Mr. Pratik Thantharate | Artificial Intelligence | Editorial Board Member

Published on by Computer Scientists Awards

Mr. Pratik Thantharate | Artificial Intelligence | Editorial Board Member

Paycor | United States

Pratik Thantharate is a distinguished researcher and Principal Software Engineer whose work spans Agile Software Development, Cybersecurity, DevOps, Cloud Computing, and Code-to-Cloud Security. With dual master’s degrees in Computer Science and Information Systems, he has established a strong research portfolio integrating automation, security, and large-scale distributed architectures. His expertise includes CI/CD pipelines, containerization, microservices, infrastructure as code, observability frameworks, and privacy-preserving systems for modern software ecosystems. Pratik has authored peer-reviewed publications, contributed book chapters, and published impactful research in prominent venues across Elsevier, IEEE, and MDPI. His innovations explore energy-efficient UAV optimization, federated learning for cybersecurity, Zero-Trust blockchain architectures, advanced observability mechanisms for DevOps, and heuristic genetic algorithms for automated vulnerability detection. He has also contributed two patents focused on intelligent monitoring and advanced security analytics for DevSecOps environments. In addition to his research outputs, Pratik has served on numerous technical program committees and peer-reviewed over a hundred scholarly articles across international conferences and journals. His scholarly influence continues to grow, with Scopus indexing showing 128 citations across 119 citing documents, 9 documents, and an h-index of 5. Google Scholar metrics reflect 46 citations, an h-index of 4, and an i10-index of 2. His research aims to advance secure, reliable, and high-performance software delivery by integrating next-generation DevOps automation, AI-driven cybersecurity, and privacy-aware computing frameworks to meet emerging industry and academic challenges.

Profile

Scopus | ORCID

Featured Publications

Thantharate, P., Thantharate, A., & Kulkarni, A. (2024). GREENSKY: A fair energy-aware optimization model for UAVs in next-generation wireless networks. Green Energy and Intelligent Transportation, 3(1), 100130.

Thantharate, P., & Thantharate, A. (2023). ZeroTrustBlock: Enhancing security, privacy, and interoperability of sensitive data through ZeroTrust permissioned blockchain. Big Data and Cognitive Computing, 7(4), 165.

Thantharate, P., & Anurag, T. (2023). CYBRIA: Pioneering federated learning for privacy-aware cybersecurity with brilliance. Proceedings of the IEEE International Conference on Smart Communities.

Thantharate, P. (2023). IntelligentMonitor: Empowering DevOps environments with advanced monitoring and observability. Proceedings of the International Conference on Information Technology, 800–805.

Thantharate, P. (2023). GeneticSecOps: Harnessing heuristic genetic algorithms for automated security testing and vulnerability detection in DevSecOps. Proceedings of the International Conference on Contemporary Computing and Informatics.

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

Published on by Computer Scientists Awards

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.