Anjan Kumar reddy Ayyadapu | Team Building and Team Management | Best Researcher Award

Published on by Leadership and Management

Mr. Anjan Kumar reddy Ayyadapu | Team Building and Team Management | Best Researcher Award

Cloudera | United States

Anjan Kumar Reddy Ayyadapu focuses on advanced data engineering, distributed systems, and big data analytics. His work emphasizes scalable data platforms, cloud-based architectures, and real-time data processing frameworks. His research interests include data warehousing, machine learning integration, and performance optimization in large-scale systems. He has contributed to designing efficient data pipelines and improving data reliability across enterprise environments. His expertise also extends to Hadoop ecosystems and modern data infrastructure. His contributions support innovation in data-driven decision-making, enabling organizations to process, analyze, and derive insights from complex and high-volume datasets efficiently.

                  Citation Metrics (Google Scholar)

100
80
60
40
20
0

Citations
73

Documents
20

h-index
5

Citations

Documents

h-index

View Google Scholar

Featured Publications


Fuzzy Logic and Machine Learning Hybrid Model for Influencing Consumer Purchasing Behavior in E-Commerce

– International Conference on Computing Technologies & Data Communication, 2025

Deep Learning Models for Predictive Maintenance in Industrial IoT with Big Data Support

– FMDB Transactions on Sustainable Intelligent Networks, 2025

Ms. Shaguna Gupta | Cloud Computing Computer Science Research | Best Researcher Award

Published on by Leadership and Management

Ms. Shaguna Gupta | Cloud Computing Computer Science Research | Best Researcher Award

National College of Ireland | Ireland

Shaguna Gupta is a dedicated computer science researcher specializing in cloud computing, distributed systems, and intelligent transportation systems. She is currently pursuing her Ph.D. at Trinity College Dublin (TCD), Ireland, focusing on highway traffic flow optimization using deep reinforcement learning to improve traffic throughput and travel time reliability. She holds a Master of Technology in Cloud Computing with Queuing Theory from Shri Mata Vaishno Devi University (SMVDU), India, and a Bachelor of Engineering from Jammu University, India. Her research experience spans multiple international institutions, including a postgraduate studentship under Science Foundation Ireland’s CRT ADVANCE project, a research internship at the University of Virginia, USA, and project work at the Indian Institute of Science, Bangalore. She has contributed to multiple publications in areas such as rideshare optimization, queuing theory for cloud services, and microservice resilience. As an educator, she has served as an associate faculty member, demonstrator, and lecturer, supervising cloud computing projects and teaching modules on AI, programming, and cybersecurity. Her research interests include cloud computing, traffic management, multi-agent reinforcement learning, and distributed systems. She has received several academic awards, including gold medals, scholarships, and best paper presentations. Committed to advancing technology for societal benefit, she actively participates in workshops, conferences, and community outreach, reflecting a balance of innovation, leadership, and practical impact.

Profile:  Google Scholar 

Featured Publications

Gupta, S., Narang, R., Krishnaswami, K., & Yadav, S. (1994). Plasma selenium level in cancer patients. Indian Journal of Cancer, 31(3), 192–197.

Fusco, V. F., Sancheti, S., & Gupta, S. (1994). Active antenna element design issues. IEE Colloquium on Smart Antennas (Digest No: 1994/182), 9/1–9/7.

Gupta, S., & Fusco, V. F. (1996). Low cross-polarized integrated mixer/phase shifter patch antenna for beamforming applications. 26th European Microwave Conference, 1, 397–400.

Gupta, S., & Pourush, R. K. S. (1999). Technical Notes-4 x 4 planar phased array of circular patch microstrip antenna in plasma environment for on-board applications. Space Technology-Abingdon, 19(2), 97–108.

Gupta, S., Fusco, V. F., & Sancheti, S. (1999). Self-phased re-transmitting integrated mixer antenna array. International Journal of Electronics, 86(2), 207–215.

Gupta, S., Narang, R., & Patel, M. K., Gupta, K., Kumar, K. (2025). Enhanced ECC-driven text encryption scheme using chaotic maps and Rhotrices. Palestine Journal of Mathematics, 14(3).

