Scientific Publications on Artificial Intelligence

Method/approach: A general conceptual approach is applied. The paper discusses AI applications in trend analysis, preparation of scientific texts, topic selection, abstract and hypothesis generation, translation, novelty and originality checking, and the management of limitations. Case studies and SWOT analysis are used.

Key results: AI is defined as a valuable tool for automating routine activities, supporting creative stages, and discovering relationships that may remain unnoticed in traditional approaches. The need for human control and ethical rules is emphasized.

Bibliographic description: Rashidov, A. Artificial intelligence in scientific research. Strategies for Policy in Science and Education, vol. 32 (5s), pp. 35–45, Az-buki, 2024. ISSN: 1310-0270. DOI: 10.53656/str2024-5s-3-ald.

Method/approach: A ten-stage algorithm is proposed, combining automated analysis by ChatGPT with the expert judgment of the reviewer. It includes criteria and weighting coefficients, quantitative and qualitative assessment, SWOT analysis, reviewer corrections, and a final decision.

Key results: The approach can accelerate preliminary assessment, increase the level of detail, and reduce the influence of some subjective factors. The paper emphasizes that the final decision remains with the reviewer.

Bibliographic description: Rashidov, A. An algorithm to support the scientific manuscript review process with the assistance of ChatGPT. Strategies for Policy in Science and Education, vol. 32 (6), pp. 669–681, Az-buki, 2024. DOI: 10.53656/str2024-6-1-alg.

Method/approach: A structured and iterative algorithm for topic selection through ChatGPT is developed. It combines criteria for relevance, alignment with expertise, practical applicability, collaboration potential, novelty, and SWOT analysis.

Key results: The algorithm provides a personalized and adaptive approach and supports a more reasoned topic selection. Its potential to accelerate scientific work and stimulate interdisciplinary collaboration is emphasized.

Bibliographic description: Rashidov, A. Algorithm for optimizing the process of selecting a topic for a scientific publication with the assistance of ChatGPT. Strategies for Policy in Science and Education, vol. 33 (3), pp. 281–295, Az-buki, 2025. DOI: 10.53656/str2025-3-1-alg.

Method/approach: A six-step algorithm is proposed: setting formatting rules, entering sources, adapting the rules, automatic formatting, review and corrections, final confirmation and export. The configuration of a GPT assistant with examples of citation styles is also discussed.

Key results: The approach reduces manual work and the risk of formal errors and offers a flexible, scalable solution for authors and institutions.

Bibliographic description: A. Rashidov, “Automating Citation Formatting in Scientific Publications Using ChatGPT,” 2024 Asian Conference on Communication and Networks (ASIANComNet), Bangkok, Thailand, 2024, pp. 1–6. DOI: 10.1109/ASIANComNet63184.2024.10811018.

Method/approach: An eight-stage algorithm is proposed: entering the project proposal, defining criteria and sub-criteria with weights, ChatGPT analysis, qualitative assessment, quantitative assessment, SWOT analysis, reviewer verification and corrections, final evaluation and decision.

Key results: The algorithm creates a structured framework for faster and more consistent evaluation and facilitates the formulation of recommendations for improving project proposals.

Bibliographic description: A. Rashidov, “An Algorithm to Support the Review Process of a Scientific Research Project Proposal Using ChatGPT,” 2024 8th International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT), Ankara, Turkiye, 2024, pp. 1–6. DOI: 10.1109/ISMSIT63511.2024.10757273.

Method/approach: Six applied case studies and eight groups of limitations are systematized. A SWOT analysis of AI implementation in scientific research is carried out and possible solutions are proposed.

Key results: AI can improve the efficiency and quality of scientific work, but successful application requires coordination between the scientific community, industry, and regulators, as well as the preservation of human participation.

Bibliographic description: A. Rashidov and F. Rashidova, “Challenges and limitations in the use of artificial intelligence in research and some options to overcome them,” 2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT), Kamand, India, 2024, pp. 1–4. DOI: 10.1109/ICCCNT61001.2024.10724588.

