Systems and Technologies (ETU "LETI")
Saint Petersburg State Electrotechnical University "LETI"
set 2015 - giu 2022 (6 anni, 9 mesi)
Scientific and educational activities. Scientific: development and research of multichannel information-measuring systems. Educational: Metrology, Computer technologies in instrument making, Theoretical foundations of information and measuring equipment, Adaptive information and measuring systems, Bachelor's scientific director.
Skills: Research Skills · Mentoring · University Teaching · Publications · Presentation Skills
Middle Software Developer
Saint Petersburg State Electrotechnical University "LETI"
mar 2021 - dic 2021 (9 mesi, 1 giorno)
Development of software for the automatic control system, collection, processing and analysis of measurement data.
Skills: Machine Learning · Python (Programming Language) · Statistical Data Analysis · Data Analysis · Error Analysis
Formazione
PhD (Russian PhD)
Sankt-Peterburgskij Gosudarstvennyj Elektrotehniceskij Universitet 'LETI', Russian Federation 2015 - 2021
(6 anni)
Researcher. Lecturer-Researcher.
Sankt-Peterburgskij Gosudarstvennyj Elektrotehniceskij Universitet 'LETI', Russian Federation 2015 - 2019
(4 anni)
Master
Sankt-Peterburgskij Gosudarstvennyj Elektrotehniceskij Universitet 'LETI', Russian Federation 2013 - 2015
(2 anni)
Certificati
ArcGIS: Tools, functionality, and execution of analysis
Saint Petersburg State Electrotechnical University "LETI"
2020
Data analysis in geographic information systems.
Frontiers of applied artificial intelligence: industrial, economics, education
ITMO University
2021
The school will be devoted to the development of promising AI technologies that form the methodological and algorithmic foundations of strong AI, which provides decision support in situations that exceed the cognitive abilities of an expert in complexity.
Pubblicazioni
Optimal Design of the Structure of an Adaptive Information-Measuring System
IEEE
The functioning of complex technical objects involves the use of information-measuring systems to obtain information about the environment and the state of devices within the system itself. At the same time, to prevent emergency and pre-emergency situations, it is important to receive timely information about the discrete state of the object, for example, information about the presence of sand in the flow of the produced hydrocarbons...
Dynamic Pricing for the Open Online Ticket System: A Surrogate Modeling Approach
Smart Cities
Dynamic pricing is frequently used in online marketplaces, ticket sales, and booking systems. The commercial principles of dynamic pricing systems are often kept secret; however, their application causes complex changes in human behavior. Thus, a scientific tool is needed to evaluate and predict the impact of dynamic pricing strategies. Publications in the field lack a common quality evaluation methodology, public data, and source code, making them difficult to reproduce.
Forecasting railway ticket demand with search query open data
Procedia Computer Science
This study proposes a solution to the problem of railway demand forecasting on open data of a passenger railway company and search engines. A time series of web search queries is used as a predictor, and demand time series for train tickets is used as a target variable. The predictor is taken with a lag corresponding to the best correlation with the demand series.
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