Gupta, S., & Arora, S. (2018). Queueing system in cloud services management: a survey. International Journal of Pure and Applied Mathematics, 119(12), 12741–12753.

Shaikh, R. (2025). Prediction of resource utilization in cloud computing using machine learning. Dublin, National College of Ireland.

Dr. Uma Jothi | Team Building and Team Management | Excellence in Research

Published on by Leadership and Management

Dr. Uma Jothi | Team Building and Team Management | Excellence in Research

Amrita University, India

Dr. J. Uma is an accomplished academic and researcher in the fields of information technology, cloud computing, artificial intelligence, and cybersecurity. She holds a B.Tech in Information Technology, an M.E. in Computer Science and Engineering with distinction, and has submitted her Ph.D. thesis in Information and Communication Engineering at Anna University. With more than twelve years of academic experience, she has served as Assistant Professor in leading engineering institutions, contributing significantly to teaching, curriculum development, and research mentorship. Her research focuses on cloud resource allocation, deep reinforcement learning, intelligent optimization algorithms, blockchain technologies, IoT-based systems, and data security. She has published impactful journal articles in reputed outlets like Transactions on Emerging Telecommunications Technologies and Springer’s Lecture Notes in Networks and Systems, along with several book chapters and conference papers. Her work includes innovations in heuristic optimization, adversarial defenses in deep learning, and smart healthcare IoMT solutions. She is also a published patent holder in IoT-based agriculture monitoring systems and employee training platforms. Dr. Uma has organized major AICTE- and RGNIYD-funded programs, contributing to national-level capacity building in data science, IoT, and smart city technologies. Her career reflects a strong commitment to advancing research, innovation, and academic excellence.

Profiles:  ORCID

Featured Publications

Assist. Prof. Dr. Anusuyah Subbarao | Digital Transformation | Research Excellence Award

Published on by Leadership and Management

Assist. Prof. Dr. Anusuyah Subbarao | Digital Transformation | Research Excellence Award

Multimedia University | Malaysia

Ts. Dr. Anusuyah Subbarao is an accomplished Assistant Professor with more than two decades of academic experience in Software Engineering, Computer Science, and Information Technology. She holds a PhD from Universiti Teknologi Malaysia, a Master of Science in Computer Science majoring in Software Engineering, and a Bachelor’s degree in Computer Science from Universiti Putra Malaysia. Her research interests span digital transformation, healthcare informatics, enterprise resource planning, cloud computing risks, global software development, qualitative methodologies, and digital literacy. Throughout her career, she has contributed extensively to research through journal articles, book chapters, and conference proceedings, earning numerous national and international awards for teaching, innovation, and research excellence. She has successfully secured internal and external research grants and served as a reviewer for high-impact journals. Her innovation projects have received multiple gold, silver, and bronze medals at prestigious exhibitions such as InventX and RICES. With strong expertise in digital health, social innovation, ERP adoption, and technology acceptance, she actively supports technological advancement and community empowerment through impactful research. Recognized for her dynamic communication skills and commitment to transformative education, she continues to inspire learners and professionals while advancing cutting-edge research in digital technologies.

Profiles:  ORCID

Featured Publications

Rahman, H. M. M., Islam, J., Malarvizhi, C. A. N., Khan, N., Subhan, K. M. A., & Subbarao, A. (2026). Women empowerment in war and nation building on the basis of Tahmima Anam’s trilogy. Salud, Ciencia y Tecnología.

Murugasu, U. S. G., & Subbarao, A. (2025). Empirical method for developing a hyper-personalization artifact. Engineering Applications of Artificial Intelligence.

Subbarao, A., Siddika, A., Fathullah, M. A., & Sanwani, M. A. B. (2025). The role of mobile applications in shaping digital transformation in higher education among Generation I: A bibliographic study. Information.

Tang, Y., Subbarao, A., & Aw, A. T. H. (2025). A critical review of Theory of Planned Behavior in knowledge payment. International Journal of Management, Finance and Accounting.

