Mr. Pratik Thantharate | Artificial Intelligence | Editorial Board Member

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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. Mehtab Alam | Artificial Intelligence | Best Researcher Award

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Assist. Prof. Dr. Mehtab Alam | Artificial Intelligence | Best Researcher Award

Assist. Prof. Dr. Mehtab Alam |Assistant Professor | Delhi University | India

Dr. Mehtab Alam is an accomplished IT professional and academic specializing in Artificial Intelligence (AI), Internet of Things (IoT), Cyber Forensics, and Information Security. His research primarily focuses on developing AI-based smart IoT frameworks for intelligent healthcare systems, with a strong emphasis on predictive modeling, machine learning integration, and cloud-based data analytics. His scholarly contributions demonstrate a multidisciplinary approach combining computer science, data-driven healthcare innovation, and digital transformation. He has explored diverse research areas including smart city technologies, blockchain applications in e-governance, cybersecurity frameworks, and the application of swarm intelligence in network optimization. Dr. Alam has published extensively in reputed international journals and conferences, contributing to advancements in AI-driven sustainable systems and smart healthcare solutions. His works reflect technical depth and practical applicability, addressing modern challenges in digital infrastructure, public health informatics, and secure communication systems. He has authored 15 Scopus-indexed publications, with 30 Scopus citations and an h-index of 4. On Google Scholar, his research has received 256 citations with an h-index of 10 and an i10-index of 11, showcasing his growing academic influence.

Publication Profile

Scopus | ORCID | Google Scholar

Featured Publications

Alam, M., Khan, E. R., Alam, A., Siddiqui, F., & Tanweer, S. (2023). The DIABACARE CLOUD: Predicting diabetes using machine learning. Acta Scientiarum Technology, 46(1).

Alam, M., Khan, I. R., Alam, A., Siddiqui, F., & Tanweer, S. (2023). Smart healthcare: Making medicine intelligent. Journal of Propulsion Technology, 44(3).

Alam, M., Khan, R., Alam, A., Siddiqui, F., & Tanweer, S. (2023). AI for sustainable smart city healthcare. China Petroleum Processing and Petrochemical Technology Catalyst Research, 23(2), 2245–2258.

Ansari, A. A., Narain, L., Prasad, S. N., & Alam, M. (2022). Behaviour of motion of infinitesimal variable mass oblate body in the generalized perturbed circular restricted three-body problem. Italian Journal of Pure and Applied Mathematics, 47, 221–239.

Alam, M., Parveen, S. (2021). Shipment delivery and COVID-19: An Indian context. International Journal of Advanced Engineering Research and Science, 8(8), 145–154.

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

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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.

Dr. Ananthoju Vijay Kumar | Artificial Intelligence | Best Researcher Award

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Dr. Ananthoju Vijay Kumar | Artificial Intelligence | Best Researcher Award

Associate Professor | Jain Deemed to be University | India

Dr. Ananthoju Vijay Kumar is an accomplished academician and researcher currently serving as an Associate Professor in the Department of Computer Science and Engineering at Jain University, Bangalore. With nearly two decades of dedicated teaching and research experience, he has established himself as a recognized guide and mentor, supervising multiple doctoral candidates. His expertise spans across Cyber Security, Data Mining, Data Warehousing, Data Science, and Natural Language Processing. Dr. Kumar has made significant contributions to his field through impactful research collaborations, scholarly publications, and active participation in professional academic communities.

Publication Profile

Scopus

ORCID

Google Scholar

Education Background

Dr. Ananthoju Vijay Kumar pursued his doctoral studies in Computer Science and Engineering at Acharya Nagarjuna University, where he developed a strong foundation in computational theories and advanced research methodologies. His education provided him with specialized knowledge in core computer science disciplines and helped him build a research-oriented outlook. This academic journey laid the groundwork for his professional career in both teaching and research, equipping him to mentor students and lead projects across multiple domains. His academic credentials reflect his deep engagement in the field and his commitment to advancing the boundaries of computer science education and innovation.

