Moumita Mukherjee | Machine Learning and Statistics | Best Researcher Award

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Dr. Moumita Mukherjee | Machine Learning and Statistics | Best Researcher Award

Charite-University Medicine Berlin | Germany

Dr. Moumita Mukherjee is an accomplished health economist and digital health researcher with expertise in health systems research, machine learning applications in healthcare, and interdisciplinary teaching. She holds a PhD in Economics from the University of Calcutta, an MBA in Entrepreneurship, Innovation and Project Development from International Telematic University, and an MSc in Data Science from the University of Europe for Applied Sciences, Germany. Her professional experience spans both academic and applied research environments, including positions at Charite-University Medicine Berlin, the Indian Institute of Public Health in Shillong, and the Berlin School of Business and Innovation. She has contributed extensively to global health research focusing on digital transformation, equity in healthcare access, and the use of data-driven methods for improving health outcomes. Her body of work includes numerous peer-reviewed publications in leading journals such as Scientific Reports, Journal of Health, Population and Nutrition, Journal of Health Management, and International Journal for Equity in Health, as well as book chapters and authored volumes addressing child health, nutrition, and health equity. In her current role at Charite-University Medicine Berlin, she lectures on digital health and artificial intelligence, supervises master’s theses, and mentors students. With advanced technical proficiency in Python, STATA, and NVivo, she applies econometric, machine learning, and deep learning models to address complex public health and policy questions. Her interdisciplinary approach integrates health economics, digital innovation, and policy analysis to support equitable and sustainable health systems worldwide. Through her research, teaching, and mentorship, Dr. Moumita Mukherjee continues to bridge data science and health economics to shape the future of evidence-based global health policy and digital healthcare transformation.

Profiles: Google Scholar | Orcid

Featured Publications

Kiran Sree Pokkuluri | Machine Learning and Statistics | Excellence in Research Award

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Prof. Dr. Kiran Sree Pokkuluri | Machine Learning and Statistics | Excellence in Research Award

Shri Vishnu Engineering College For Women | India

Prof. Dr. Kiran Sree Pokkuluri is a distinguished academician, researcher, and innovator in the field of Artificial Intelligence and Machine Learning with an illustrious career of academic and research excellence. Currently serving as Professor and Head of the Department of Computer Science and Engineering at Shri Vishnu Engineering College for Women, he has significantly contributed to advancing computational intelligence and data-driven innovation in academia and industry. He holds a Ph.D. in Artificial Intelligence from JNTU-Hyderabad and has an impressive scholarly record with over 100 research publications in reputed SCI and Scopus-indexed journals, a citation count exceeding 653, an h-index above 13, and an Documents exceeding 152, reflecting the global impact of his research. His research areas include Deep Learning, Healthcare Analytics, Bioinformatics, IoT Power Optimization, Big Data Analytics, and Cloud Computing. Dr. Sree has authored six textbooks with ISBNs on Artificial Intelligence, Machine Learning, and Deep Learning, and has filed and published six patents in the domains of AI and intelligent systems. His innovations such as the Hybrid Deep Neural ZF Network (HDNZF-Net) have set new benchmarks in real-time speech enhancement for speech-impaired individuals and IoT optimization. He has completed five major funded projects and collaborated with premier institutions including Stanford University through the UIF program, fostering cross-disciplinary innovation. A recognized thought leader, Dr. Sree serves as Editor-in-Chief, editorial board member, and reviewer for multiple international journals. His remarkable achievements have earned him prestigious recognitions like the Bharat Excellence Award and Rashtriya Ratan Award, and he has been featured in Marquis Who’s Who in the World. As Global Vice President of the World Statistical Data Analysis Research Association (WSA) and a member of professional bodies such as IEEE, ISTE, CSI, and IAENG, Dr. Kiran Sree continues to inspire excellence in AI-driven research, education, and technological innovation.

Profiles: Scopus | Google Scholar | Orcid

Featured Publications

Venkatachalam, B., Pokkuluri, K. S., Suguna Kumar, S., Dhandapani, A., & Bhonsle, M. (2025). Adaptive fuzzy heuristic algorithm for dynamic data mining in IoT integrated big data environments. Journal of Fuzzy Extension and Applications, 6(3), 615–636.

Pokkuluri, K. S., Sarkar, P., Birchha, V., Mathariya, S. K., Veeramachaneni, V., & others. (2025). Intelligent reasonable optimization for virtual machine provisioning in hybrid cloud using fuzzy AHP and cost-effective autoscaling. SN Computer Science, 6(7), 1–15.

Sivanuja, M., Raju, P. J. R. S., Prasad, M., RR, P. B. V., Kumar, K. S., & Pokkuluri, K. S,. (2025). A novel ensemble-based deep learning framework combining CNN and transfer learning models for enhanced wildfire detection. In Proceedings of the 2025 International Conference on Computational Robotics, Testing and Applications.