Subbarao, A., Khan, N., Siddika, A., Fathullah, M. A., Sanwani, M. A., Adam, F. F., Ferezagia, D. V., & Altamira, M. B. (2025). Digital transformation in higher education: Enhancing support services through mobile apps. HighTech and Innovation Journal.

Lee, A. T., Ramasamy, R. K., & Subbarao, A. (2025). Barriers to and facilitators of technology adoption in emergency departments: A comprehensive review. International Journal of Environmental Research and Public Health.

Abd Sukor, N. I., & Subbarao, A. (2025). Unveiling the pathways: Exploring influential factors shaping intentions to engage with ChatGPT. International Journal of Management, Finance and Accounting.

Lee, A. T., Ramasamy, R. K., & Subbarao, A. (2025). Barriers and facilitators of technology adoption in emergency departments: A comprehensive review [Preprint]. Preprints.

Lee, A. T., Ramasamy, R. K., & Subbarao, A. (2025). Understanding psychosocial barriers to healthcare technology adoption: A review of TAM technology acceptance model and unified theory of acceptance and use of technology (UTAUT) frameworks. Healthcare.

Lee, A. T., Ramasamy, R. K., & Subbarao, A. (2025). Understanding psychosocial barriers to healthcare technology adoption: A review of TAM and UTAUT frameworks [Preprint]. Preprints.

Khairuddin, I. K., & Subbarao, A. (2024). Examining the offline shopping preferences of millennial women: A comprehensive review. International Journal of Management, Finance and Accounting.

Assist. Prof. Dr. Christos Kakarougkas | Motivation and Employee Engagement | Strategic Business Management Award

Published on by Leadership and Management

Assist. Prof. Dr. Christos Kakarougkas | Motivation and Employee Engagement | Strategic Business Management Award

University of the Aegean | Greece

Christos S. Kakarougkas is an Assistant Professor specializing in Human Resource Management of Tourism Enterprises and Organizations. He holds a Doctoral Diploma from the University of the Aegean, where his research focused on the impact of reward systems on organizational culture change in Greek five-star hotels. He also earned a Master’s Degree in Hospitality Management from Thames Valley University and a Bachelor’s Degree in Tourism Business Management from ATEI Larisa. With extensive academic and professional experience, he has taught in undergraduate and postgraduate programs across Greek universities, including the University of the Aegean, University of West Attica, and Hellenic Open University, as well as international programs in collaboration with Metropolitan College and Queen Margaret University, Edinburgh. His teaching covers Human Resource Management, Strategic Management, Entrepreneurship, Global Booking Systems, and Hospitality Administration. Beyond teaching, he has supervised numerous graduate and postgraduate theses, developed vocational training curricula, and contributed to adult education programs in leadership, tourism management, and entrepreneurship. His research interests include organizational culture, human resource practices in tourism, and strategic management of hospitality enterprises. He has been recognized for his scholarly contributions and active engagement in educational innovation. Christos continues to advance knowledge in tourism management while fostering excellence in academic and professional development.

Profiles:  Google Scholar 

Featured Publications

Katsoni, V., Upadhya, A., & Stratigea, A. (2017). Tourism, culture and heritage in a smart economy. Springer Proceedings in Business and Economics, 38.

Stavrinoudis, T., & Kakarougkas, C. (2017). A theoretical model of weighting and evaluating the elements defining the change of organizational culture. In Tourism, culture and heritage in a smart economy: Third International Conference (pp. xx–xx).

Stavrinoudis, T., & Kakarougkas, C. (2017). Factors of human motivation in organizations: A first scientific modeling for a more effective application in the hospitality industry. International Journal of Cultural and Digital Tourism, 4(2), 20–30. https://doi.org/xxxx

Stavrinoudis, T., Kakarougkas, C., & Vitzilaiou, C. (2022). Hotel front line employees’ perceptions on leadership and workplace motivation in times of crisis. Tourism and Hospitality Management, 28(2), 257–276. https://doi.org/xxxx

Kakarougkas, C., & Stavrinoudis, T. (2021). COVID-19 impact on the human aspect of organizational culture and learning: The case of the Greek hospitality industry. In Organizational learning in tourism and hospitality crisis management (Vol. 8, pp. 49–xx).

