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.

Mrs. Kavitha Duraipandian | Machine learning Awards | Excellence in Research

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Mrs. Kavitha Duraipandian | Machine learning Awards | Excellence in Research

Mrs. Kavitha Duraipandian, Sathyabama Institute of Science and Technology, India

Mrs. Kavitha Duraipandian is an Assistant Professor at Sathyabama Institute of Science and Technology, Chennai, and is currently pursuing a Ph.D. in Deep Learning at SRM Institute of Science and Technology. She holds a Master’s degree in Computer Science from Anna University and a Bachelor’s degree from Madras University. With a rich teaching career spanning roles at SRM Institute of Science and Technology, Dhaanish Ahmed College of Engineering, and other institutions, Kavitha has instructed various subjects, including Machine Learning and Cloud Computing. She has earned accolades such as “The Real Super Woman 2020” award and the Woman MoU Leader of the Year 2024 award. Kavitha also mentors over 75 students in Indo-Global internships, focusing on ML, DL, AI, and Cybersecurity.

Professional Profile:

Scopus
Orcid
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🎓 Education:

Kavitha Duraipandian is currently pursuing a Ph.D. in Deep Learning at SRM Institute of Science and Technology, Kattankulathur (since January 2020). She holds a Master of Engineering in Computer Science from Anna University (2009-2011) with a 79% score and a Bachelor of Engineering in Computer Science from Madras University (1997-2001) with a 70% score.

💼 Academic Experience:

Kavitha is an Assistant Professor at Sathyabama Institute of Science and Technology, Chennai (since June 2024). She has previously served as an Assistant Professor at SRM Institute of Science and Technology, Ramapuram (2019-2024), and Dhaanish Ahmed College of Engineering, Chennai (2011-2019). Her earlier roles include Lecturer positions at Tagore Engineering College, Sri Sai Ram Engineering College, and Thiruvalluvar College of Engineering and Technology.

🏆 Awards and Achievements:

Kavitha has coordinated and mentored a team that won first prize in the International App Development Competition (2020) and has received several accolades, including “The Real Super Woman 2020” award and the Woman MoU Leader of the Year 2024 award.

🌐 International Mentorship:

She mentors over 75 students in Indo-Global Summer/Winter Internships, focusing on ML, DL, AI, and Cybersecurity, in collaboration with MIT Square, London, and foreign universities.

📚 Subjects Handled:

Kavitha has taught a wide range of subjects under both deemed universities and Anna University-affiliated institutions, including Information Storage and Management, Machine Learning applications, Cloud Computing, Database Management Systems, Data Structures, Software Engineering, and more.

Publication Top Notes: