Assist. Prof. Dr. Mustaqeem Khan | Artificial intelligence | Best Researcher Award

Assist. Prof. Dr. Mustaqeem Khan | Assistant Professor | United Arab Emirates University | United Arab Emirates

Academic Background

Dr. Mustaqeem Khan is a distinguished researcher and academic in the field of Artificial Intelligence and Signal Processing. He earned his Doctorate in Software Convergence from Sejong University, South Korea, where his research focused on emotion recognition using deep learning. He also holds a Master’s degree in Computer Science from Islamia College Peshawar, Pakistan, where he was awarded a Gold Medal for academic excellence, and a Bachelor’s degree in Computer Science from the University of Agriculture, Peshawar. Dr. Khan’s scholarly impact is reflected in his remarkable research record, with Scopus indexing 47 documents and over 2,412 citations, resulting in an h-index of 20. On Google Scholar, his work has gained over 2,934 citations, maintaining an h-index of 21 and an i10-index of 31, positioning him among the top two percentage scientists globally.

Research Focus

His research primarily explores Speech and Audio Signal Processing, Emotion Recognition, and Deep Learning. Dr. Khan’s studies integrate multi-modal data analysis through advanced architectures, such as CNNs and Transformers, for applications in speech emotion recognition, computer vision, and energy analytics.

Work Experience

Dr. Khan serves as an Assistant Professor at the United Arab Emirates University, contributing to teaching, research supervision, and curriculum development. Previously, he worked as a Postdoctoral Fellow and Lab Coordinator at the Mohamed Bin Zayed University of Artificial Intelligence, where he collaborated with the Technical Innovation Institute on drone detection systems and managed multidisciplinary AI research teams. Before that, he gained substantial academic and research experience as a Research Assistant at Sejong University and as a Lecturer at Islamia College Peshawar, mentoring students in core computer science and artificial intelligence subjects.

Key Contributions

Dr. Khan has developed several advanced deep learning models, including hybrid attention transformers, multimodal cross-attention networks, and ensemble architectures for audio-visual recognition tasks. His work has contributed to advancements in emotion recognition, drone-based surveillance, and smart city analytics. He has also participated in major funded projects supported by the National Research Foundation of Korea and the Technology Innovation Institute, UAE.

Awards & Recognition

He has been honored with multiple distinctions, including Best Paper Awards, an Outstanding Research Award during his Ph.D., and recognition as a Gold Medalist for academic performance. His inclusion among the Top 2% Scientists (2023–2024) underscores his exceptional research influence and scholarly excellence.

Professional Roles & Memberships

Dr. Khan is an editorial board member and associate editor for several international journals, including the Annals of Applied Sciences and the European Journal of Mathematical Analysis. He serves as a reviewer for over 35 prestigious journals such as IEEE Access, Applied Soft Computing, and Knowledge-Based Systems, actively contributing to academic quality and peer review.

Profile

Scopus | Google Scholar | ORCID

Featured Publications

Khan, M., Ahmad, J., El Saddik, A., & Gueaieb, W. (2025). Joint Multi-Scale Multimodal Transformer for Emotion Using Consumer Devices. IEEE Transactions on Consumer Electronics.

Khan, M., Tran, P. N., Pham, N. T., & Othmani, A. (2025). MemoCMT: Multimodal Emotion Recognition Using Cross-Modal Transformer-Based Feature Fusion. Nature Scientific Reports.

Khan, M., Ahmad, J., El Saddik, A., & Gueaieb, W. (2024). Drone-HAT: Hybrid Attention Transformer for Complex Action Recognition in Drone Surveillance Videos. Proceedings of IEEE/CVF Conference on Computer Vision and Pattern Recognition.

Khan, M., Kwon, S. (2021). Optimal Feature Selection Based Speech Emotion Recognition Using Two-Stream Deep Convolutional Neural Network. International Journal of Intelligent Systems.

Khan, M., Kwon, S. (2021). Att-Net: Enhanced Emotion Recognition System Using Lightweight Self-Attention Module. Applied Soft Computing.

Impact Statement / Vision

Dr. Mustaqeem Khan envisions advancing AI systems capable of understanding human emotions and behaviors with precision and empathy. His goal is to integrate deep learning and multimodal intelligence into real-world applications that enhance human–machine interaction, healthcare, and smart technologies. His ongoing commitment to innovation continues to shape the future of intelligent computing and global research collaboration.

Ms. Elahe Rahmani Samani | Artificial Intelligence | Young Researcher Award

Ms. Elahe Rahmani Samani, Undergraduate Researcher, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.

Ms. Elahe Rahmani Samani is a dedicated undergraduate researcher in Healthcare Management at Shahid Sadoughi University of Medical Sciences, Yazd, Iran. With a strong commitment to advancing health systems through innovative technologies, she has emerged as a promising young voice in the intersection of healthcare and artificial intelligence. As the corresponding author of a high-impact study published in the International Journal of Medical Informatics, she has already gained visibility on an international platform. Elahe is also an editorial board member of a university-affiliated journal and actively engages in research collaboration, demonstrating leadership and academic excellence early in her career.

🎓 Education Background

Ms. Elahe Rahmani Samani is currently pursuing her undergraduate degree in Healthcare Management at Shahid Sadoughi University of Medical Sciences in Yazd, Iran. Her academic journey has been marked by an early passion for healthcare innovation and policy development. As a student member of the Health Policy and Management Research Center, she has access to extensive research mentorship and academic resources, which support her pursuits in AI integration in health systems. Her education equips her with both practical management knowledge and technical understanding essential for modern health leadership. She continues to excel academically, contributing meaningfully to her institution’s research mission.

💼 Professional Experience

Although still an undergraduate student, Ms. Rahmani Samani has demonstrated remarkable initiative by leading and collaborating on several research projects. Her standout experience includes serving as the primary researcher and corresponding author for a study on AI adoption in hospital settings, presented at the International Congress on Artificial Intelligence in Health. She also serves on the editorial board of a university-affiliated journal, where she helps shape academic content for peer learning. Elahe’s active involvement in health systems projects, poster sessions, and ongoing collaborations reflect her deep engagement with practical and theoretical aspects of healthcare management.

🏆 Awards and Honors

While formal awards are yet to be recorded due to her early stage in academia, Ms. Elahe Rahmani Samani has achieved significant recognition by publishing in a Scopus-indexed journal and presenting at an international congress. She earned certificates of participation from the International Congress on Artificial Intelligence in Health and is continuously contributing to scholarly work in health systems. Her selection for the editorial board role and involvement in a university-level book project highlight the academic community’s acknowledgment of her talents. Her publication is already accessible through global platforms and is poised to gain academic citations in the near future.

🔬 Research Focus

Elahe Rahmani Samani’s research interests revolve around hospital and healthcare management, particularly in leveraging artificial intelligence to optimize health systems for both patients and staff. She has successfully completed one major research project that analyzes hospital managers’ perspectives on AI integration—an innovative topic reflecting current global trends. Her work aims to influence strategic decision-making within health institutions by promoting the adoption of intelligent systems. She is also contributing to an ongoing book project in healthcare management and continues to work on four other health-related research studies, exploring themes of efficiency, technology adoption, and patient-centered care in health policy.

🧭 Conclusion

Ms. Elahe Rahmani Samani exemplifies the drive and intellect of a next-generation healthcare researcher. Her early publication in a high-impact journal and involvement in both local and international academic platforms underscore her potential to become a leader in the field. With a unique blend of management insight and technological perspective, she aims to transform how healthcare institutions approach innovation. Her commitment to research excellence, combined with her growing professional network and academic contributions, positions her as a strong contender for the Young Researcher Award. Her journey is only beginning, and she is already contributing to global discussions in health innovation.