Kakarougkas, C., & Stavrinoudis, T., & Psimoulis, M. (2023). Evaluating the COVID-19 pandemic changes on hotel organizational culture. Journal of Global Business Insights, 8(1), 80–94. https://doi.org/xxxx

Kakarougkas, C., & Papageorgakis, E. (2023). Evaluating the effectiveness of training methods on the performance of human resources in Greek hotel businesses. Journal of Advances in Humanities Research, 4863, 11–xx. https://doi.org/xxxx

Assoc. Prof. Dr. Surbhi Agrawal | Innovative Leadership | Research Excellence Award

Published on by Leadership and Management

Assoc. Prof. Dr. Surbhi Agrawal | Innovative Leadership | Research Excellence Award

RV Institute of Technology and Management, India

Profiles:  Google Scholar 

Featured Publications

Bora, K., Saha, S., Agrawal, S., Safonova, M., Routh, S., & Narasimhamurthy, A. (2016). Cd-hpf: New habitability score via data analytic modeling. Astronomy and Computing, 17, 129–143.

Saha, S., Basak, S., Safonova, M., Bora, K., Agrawal, S., Sarkar, P., & Murthy, J. (2018). Theoretical validation of potential habitability via analytical and boosted tree methods: An optimistic study on recently discovered exoplanets. Astronomy and Computing, 23, 141–150.

Agrawal, S., Basak, S., Mathur, A., Theophilus, A. J., Deshpande, G., & Murthy, J. (2021). Habitability classification of exoplanets: A machine learning insight. The European Physical Journal Special Topics, 230, 2221–2251.

Viquar, M., Basak, S., Dasgupta, A., Agrawal, S., & Saha, S. (2018). Machine learning in astronomy: A case study in quasar-star classification. In Emerging Technologies in Data Mining and Information Security (pp. xxx–xxx). (Publisher details not provided).

Basak, S., Saha, S., Mathur, A., Bora, K., Makhija, S., Safonova, M., & Agrawal, S. (2020). Ceesa meets machine learning: A constant elasticity earth similarity approach to habitability and classification of exoplanets. Astronomy and Computing, 30, 100335.

Naik, P., Agrawal, S., & Murthy, S. (2015). A survey on various task scheduling algorithms toward load balancing in public cloud. American Journal of Applied Mathematics, 3(1-2), 14–17.

Sarkar, J., Saha, S., & Agrawal, S. (2014). An efficient use of principal component analysis in workload characterization—a study. AASRI Procedia, 8, 68–74.

Saha, S., Agrawal, S., Bora, K., Routh, S., & Narasimhamurthy, A. (2015). ASTROMLSKIT: A new statistical machine learning toolkit: A platform for data analytics in astronomy. arXiv preprint arXiv:1504.07865.

Safonova, M., Mathur, A., Basak, S., Bora, K., & Agrawal, S. (2021). Quantifying the classification of exoplanets: In search for the right habitability metric. The European Physical Journal Special Topics, 230(10), 2207–2220.

Mr. Gabriel Amaizu | Charismatic Leadership | Best Researcher Award

Published on by Leadership and Management

Mr. Gabriel Amaizu | Charismatic Leadership | Best Researcher Award

Towson University | United States

Profile:  Google Scholar 

Featured Publications

Njoku, J. N., Nwakanma, C. I., Amaizu, G. C., & Kim, D. S. (2023).
Prospects and challenges of Metaverse application in data‐driven intelligent transportation systems. IET Intelligent Transport Systems, 17(1), 1–21.

Amaizu, G. C., Nwakanma, C. I., Bhardwaj, S., Lee, J. M., & Kim, D. S. (2021).
Composite and efficient DDoS attack detection framework for B5G networks. Computer Networks, 188, Article 107871.

Amaizu, G. C., Nwakanma, C. I., Lee, J. M., & Kim, D. S. (2020).
Investigating network intrusion detection datasets using machine learning. In Proceedings of the 2020 International Conference on Information and Communication Technology Convergence (ICTC). IEEE.
(Add page numbers if available.)