Method/approach: A nine-stage algorithm is proposed: setting the topic and framework, generating a response, author evaluation, iterative corrections, SWOT analysis of structure and content, decision making, optional translation, grammar and spelling check, and process completion.

Key results: The algorithm enables personalization and time-resource optimization and provides a consistent process for creating abstracts according to the author’s needs.

Bibliographic description: A. Rashidov, “Algorithm for generating an abstract of a scientific publication with the assistance of ChatGPT,” 2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT), Kamand, India, 2024, pp. 1–5. DOI: 10.1109/ICCCNT61001.2024.10724617.

Method/approach: A nine-stage expert algorithm is proposed: information about the team and topics, profile analysis, generation and evaluation of proposals, SWOT analysis, selection, additional study, decision, optimization and additional consultations, and completion.

Key results: The approach provides personalized suggestions, faster decision-making, and the possibility of a reasoned SWOT analysis of alternatives.

Bibliographic description: A. Rashidov, “Expert algorithm to optimize the process of selecting a topic for a research project with the assistance of ChatGPT,” 2024 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA), Istanbul, Turkiye, 2024, pp. 1–5. DOI: 10.1109/HORA61326.2024.10550536.

Method/approach: A structured ten-stage approach is presented, including task initiation, specification of requirements, generation of a revised version, author evaluation, iterative corrections, optional SWOT analysis, multilingual adaptation or external verification, and finalization.

Key results: ChatGPT is presented as an effective assistant when instructions are clearly formulated and author control is explicit. The approach is flexible, fast, and applicable at both individual and institutional levels.

Bibliographic description: A. Rashidov and F. Rashidova, “A Structured Approach to Grammar and Style Checking of Scientific Texts With ChatGPT,” 2026 8th International Congress on Human-Computer Interaction, Optimization and Robotic Applications (ICHORA), Ankara, Turkiye, 2026, pp. 1–6. DOI: 10.1109/ICHORA69329.2026.11536994.

Method/approach: A nine-stage interactive algorithm is proposed: initiation, formulation of structural requirements, initial structure, author evaluation, decision, new instructions, revised structure, optional SWOT analysis, and finalization.

Key results: In a test with three authors, the average generation time was under 15 minutes, 1–3 iterations were needed, the average satisfaction was 4.7 out of 5, and all requirements were met.

Bibliographic description: A. Rashidov and F. Rashidova, “Model for generating the structure of a scientific publication using generative AI,” 2025 9th International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT), Ankara, Turkiye, 2025, pp. 1–6. DOI: 10.1109/ISMSIT67332.2025.11267973.

Method/approach: A ten-stage algorithm for grammar and style checking is presented: initiation, requirements, initial revision, author evaluation, decision, new instructions and iterations, optional SWOT analysis, multilingual adaptation or external check, and finalization.

Key results: The applicability of ChatGPT as an editorial assistant is demonstrated, with high flexibility, personalization, and speed when the author maintains control over meaning and terminology.

Bibliographic description: A. Rashidov, F. Rashidova. “Grammar and Style Verification of Scientific Publications Using ChatGPT,” 2025 16th International Conference on Computing Communication and Networking Technologies (ICCCNT), India, 2025, pp. 1–6.

Method/approach: A conceptual cyclical model is proposed with four blocks: educational objectives and input conditions; areas of application; a mechanism for controlled and responsible use; and results, assessment, and feedback. Synchronous and asynchronous modes are differentiated.

Key results: The model formulates a framework that places pedagogical purpose, teacher control, transparency, ethics, and data protection above the self-serving use of technology.

Bibliographic description: Rashidov, A. A model for the controlled and responsible implementation of generative artificial intelligence in synchronous and asynchronous distance learning in higher education. Fourth National Scientific and Practical Conference “Digital Transformation of Education – Problems and Solutions,” Ruse, 2026, pp. 621–626.

Method/approach: An experimental comparison between a control and an experimental group is conducted. The experimental group integrates adaptive exercises, automated checking, chatbots, virtual laboratories, recommendation systems, and early intervention.

Key results: Group B shows higher results: final test 4.75 ± 0.48 versus 4.20 ± 0.55; projects 4.80 ± 0.45 versus 4.30 ± 0.50; improvement +22% versus +9%. A statistically significant difference is reported at p < 0.05, together with higher confidence and satisfaction.

Bibliographic description: Rashidova, F., Rashidov, A. The application of artificial intelligence in teaching the course Internet-Based Systems. ARTTE, vol. 13, no. 3–4, 2026, pp. 145–152. DOI: 10.15547/artte.2025.03.005.

Method/approach: An experimental comparison is made between two groups of 20 second-year students. The experimental group uses adaptive exercises, automated code checking, ChatGPT for explanations and feedback, emulators, and virtual laboratories.

Key results: The experimental group shows a tendency toward better theoretical and practical results, higher motivation and confidence, and faster feedback. The authors note that the results are indicative.

Bibliographic description: A. Rashidov, F. Rashidova. Integrating Artificial Intelligence into the Teaching of Mobile Application Programming. International Scientific Conference UNITECH 2025, Gabrovo, Bulgaria, 20–21 November 2025.

Method/approach: A five-stage methodology is proposed: data collection and preparation; detection of functional dependencies through machine learning, statistical, and hybrid approaches; recommendation of normal forms; table transformation; verification and evaluation.

Key results: Higher motivation, fewer typical errors, and better understanding of theory through practical interaction with AI are observed.

Bibliographic description: A. Rashidov, F. Rashidova. Methodology for Database Normalization Using Artificial Intelligence. International Scientific Conference UNITECH 2025, Gabrovo, Bulgaria, 20–21 November 2025.

Method/approach: A review and analytical report is presented, with examples of tools and practices in preschool, secondary, and higher education. Applications, risks, and future directions are discussed.

Key results: AI is defined as a catalyst of educational transformation. The teacher’s role as mentor and critical corrective remains central, along with the need for AI literacy, an ethical framework, and an inclusive approach.

Bibliographic description: A. Rashidov, F. Rashidova. Education with Artificial Intelligence: Perspectives for the Next Generation of Learners. E-journal “Science and Education,” issue 11, July 2025, pp. 351–361. ISSN: 2683-0191.

Method/approach: An adapted ranking method based on weighting coefficients and concordance is applied. The evaluation is performed according to four criteria: efficiency, convenience, communication, and trust. A dynamic component and forecasting are added.

Key results: For 2025, the highest aggregate preferences are reported for ChatGPT, Grammarly, and Microsoft Copilot. The analysis identifies a stable preference for ChatGPT and Copilot, a rising trend for Khanmigo, a decline for Grammarly, a sustained decrease for AI search engines, and fluctuating behavior for Google Bard and other tools.

Bibliographic description: Aldeniz Rashidov. Analysis and evaluation of satisfaction and preferences regarding the use of artificial intelligence in education. International Journal on Information Technologies & Security, vol. 17, no. 4, 2025, pp. 23–32. DOI: 10.59035/STBI7753.

Method/approach: A modular conceptual architecture is proposed: an electronic nose with gas and chemical sensors, preprocessing, an ML/DL classification model, an LLM for interpretation and dialogue, an aroma generator, and user feedback.

Key results: The architecture closes the cycle “scent – analysis – transmission – reproduction – feedback” and outlines applications in industry, medicine, VR/AR, and e-commerce.

Bibliographic description: Rashidov, A., Rashidova, F. Conceptual architecture for imparting AI with olfaction: integration of electronic noses, aroma generators and LLM. International Journal on Information Technologies & Security, vol. 17, no. 2, 2025. DOI: 10.59035/VJJI1464.

Method/approach: A methodology for AISIQ — the intelligence quotient of artificial intelligence systems — is proposed. Types of intelligence are defined: linguistic, logical-mathematical, spatial, musical, motor, emotional, and others. mAISIQ and a correction factor for the “age” of the system are introduced.

Key results: The methodology offers an initial quantitative tool for comparing intelligent systems and identifying areas for improvement.

Bibliographic description: A. Rashidov, “Determining of the degree of intelligence of artificial intelligence systems,” 2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT), Delhi, India, 2023, pp. 1–6. DOI: 10.1109/ICCCNT56998.2023.10307831.