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Arabov Mulosharaf Kurbanovich

Department of Data Analysis and Software Technology, Kazan Federal University · Kazan Federal University

https://researchid.co/sharaf250489
@kpfu.ru
7Scopus Publications
87Google Scholar Citations
5Google Scholar h-index

Research Interests

Natural Language Processing (NLP), Large Language Models (LLMs), Parameter-Efficient Fine-Tuning (LoRA, QLoRA, PEFT), Time Series Forecasting, Computer Science, Machine Learning, Deep Learning

Biography

Highly motivated researcher and software engineer with a PhD in Physical and Mathematical Sciences and 10+ years of experience in academic research, teaching, and full-stack development. Senior Lecturer at Kazan Federal University teaching ML, NLP, and time series forecasting. Research focuses on differential equations, dynamical systems, and applied machine learning. Published in peer-reviewed journals and conferences. Supervised 25+ Master's projects in AI.

Education

PhD (Candidate of Sciences) in Physical and Mathematical Sciences, Institute of Mathematics, Academy of Sciences of Tajikistan (2012–2016). Specialist Degree in Computer Science & Software Engineering, Tajik National University (2007–2012).

Recent Scopus Publications

  1. Character-Level Transformer for Tajik-Persian Transliteration with a Parallel Lexical Corpus
    Eacl 2026 19th Conference of the European Chapter of the Association for Computational Linguistics Proceedings of the 2nd Workshop on Nlp for Languages Using Arabic Script Abjadnlp 2026, 2026
  2. Identification of the Original Author of a Social Media Post Based on Text Analysis, Time Dependencies, and the Structure of Reposts Using Combined Neural Networks
    Proceedings 2025 International Conference on Industrial Engineering Applications and Manufacturing Icieam 2025, 2025
  3. Comparative Analysis of Intelligent Methods for Automatic Anomaly Detection in Industrial and Distributed Systems Based on Machine Learning and Deep Learning Algorithms
    Rusautocon Proceedings of the International Russian Automation Conference, 2025
  4. Comparative Analysis of FCN and U-Net for Retinal Blood Vessels Segmentation: A Performance Evaluation
    Rusautocon Proceedings of the International Russian Automation Conference, 2024
  5. Comparative Analysis of Ensemble and Linear Machine Learning Models in the Task of House Price Prediction
    Rusautocon Proceedings of the International Russian Automation Conference, 2024

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