Sampedro, G. A. R., Agron, D. J. S., Amaizu, G. C., Kim, D. S., & Lee, J. M. (2022).
Design of an in-process quality monitoring strategy for FDM-type 3D printer using deep learning. Applied Sciences, 12(17), Article 8753.

Amaizu, G. C., Njoku, J. N., Lee, J. M., & Kim, D. S. (2024).
Metaverse in advanced manufacturing: Background, applications, limitations, open issues & future directions. ICT Express, 10(2), 233–255.

Dr. Kalpesh Popat | Computer Science | Best Researcher Award

Published on by Leadership and Management

Dr. Kalpesh Popat | Computer Science | Best Researcher Award

Marwadi University | India

Profile:  Google Scholar

Featured Publications

  • Wearable Computer Applications: A Future Perspective
    KA Popat, P Sharma
    International Journal of Engineering and Innovative Technology, 3(1), 213–217, 2013. (Citations: 52)

  • A Study of Routing Protocols for MANETs
    KA Popat, P Sharma, H Molia
    International Congress on Information and Communication Technology (ICICT), Springer Proceedings, 2016. (Citations: 7)

  • Comparative Analysis of Several Approaches of Encoding Audio Files
    LK Patil, KA Popat
    International Conference on Advancements in Smart Computing and Information Security, Springer, 2022. (Citations: 6)

  • Various Location Update Strategies in Mobile Computing
    K Popat, P Sharma
    International Journal of Computer Applications (IJCA), pp. 34–38, 2014. (Citations: 5)

  • A Study on Datasets, Risk Factors and Machine Learning Methods Associated with Alzheimer’s Disease
    V Gondalia, K Popat
    International Conference on Advancements in Smart Computing and Information Security, Springer, 2023. (Citations: 4)

Assoc. Prof. Dr. Ankit Chaudhary | Strategic Leadership | Best Researcher Award

Published on by Leadership and Management

Assoc. Prof. Dr. Ankit Chaudhary | Strategic Leadership | Best Researcher Award

Jawaharlal Nehru University | India

Profiles: Google Scholar | Scopus

Featured Publications

Raheja, J. L., Chaudhary, A., & Singal, K. (2011). Tracking of fingertips and centers of palm using KINECT. 2011 IEEE 3rd International Conference on Computational Intelligence, Modelling and Simulation (CIMSIM), 248–252.

Pandy, H., Chaudhary, A., & Mehrotra, D. (2014). A comparative review of approaches to prevent premature convergence in GA. Applied Soft Computing, 24, 1047–1077.

Chaudhary, A., Raheja, J. L., Das, K., & Raheja, S. (2011). Intelligent approaches to interact with machines using hand gesture recognition in natural way: A survey. International Journal of Computer Science and Engineering Survey (IJCSES), 2(1), 122–133.

Raheja, J. L., Kumar, S., & Chaudhary, A. (2013). Fabric defect detection based on GLCM and Gabor filter: A comparison. Optik, 124(23), 6469–6474.

Raheja, J. L., Mishra, A., & Chaudhary, A. (2016). Indian Sign Language recognition using SVM. Pattern Recognition and Image Analysis, 26(2), 434–441.

Dr. Hai Xue | Edge computing | Best Researcher Award

Published on by Leadership and Management

Dr. Hai Xue | Edge computing | Best Researcher Award

University of Shanghai for Science and Technology,

Profile

Google Scholar

🎓 Early Academic Pursuits

Dr. Hai Xue embarked on his academic journey in the field of computer engineering with a Bachelor of Science in Information and Communication Engineering from Konkuk University, Seoul, South Korea, in 2014. Driven by an insatiable curiosity for software and computing, he pursued his Master’s degree at Hanyang University, Seoul, where he specialized in Computer and Software under the guidance of Prof. Inwhee Joe. This period was crucial in shaping his foundational knowledge and research skills, which later fueled his contributions to edge computing and network science. Dr. Xue culminated his formal education with a Ph.D. in Computer Engineering from Sungkyunkwan University, Suwon, in 2020, where he worked under the mentorship of Prof. Hee Yong Youn. His doctoral research laid the groundwork for his future breakthroughs in dynamic resource allocation and federated learning.