Professional Experience

Dr. Ananthoju Vijay Kumar has held several important academic positions during his career, shaping his path as a teacher, researcher, and guide. Prior to joining Jain University as an Associate Professor, he served in Sree Chaitanya College of Engineering in Telangana, where he contributed to academic growth and program development in computer applications. At Jain University, he continues to lead both undergraduate and postgraduate courses, while simultaneously mentoring doctoral candidates. His ongoing research includes international collaborations, such as a major project with Melbourne University, Australia, further reflecting his active contribution to the global research community.

Awards and Honors

Throughout his career, Dr. Ananthoju Vijay Kumar has been recognized for his excellence in teaching, research, and academic leadership. Notably, he was honored with the APJ Abdul Kalam Lifetime Achievement National Award, presented by the International Institute of Socio Economic Reforms in Bangalore. This recognition underscores his significant contributions to the academic and research ecosystem. His role as a recognized doctoral guide at Jain University further highlights his influence and dedication to nurturing future researchers. His academic and professional achievements stand as a testament to his dedication to advancing knowledge and societal progress through impactful research and mentorship.

Research Focus

Dr. Ananthoju Vijay Kumar’s primary research interests encompass a wide range of areas within computer science. His focus extends across Cyber Security, Data Mining, Data Warehousing, Data Science, and Natural Language Processing. He has successfully guided research scholars in emerging domains such as agricultural data mining and advanced applications of security systems. His collaboration with international institutions has allowed him to address interdisciplinary challenges and deliver innovative solutions. With more than forty publications in reputed national and international journals, he continues to explore cutting-edge topics while contributing to both academic literature and practical applications of technology.

Publication Notes

  • Enhancing drug discovery and patient care through advanced analytics with the power of NLP and machine learning in pharmaceutical data interpretation
    Published Year: 2025
    Citation: 5

  • Investigating the Determinants of Indian Rupee Exchange Rate: An Empirical Analysis of Influential Factors and Their Impact Level: Part 1
    Published Year: 2024
    Citation: 1

  • A Personalized System to Recommend a Healthy Diet Based on an Individual’s Unique Dietary Needs and Goals
    Published Year: 2023
    Citation: 2

  • Penetration Testing to Investigate Security Vulnerabilities, Bugs and Potential Threats in Flip Kart, JioMart, and Amazon Mobile Application
    Published Year: 2023
    Citation: 1

  • Hybrid Algorithm for Real-Time Sign Language Detection System
    Published Year: 2023
    Citation: 5

Conclusion

In summary, Dr. Ananthoju Vijay Kumar stands out as a distinguished academician with a strong record of teaching, mentoring, and impactful research. His academic background, professional experience, and recognized contributions to the field of computer science demonstrate his commitment to innovation and academic growth. His awards and ongoing projects highlight his active role in both national and international research communities. Through his expertise and dedication, Dr. Kumar continues to inspire students and researchers while making meaningful contributions to technology and society.

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

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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.

Publication Profile

ORCID

🎓 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.

📚 Top Publication Note

Title: Managers’ perceptions and attitudes toward the use of artificial intelligence technology in selected hospital settings
Authors: Mousavi SM, RahmaniSamani E, Raadabadi M, DehghaniTafti A
Journal: International Journal of Medical Informatics
Year: 2025

Assist. Prof. Dr. Yuchae Jung | Generative AI | Distinguished Scientist Award

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Assist. Prof. Dr. Yuchae Jung | Generative AI | Distinguished Scientist Award

Assist. Prof. Dr. Yuchae Jung, Open Cyber University of Korea , South Korea.

Dr. Yuchae Jung is an accomplished Affiliated Professor at KAIST School of Computing, Seoul, South Korea. With an interdisciplinary background spanning computer science, medical sciences, and artificial intelligence, she brings a unique integration of biomedical knowledge and computational innovation to her research. Over the years, Dr. Jung has held key academic and research roles in prestigious institutions, including Harvard Medical School and State University of New York. Her professional journey reflects a strong commitment to advancing digital healthcare, AI-driven diagnostics, and computational biology. 🧠💻🧬

Professional Profile

Google Scholar

🎓 Education Background

Dr. Jung earned her Ph.D. and M.S. in Medical Science from The Catholic University of Korea (2008, 2002), following her undergraduate degree in Computer Science from Sookmyung Women’s University in 2000. This solid academic foundation has enabled her to contribute innovatively to both computer science and medical informatics. 🎓📚

