Professor: Ivan Oseledets
Basic and Applied research in the field of Natural Language Processing. Developing new and applying modern NLP-methods to solve research tasks at CREI. Extending the project team of young and experienced researchers in the field of Natural Language Processing, Natural Language Understanding and Information Retrieval systems.
Latest scientific papers (last three years, in English):
Peoples’ Friendship University of Russia: Master of Applied Mathematics and Computer Science Moscow, 2007 – 2009 – Faculty of Sciences, Computer Science Department.
Peoples’ Friendship University of Russia: Bachelor of Applied Mathematics and Computer Science Moscow, 2002 – 2007 – Faculty of Sciences, Computer Science Department
PhD (“Candidate of Science”) in Computer Science (2014). PhD thesis: “Relational-situational data structures, methods and algorithms for search and analytical engines”, assigned by Dorodnicyn Computing Center of the Russian Academy of Sciences. Supervisor: prof. Gennady S. Osipov, Institute for Systems Analysis of the Russian Academy of Sciences.
Methods and applications of natural language processing, information retrieval, dynamic web-content filtering, machine learning, search engines, big data, and scientometrics.
The Semantic Plagiarism Detection System: http://like.exactus.ru.
System for scientific research activity support (museum exhibit from the dinosaur era): http://expert.exactus.ru.
Search and analysis engine for the patent information: http://patent.exactus.ru.
Meta-search engine Exactus (museum exhibit from the dinosaur era): http://exactus.ru
The software tools for the intelligent retrieval and analysis of huge text datasets – TextAppliance: http://textapp.ru/ (applied at Directorate of STP, RFBR, LLC INFRA-M, LLC RUKONT).
The projects lead of three research grants of the Russian Foundation for Basic Research (RFBR):
No. 14-07-31149, mall_a, 2014-2015 g. “Development and research of data structures and algorithms for search and analysis of textual information”;
Personal Grant No. 16-37-60048, Mol_a_Dk, 2016-2018. “Development and research of methods for semantic plagiarism retrieval based on deep semantic text analysis”;
No. 15-29-06031, 2015-2017. “Methods for detecting and extracting information about events related to the Arctic in information streams from various sources”.
The research team member for more than 20 projects of the Ministry of Education and Science of the Russian Federation, RFBR, RSF, RAS.
Achievements and awards