🌟 Professional Endeavors

Dr. Xue’s professional career is marked by a series of prestigious positions that reflect his growing influence in the field of computer engineering. After earning his Ph.D., he served as a Research Professor at Korea University, Seoul, from September 2020 to September 2021. During this tenure, he collaborated with renowned researcher Prof. Sangheon Pack, contributing significantly to the domains of edge computing and network optimization. In September 2021, he transitioned to his current role as an Assistant Professor at the University of Shanghai for Science and Technology (USST), Shanghai, China. Here, he continues to engage in high-impact research, mentoring young scholars, and advancing cutting-edge technological solutions.

🔮 Contributions and Research Focus

Dr. Xue’s research interests are deeply rooted in dynamic resource allocation, federated learning, and edge computing. His contributions have led to substantial advancements in these areas, including:

  • Dynamic Pricing in Edge Offloading: His recent work on dynamic pricing-based near-optimal resource allocation is set to redefine how computational resources are distributed efficiently across networks.
  • Energy Harvesting in Edge Computing: His paper on dynamic differential pricing-based edge offloading systems with energy harvesting devices has been accepted by IEEE Transactions on Network Science and Engineering, highlighting his expertise in sustainable and energy-efficient computing.
  • Federated Learning Incentive Mechanisms: His study on Yardstick-Stackelberg pricing-based incentive mechanisms for federated learning in edge computing, accepted by Computer Networks, sheds light on optimizing collaborative learning models.
  • Neural Network Optimization: His work on dynamic pseudo-mean mixed-precision quantization (DPQ) for pruned neural networks, published in Machine Learning, underscores his ability to push the boundaries of artificial intelligence efficiency.

🏆 Accolades and Recognition

Dr. Xue’s contributions have not gone unnoticed. His publications in high-impact journals such as IEEE Transactions, Computer Networks, and Machine Learning underscore his academic excellence. His research has been classified under prestigious rankings, including CAS Q2 and JCR Q1, affirming its significance within the scientific community. These accolades reflect his unwavering commitment to innovation and the quality of his scholarly output.

🌐 Impact and Influence

Dr. Xue’s research has far-reaching implications in both academia and industry. His work in dynamic pricing mechanisms is influencing how network providers optimize their resource allocation, while his advancements in federated learning are paving the way for more secure and efficient decentralized AI applications. His insights into energy harvesting in edge computing hold promise for sustainable technological solutions, a pressing need in today’s energy-conscious world.

🌟 Legacy and Future Contributions

Looking ahead, Dr. Xue is poised to make even more significant contributions to computer engineering. His ongoing projects aim to refine the synergy between AI and edge computing, ensuring smarter, more adaptive network solutions. As an educator, he remains dedicated to nurturing the next generation of computing professionals, equipping them with the knowledge and skills necessary to tackle future challenges in technology.

📝Notable Publications

Dynamic load balancing of software-defined networking based on genetic-ant colony optimization

Author(s): H. Xue, K.T. Kim, H.Y. Youn
Journal: Sensors
Year: 2019

 Detection of falls with smartphone using machine learning technique

Author(s): X. Chen, H. Xue, M. Kim, C. Wang, H.Y. Youn
Journal: 2019 8th International Congress on Advanced Applied Informatics (IIAI-AAI)
Year: 2019

Packet Scheduling for Multiple‐Switch Software‐Defined Networking in Edge Computing Environment

Author(s): H. Xue, K.T. Kim, H.Y. Youn
Journal: Wireless Communications and Mobile Computing
Year: 2018

 Dynamic pricing based near-optimal resource allocation for elastic edge offloading

Author(s): Y. Xia, H. Xue, D. Zhang, S. Mumtaz, X. Xu, J.J.P.C. Rodrigues
Journal: arXiv preprint arXiv:2409.18977
Year: 2024

DPQ: dynamic pseudo-mean mixed-precision quantization for pruned neural network

Author(s): S. Pei, J. Wang, B. Zhang, W. Qin, H. Xue, X. Ye, M. Chen
Journal: Machine Learning
Year: 2024