🧪 Professional Experience

Dr. Jung is currently affiliated with KAIST’s School of Computing as a professor. She has previously held significant roles at The Catholic University of Korea, Boin IT, Seoul National University, and Sookmyung Women’s University. She has also conducted postdoctoral research at Brigham & Women’s Hospital (Harvard Medical School) and State University of New York. Her professional engagements include lectures, research leadership, and AI-based system development across medical and computing fields. 🏥🖥️📊

🏅 Awards and Honors

Dr. Jung has been the Principal Investigator of several prestigious grants from organizations such as the Ministry of SMEs and Startups, National Library of Korea, Ministry of Science, and Ministry of Education. Her projects span from NLP-based clinical dialogue systems to cancer therapy algorithms and bioinformatics applications in glioblastoma research. She was also honored as a keynote speaker by The Korean Society of Pathologists. 🏆📜🇰🇷

🔬 Research Focus

Her core research interests lie in Medical AI, including deep transfer learning for digital pathology image analysis, clinical Natural Language Processing (Bio-NLP), and cancer genomics (TFs, repeat sequences, miRNAs). She also explores gene expression network analysis in cancer and functional informatics for precision diagnostics. Her work bridges cutting-edge AI with real-world healthcare applications. 🧬🤖📈

✅ Conclusion

Dr. Yuchae Jung is a pioneering figure in interdisciplinary AI and bioinformatics, contributing impactful research to cancer genomics and healthcare AI. With a dynamic academic trajectory and a clear focus on translational science, she continues to be a driving force in computational medicine and smart health systems. Her extensive contributions position her as a deserving candidate for recognition in digital healthcare innovation. 🌐💡👩‍⚕️

📝 Top Publications Highlights

  1. Classification of Diffuse Glioma Subtype from Clinical-Grade Pathological Images Using Deep Transfer Learning
    📅 Published: 2021 in MDPI Sensors
    📊 Cited by: 39 articles (Google Scholar)
    🔍 A groundbreaking study applying deep transfer learning for pathology image classification.

  2. Impact of tumor purity on immune gene expression and clustering analyses across multiple cancer types
    📅 Published: 2018 in Cancer Immunology Research
    📊 Cited by: 107 articles
    🔬 Investigates how tumor purity affects gene expression in cancer immunology.

  3. Hybrid-Aware Model for Senior Wellness Service in Smart Home
    📅 Published: 2017 in MDPI Sensors
    📊 Cited by: 25 articles
    🏡 Explores smart health monitoring using a hybrid AI model in smart homes.

  4. Aneuploidy meets network analysis: leveraging copy number alterations
    📅 Published: 2017 in Translational Cancer Research
    📊 Cited by: 15 articles
    🧬 Integrates systems biology with cancer genomics.

  5. Cancer stem cell targeting: Are we there yet?
    📅 Published: 2015 in Archives of Pharmacal Research
    📊 Cited by: 55 articles
    💡 Reviews strategies to target elusive cancer stem cells.

  6. Systemic approaches identify Z-ajoene as a GBM stem cell-specific targeting agent
    📅 Published: 2014 in Molecules and Cells
    📊 Cited by: 40+ articles
    🧪 Identifies garlic-derived compound with anti-glioblastoma activity.

  7. Numb regulates glioma stem cell fate and growth
    📅 Published: 2012 in Stem Cells
    📊 Cited by: 100+ articles
    📈 A critical study in stem cell regulation in glioma.

  8. GEAR: Genomic Enrichment Analysis of Regional DNA Copy Number Changes
    📅 Published: 2008 in Bioinformatics
    📊 Cited by: 80+ articles
    🧬 Proposes a novel method for regional DNA copy number analysis.

  9. DNA methylation patterns of ulcer-healing genes in gastric cancers
    📅 Published: 2010 in Journal of Korean Medical Science
    📊 Cited by: 35 articles
    🔬 Connects epigenetics with cancer pathology.

  10. PathCluster: a framework for gene set-based hierarchical clustering
    📅 Published: 2008 in Bioinformatics
    📊 Cited by: 90+ articles
    📂 Presents a tool widely adopted in gene expression analysis.