Alzubi, J. A., Pokkuluri, K. S., Arunachalam, R., Shukla, S. K., Venugopal, S., & others. (2025). A generative adversarial network-based accurate masked face recognition model using dual scale adaptive efficient attention network. Scientific Reports, 15(1), 17594.

Pokkuluri, K. S., Chandanan, A. K., Mishra, A. K., Jyothi, D., Lavanya, M. S. S. L., & others. (2025). Deep learning-enhanced intrusion detection and privacy preservation for IIoT networks. In Proceedings of the 2025 4th International Conference on Distributed Computing and Electrical Systems.

Ahmad Abuhani | Machine Learning and Statistics | Best Researcher Award

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Assist Prof. Dr. Ahmad Abuhani | Machine Learning and Statistics | Best Researcher Award

Middle East University | Jordan

Assist Prof. Dr. Ahmad Abuhani is an accomplished Assistant Professor of Interior Design at the Faculty of Engineering and Design, Middle East University, Amman, Jordan, known for his distinguished academic, artistic, and research achievements. He earned his B.Sc., M.Sc., and Ph.D. in Interior Design from the Moscow State University of Applied Arts named after S.G. Stroganov, Russia, where he specialized in interior composition, architectural planning, and the artistic formation of traditional Jordanian housing. His doctoral research, titled “The Construction System and Technical Composition of the Interior Design of the Jordanian Home,” demonstrates his dedication to blending cultural identity with modern design principles. Dr. Abu Hani has held several academic and administrative positions, including Head of the Interior Design Department at Middle East University, Amman University, and Yarmouk University. His teaching expertise covers a wide range of design areas such as architectural drawing, color theory, space planning, and professional practice. His scholarly contributions include publications in international journals and conferences focusing on design aesthetics, visual communication, and creative methodology. His research interests span fine and applied arts, architectural design, descriptive geometry, and color theory. A member of the Fine Artists Association (Amman) and the International Council of Societies of Industrial Design (ICSID), he also serves as a reviewer for Horizon Research Publishing and participates in multiple academic committees and juries. Dr. Abu Hani has exhibited his work in 15 personal and 9 collective exhibitions across Jordan and Russia, receiving prestigious awards including first place in national art competitions and recognition from the Ministry of Culture, Dr. Abu Hani continues to make impactful contributions to the fields of interior design, applied arts, and creative education, combining innovation with cultural and academic excellence.

Profiles: Orcid |  Google Scholar 

Oleg Selyugin | Big Data and Statistical Analytics | Big Data Analytics Award

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Dr. Oleg Selyugin | Big Data and Statistical Analytics | Big Data Analytics Award

Joint Institute for Nuclear Research | Russia

Dr. Oleg Selyugin is a Russian empirical and theoretical physicist with a distinguished career in high-energy hadron scattering and the structure of hadrons. After completing his studies at the Physics Department of Moscow State University, he joined the Joint Institute for Nuclear Research (JINR), first as a probationer and researcher at the Laboratory of Nuclear Problems, and later at the Bogoliubov Theoretical Laboratory (BTL), where he now serves as a leading scientist. At BTL, he earned his Ph.D. with the thesis “High energy elastic hadron-hadron scattering in a wide momentum transfer region,” and later obtained his Doctor of Physics and Mathematics degree with the thesis “The structure of high-energy amplitude of the elastic hadron-hadron scattering in the diffraction region.” Dr Selyugin has been recognized with multiple International Prizes of JINR for his outstanding contributions to polaron physics, hadron physics, and high-energy physics. His primary research interests include the structure of hadrons (PDFs, GPDs, form-factors), phenomenology of high-energy physics (differential cross sections, spin phenomena), models of extra dimensions (d-brane gravity), and nonlinear effects. He has been actively involved in interpreting experimental results from the CERN LHC, particularly the TOTEM and ATLAS Collaborations. His theoretical work integrates electromagnetic and gravitational form-factors derived from novel t-dependent GPDs, as well as soft and cross-even pomeron contributions, within dispersion-relation-based frameworks. With over 180 scientific papers, Dr Selyugin has made a profound and lasting impact on the understanding of elastic hadron scattering at high energies. Although specific bibliometric indicators such as 17 h-index, 78 documents, and 815 citations vary across databases, his scientific influence is widely recognized within the international physics community. He continues his pioneering research at JINR in Dubna, Russia.

Profiles: Scopus | Orcid

Featured Publications

Selyugin, O. V. (2024). Unified description of elastic hadron scattering at low and high energies. Physics of Atomic Nuclei, 87(S2), S349–S362.