Didier Torres Guzmán | Machine Learning | Best Researcher Award

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Dr. Didier Torres Guzmán | Machine Learning | Best Researcher Award

Professor | National Autonomous University of Mexico | Mexico

Dr. Didier Torres Guzmán is a distinguished researcher whose work focuses on biomedical signal processing, neuroimaging, and the application of machine learning to clinical diagnostics. His research contributions have advanced the understanding and analysis of neurological and physiological conditions, particularly through the development of innovative computational biomarkers and signal processing techniques. Notably, he has explored tortuosity and discrete compactness biomarkers for machine learning-based classification of mild cognitive impairment, providing new tools for early and accurate detection of cognitive decline. In addition, his studies on discrete neuroimaging metrics have enabled the identification of structural brain alterations associated with COVID-19, highlighting the relevance of his work to pressing global health challenges. Dr. Torres Guzmán has also contributed to non-invasive physiological monitoring, including methods for estimating heart and respiratory rates through face video processing and novel approaches for ECG signal morphology analysis using tortuosity estimation. His work consistently demonstrates a combination of methodological rigor, interdisciplinary application, and translational potential, bridging computational techniques with practical healthcare solutions. The originality and impact of his research are reflected in his publications in high-quality peer-reviewed journals and book chapters, where he collaborates with international researchers across biomedical engineering, signal processing, and clinical disciplines. Through these contributions, Dr. Torres Guzmán has established himself as a leading figure in his field, whose work not only advances scientific knowledge but also has tangible implications for improving patient care, diagnostic accuracy, and the integration of artificial intelligence in biomedical research, making him a highly deserving candidate for recognition with the Best Researcher Award.

Profile: ORCID | Scopus

Featured Publications

Torres Guzmán, D., Pinzón Vivas, J. D., & Barbará Morales, E. (2026). Tortuosity and discrete compactness biomarkers for machine learning-based classification of mild cognitive impairment. Biomedical Signal Processing and Control.

Delgado-Castillo, D., Barbará-Morales, E., Hevia-Montiel, N., Arámbula-Cosío, F., & Torres Guzmán, D. (2025). Discrete neuroimaging metrics for identifying structural alterations in COVID-19-related brain atrophy. International Journal of Online and Biomedical Engineering (iJOE).

Ruíz-Espinosa, G., Jimenez-Angeles, L., Torres Guzmán, D., Rojas-Arce, J. L., & Marmolejo-Saucedo, J. A. (2024). A comparison of algorithms to estimate heart and respiratory rate from face video processing. In Book chapter.

Pacheco González, L. E., Torres Guzmán, D., & Barbará-Morales, E. (2024). A novel method for ECG signal morphology analysis using tortuosity estimation. Biomedical Signal Processing and Control.

Dilshod Nematov | Machine Learning | Best Researcher Award

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Prof. Dr. Dilshod Nematov | Machine Learning | Best Researcher Award

Head of the Quantum Electronics Laboratory, S.U.Umarov Physical–Technical Institute of the National Academy of Sciences of Tajikistan, Tajikistan

Prof. Dr. Dilshod Nematov, Ph.D., is a distinguished physicist and the Head of the Laboratory of Quantum Electronics at the S.U. Umarov Physical–Technical Institute of the National Academy of Sciences of Tajikistan, recognized for his interdisciplinary expertise in physics, quantum electronics and machine learning applications in functional materials. He completed his Ph.D. in Materials Science at Tajik National University in 2021, after earning a Master’s degree in Physics (2019) and a Bachelor of Science in Physics (2017) from the same institution. Professionally, he has held key positions including Senior Researcher, Scientific Secretary and Senior Lecturer at the Tajik Technical University, demonstrating leadership in both research and academic settings. His research focuses on the integration of molecular dynamics, quantum chemistry, and machine learning techniques to optimize functional materials for photovoltaic and LED applications, with extensive experience in experimental synthesis and advanced material characterization. Prof. Dr. Dilshod Nematov has participated in numerous international research projects and scientific internships in Japan, Portugal, Spain, Germany, Ukraine and Kazakhstan, fostering a robust global scientific network. His research skills encompass experimental physics, computational modeling, quantum electronics and data-driven material analysis, contributing to 20 Scopus-indexed publications with 162 citations and an h-index of 8. He has been recognized with several prestigious honors, including the Best Young Scientist of the CIS Countries Award (2023) and the Mayor of Dushanbe Prize in Natural and Technical Sciences (2023). With his strong academic record, international collaborations and leadership capabilities, Prof. Prof. Dr. Dilshod Nematov is well-positioned to advance high-impact research, mentor emerging scientists and drive innovative developments in machine learning and quantum materials, making him highly deserving of global recognition and awards.

Profile: Scopus | ORCID | Google Scholar | ResearchGate

Featured Publications

Nematov, D. D., Kholmurodov, K. T., Husenzoda, M. A., Lyubchyk, A., … (2022). Molecular adsorption of H2O on TiO2 and TiO2: Y surfaces. Journal of Human, Earth, and Future, 3(2), 213–222.

Davlatshoevich, N. D., Ashur, K. M., Saidali, B. A., KholmirzoTagoykulovich, K., … (2022). Investigation of structural and optoelectronic properties of N-doped hexagonal phases of TiO2 (TiO2-xNx) nanoparticles with DFT realization: Optimization of the band gap and … Biointerface Research in Applied Chemistry, 12(3), 3836–3848.

Nematov, D. D. (2021). Investigation optical properties of the orthorhombic system CsSnBr3-xIx: Application for solar cells and optoelectronic devices. Journal of Human, Earth, and Future, 2(4), 404–411.

Nematov, D. (2024). Analysis of the optical properties and electronic structure of semiconductors of the Cu2NiXS4 (X = Si, Ge, Sn) family as new promising materials for optoelectronic devices. Journal of Optics and Photonics Research, 91–97.

Nematov, D. D., Burhonzoda, A. S., Khusenov, M. A., Kholmurodov, K. T., … (2019). The quantum-chemistry calculations of electronic structure of boron nitride nanocrystals with density functional theory realization. Egyptian Journal of Chemistry, 62, 21–27.