Subhra Suhaney | Cybersecurity and Cryptography | Forensic Scientist of the Year Award

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Dr. Subhra Suhaney | Cybersecurity and Cryptography | Forensic Scientist of the Year Award

Institute for Excellence in Higher Education Bhopal | India

Dr. Subhra Suhaney is a dedicated forensic science researcher whose work spans analytical toxicology, advanced chromatographic method development, digital forensics, and technology-driven innovations in forensic education. Her research is prominently recognized for pioneering contributions in the detection, separation, and quantification of stupefacient and psychoactive compounds in foodstuffs and beverages an area of critical importance to forensic toxicology, criminal investigations, and public safety. She has significantly advanced the application of Micellar Liquid Chromatography (MLC), establishing it as an eco-friendly, cost-effective, and analytically robust alternative to conventional TLC and HPLC for benzodiazepines and other psychoactive substances. Her publications in respected journals such as the Journal of AOAC International, Journal of Liquid Chromatography & Related Technologies, E-Journal of Chemistry, and the Journal of the Indian Chemical Society demonstrate strong methodological precision and practical forensic relevance. Dr. Subhra Suhaney’s scholarly outputs include validated multi-analyte detection protocols, rapid screening techniques for ketamine-based adulteration, and improved chromatographic systems that enhance the reliability and evidentiary value of forensic analyses. Beyond chemical forensics, she contributes to the fields of digital forensics, AI-based data privacy concerns, and ICT-enabled learning, reflecting an interdisciplinary approach aligned with modern forensic challenges. She has actively presented her work in national conferences, participated in academic workshops, and developed quality e-content in fingerprint science to strengthen forensic pedagogy. According to Google Scholar, she has over six research publications with 15 citations, an h-index of 3, underscoring the scholarly impact and growing recognition of her research contributions.

Profile: Google Scholar

Featured Publications

1. Subhra, H., Devasish, B., Josep, E. R., & Abhilasha, D. (2012). Micellar liquid chromatography for the determination of some less prescribed benzodiazepines. Journal of Chemistry, 9(1), 443–450.

2. Subhra, H., Prakash, D. N., Abhilasha, D., Josep, E. R., & Devasish, B. (2014). Simultaneous determination of psychoactive compounds in foodstuffs using micellar liquid chromatography with direct injection. Journal of AOAC International, 97(2), 409–414.

3. Hoonka, S., Durgbanshi, A., Esteve-Romero, J., Dubey, N. P., & Bose, D. (2014). Simultaneous determination of three stupefacients in foodstuff using high-performance liquid chromatography. Journal of Liquid Chromatography & Related Technologies, 37(9), 1287–1297.

4. Hoonka, S., Dubey, N. P., Esteve-Romero, J., Durgbanshi, A., & Bose, D. (2013). Rapid screening of ketamine in confiscated orange juice by thin layer chromatography. Journal of the Indian Chemical Society, 90(4), 513–517.

5. Suhaney, S. (2025). Breach of users’ personal data by artificial intelligence. International Journal of All Research Education and Scientific Methods.

Mahmoud Abd-Ellah | Computer Science | Best Researcher Award

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Assoc. Prof. Dr. Mahmoud Abd-Ellah | Computer Science | Best Researcher Award

Egyptian Russian University | Egypt

Dr. Mahmoud Khaled Abd-Ellah is an accomplished Assistant Professor at the Faculty of Artificial Intelligence, Egyptian Russian University, Badr, Egypt, widely recognized for his pioneering research at the intersection of artificial intelligence, medical imaging, and deep learning. Holding a Ph.D. in Electrical Engineering from Minia University, his doctoral research focused on brain tumor diagnosis through MRI using advanced machine learning techniques. His impressive publication portfolio includes 22 Scopus-indexed papers, collectively cited 830 times by 774 documents, with an h-index of 12 demonstrating substantial scientific impact and research excellence. His scholarly work has been featured in leading journals such as Scientific Reports, Neural Computing and Applications, and Ecological Informatics, advancing AI-driven approaches for medical image analysis, automated brain tumor detection, COVID-19 classification, and environmental data modeling. Beyond research, Dr. Abd-Ellah actively contributes to academic governance and quality enhancement as a member of the Egyptian International Ranking Committee, head of the Quality Management Unit, and ranking official at the Egyptian Russian University. He is also an active member of multiple IEEE councils, engaging in the development and application of AI across engineering and biomedical domains. His ORCID profile (0000-0002-6840-2503) and Scopus ID (57191265348) further reflect his consistent record of impactful scholarship and international collaboration. With his interdisciplinary expertise, editorial service, and mentorship of Ph.D. and master’s students, Dr. Mahmoud Khaled Abd-Ellah exemplifies academic leadership, innovation, and a transformative approach to research that advances both science and society.

Profile: Scopus | Google Scholar | ORCID | ResearchGate

Featured Publications

  • Abd-Ellah, M. K., Awad, A. I., Khalaf, A. A. M., & Hamed, H. F. A. (2019). A review on brain tumor diagnosis from MRI images: Practical implications, key achievements, and lessons learned. Magnetic Resonance Imaging, 61, 300–318.

  • Abd-Ellah, M. K., Awad, A. I., Khalaf, A. A. M., & Hamed, H. F. A. (2018). Two-phase multi-model automatic brain tumour diagnosis system from magnetic resonance images using convolutional neural networks. EURASIP Journal on Image and Video Processing, 2018(1), 1–10.

  • El-Rawy, M., Abd-Ellah, M. K., Fathi, H., & Ahmed, A. K. A. (2021). Forecasting effluent and performance of wastewater treatment plant using different machine learning techniques. Journal of Water Process Engineering, 44, 102380.

  • Abd-Ellah, M. K., Awad, A. I., Khalaf, A. A. M., & Hamed, H. F. A. (2016). Design and implementation of a computer-aided diagnosis system for brain tumor classification. In 2016 28th International Conference on Microelectronics (ICM) (pp. 73–76).

  • MostafaShokry, A. A. M. K., Awad, A. I., & Abd-Ellah, M. K. (2022). Systematic survey of advanced metering infrastructure security: Vulnerabilities, attacks, countermeasures, and future vision. Future Generation Computer Systems, 1–21.