Dr. Sheharyar Khan | Diagnosis of Infectious Diseases | Best Researcher Award

Postdoctoral Research Fellow | Shandong University | China

Dr. Sheharyar Khan is a highly skilled researcher specializing in the Diagnosis of Infectious Diseases, demonstrating outstanding contributions through his academic and scientific achievements. His education in Computer Science and Software Engineering has been instrumental in developing innovative computational models and AI-based frameworks that enhance the Diagnosis of Infectious Diseases through data analysis, prediction models, and intelligent diagnostic systems. Professionally, Dr. Khan has held roles as a Postdoctoral Research Fellow, IT Specialist, and Lecturer, where he applied advanced technologies to improve the Diagnosis of Infectious Diseases by integrating machine learning and computational techniques. His research focuses on using cloud computing, big data, and ensemble learning to improve precision in the Diagnosis of Infectious Diseases. His numerous peer-reviewed publications, recognized in leading journals, contribute to cutting-edge advancements in healthcare technology and the Diagnosis of Infectious Diseases. Dr. Khan has received multiple honors and awards, including international scholarships and distinctions for his exceptional research performance related to the Diagnosis of Infectious Diseases. His technical expertise spans machine learning, deep learning, IoT, and data-driven software applications that strengthen real-time Diagnosis of Infectious Diseases. With strong analytical and programming skills, he continues to drive impactful scientific progress. Overall, Dr. Sheharyar Khan embodies a blend of innovation, academic excellence, and leadership in the Diagnosis of Infectious Diseases field, maintaining a Google Scholar profile of 113 Citations, 7 h-index, and 6 i10-index.

Profiles: Google Scholar | ORCID

Featured Publications

1. Ahmed, U., Jiangbin, Z., Almogren, A., Khan, S., Sadiq, M. T., Altameem, A., & others. (2024). Explainable AI-based innovative hybrid ensemble model for intrusion detection. Journal of Cloud Computing, 13(1), 150.

2. Khan, S., Jiangbin, Z., Irfan, M., Ullah, F., & Khan, S. (2024). An expert system for hybrid edge to cloud computational offloading in heterogeneous MEC–MCC environments. Journal of Network and Computer Applications, 225, 103867.

3. Khan, S., Zheng, J., Khan, S., Masood, Z., & Akhter, M. P. (2023). Dynamic offloading technique for real-time edge-to-cloud computing in heterogeneous MEC–MCC and IoT devices. Internet of Things, 24, 100996.

4. Khan, S., Jiangbin, Z., Ullah, F., Akhter, M. P., Khan, S., Awwad, F. A., & Ismail, E. A. A. (2024). Hybrid computing framework security in dynamic offloading for IoT-enabled smart home system. PeerJ Computer Science, 64.

5. Afridi, A., Wahab, A., Khan, S., Ullah, W., Khan, S., Islam, S. Z. U., & Hussain, K. (2021). An efficient and improved model for power theft detection in Pakistan. Bulletin of Electrical Engineering and Informatics, 10(4), 1828–1837.

Dr. Sanaz Ahmadi | Diagnosis of Infectious Diseases | Best Researcher Award

Researcher | Academic Center for Education, Culture and Research | Iran

Dr. Sanaz Ahmadi Ghezeldasht is a distinguished researcher and molecular biologist at the Molecular Biology Section, Central Laboratory ACECR, Mashhad, Iran, specializing in medical immunology, molecular virology, and infectious diseases. She holds a Ph.D. in Medical Immunology from Mashhad University of Medical Sciences, an M.Sc. in Animal Physiology from Payam-e-Noor University of Isfahan, and a B.Sc. in Biology from Ferdowsi University of Mashhad. Dr. Ghezeldasht has served as the Supervisor of the Molecular Biology Center at Jahad Daneshgahi Mashhad, contributing to several national and international research projects focused on HTLV-1 pathogenesis, viral immunology, and host-virus interactions. Her prolific research portfolio encompasses numerous peer-reviewed publications in high-impact journals such as Reviews in Medical Virology, Journal of NeuroVirology, and Applied Biochemistry and Biotechnology, highlighting novel insights into viral oncogenesis, molecular diagnostics, and therapeutic development. A dedicated academic leader, she has organized and contributed to multiple scientific congresses and health monitoring initiatives. Dr. Ghezeldasht’s expertise extends to genetic engineering, bioinformatics, PCR technologies, and cell culture, complemented by certifications in English proficiency and advanced computer literacy. She is an active member of the HTLV-I Foundation and the Research Center for HIV/AIDS, HTLV, and Viral Hepatitis at ACECR, reflecting her enduring commitment to advancing molecular medicine and public health. Her scholarly impact is reflected by 409 citations across 26 publications with an h-index of 10.

Profiles: Scopus | ORCID

Featured Publication

1. Shafaei, A., Talebi, K., Zarean, M., Mosavat, A., Khajedaluee, A. R., Afzalaghaee, M., Shamsian, S. A. A., & Ghezeldasht, S. A. (2025). Intestinal parasitic infections, eosinophilia, and Th1/Th2 immune profiles in haemodialysis patients. Parasite Immunology.

2. Rahimzada, M., Nahavandi, M., Saffari, M., Shafaei, A., Mosavat, A., Ghezeldasht, S. A., Ariaee, N., Valizadeh, N., Rahimi, H., Rezaee, S. A., et al. (2023). Gene expression study of host-human T-cell leukaemia virus type 1 (HTLV-1) interactions: adult T-cell leukaemia/lymphoma (ATLL). Molecular Biology Reports, 50(9).

3. Yousefpoor, N., Mahdavian, M., Pourbagher, Z., Ghezeldasht, S. A., Mosavat, A., Ziaee, M., Bahreini, M., Soleimanpour, S., Sharifmoghadam, M. R., Valizadeh, N., et al. (2023). Role of host immunity and HBx among inactive chronic hepatitis B patients in a highly endemic region. Microbial Pathogenesis, 180, 106170.

4. Ghezeldasht, S. A., Bidkhori, H. R., Miri, R., Baghban, A., Mosavat, A., & Rezaee, S. A. (2023). Momordica charantia phytoconstituents can inhibit human T-lymphotropic virus type-1 (HTLV-1) infectivity in vitro and in vivo. Journal of NeuroVirology, 29(4), 567–578.