Ikramov Alisher Akramovich

Alisher Ikramov is a mathematician and computer scientist from Tashkent, Uzbekistan. He earned his PhD in Physics and Mathematics from the National University of Uzbekistan in 2021, following his Master’s and Bachelor’s degrees in Applied Mathematics and Computer Science from the Tashkent branch of Lomonosov Moscow State University, both completed with honors. Throughout his academic path, he has demonstrated excellence—from ranking among the top in university entrance exams to winning 3rd place at the ACM ICPC regional contest in 2010.

Alisher has been actively involved in research since 2012, initially at the National University of Uzbekistan, where he progressed from Engineer to Senior Researcher. His work has spanned diverse areas such as cryptanalysis using parallel computing, development of novel cryptographic primitives, national Linux-based OS design, and computational modeling in soil filtration and drug discovery. Since 2015, he has also held a part-time senior research role at the Institute of Mathematics under the Uzbekistan Academy of Sciences, focusing on bioinformatics and the application of machine learning in drug design.

In parallel with research, Alisher is a dedicated educator. He has lectured on advanced mathematics, logic, and circuit control at the National University of Uzbekistan and the Tashkent branch of Lomonosov MSU. He also teaches mathematics and informatics at Lider Ta’lim School. For his contributions to education, he was awarded the title of “Excellent Teacher” by the Ministry of Public Education in 2021. Fluent in English (IELTS 8.0), proficient in C++, Python, and machine learning, Alisher continues to bridge theoretical science with practical, high-impact computational research.

1. A. Ikramov, S. Mukhtarova, R. Trigulova, D. Alimova, S. Abdullaeva. Prediction of glycosylated hemoglobin level in patients with cardiovascular diseases and type 2 diabetes mellitus with respect to anti-diabetic medication, Front. Endocrinol., 2024. DOI: 10.3389/fendo.2024.1305640
2. R.Kh. Trigulova, Sh.Sh. Mukhtarova, D.A. Alimova, Kh.G. Fozilov, A.A. Ikramov. Features of the Trajectories of Glycated Hemoglobin in Patients with CHD and DM 2, Am. Heart J., 2024. DOI: 10.1016/j.ahj.2023.08.024
3. A. Ikramov, M. Aripov, G. Juraev. SPONGE structure in the basis of a new stream cipher, Novel Trends in Rheology IX, 2023. DOI: 10.1063/5.0144775
4. D. Alimova, A. Ikramov, R. Trigulova, S. Abdullaeva, S. Mukhtarova. Prediction of diastolic dysfunction in patients with cardiovascular diseases and type 2 diabetes with respect to COVID-19 in anamnesis using artificial intelligence, Proc. ICMHI 2023. DOI: 10.1145/3608298.3608310
5. A. Ikramov, B. Rasulev, F. Adilova. Using machine learning algorithms to predict the activity of fullerene nanoparticles, Novel Trends in Rheology IX, 2023. DOI: 10.1063/5.0144774
6. A. Ikramov, D.A. Alimova, A.A. Ikramov, N.M. Alikhanova, F.A. Takhirova. Prospects for the use of AI technologies in predicting CVD outcomes in T2DM patients, Zenodo, 2022. DOI: 10.5281/ZENODO.7085885
7. A. Ikramov. Machine Learning Algorithms in Application to COVID-19 Severity Prediction in Patients, Lect. Notes Comput. Sci., 2022. DOI: 10.1007/978-3-030-97546-3_28
8. A. Ikramov, K. Nabijonov, B. Rasulev. Determining the Activity of Fullerene Nanoparticles Using QSAR Models, Adv. Intell. Syst. Comput., 2021. DOI: 10.1007/978-3-030-68004-6_11
9. A. Ikramov. The Complexity of Testing Cryptographic Devices on Input Faults, Netw. Syst. Secur., 2021. DOI: 10.1007/978-3-030-92708-0_12
10. A. Ikramov. COVID-19 Severity Prediction in Patients Based on Anomaly Detection Approach, Proc. ICICCT, 2021. DOI: 10.1007/978-981-16-2377-6_56