Bhupesh Lonkar | Mobile Computing | Best Researcher Award

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Dr. Bhupesh Lonkar | Mobile Computing | Best Researcher Award

Assistant Professor | Cummins College of Engineering for Women, Nagpur| India

Dr. Bhupesh B. Lonkar has built a strong research profile in wireless sensor networks, Internet of Things, energy-aware communication, and artificial intelligence-driven optimization techniques. His work emphasizes the design and implementation of intelligent systems that integrate wireless communication, clustering algorithms, and sustainable energy management for practical applications in smart environments. Research contributions include smart home automation, IoT-based control systems, bioinspired clustering models for energy-efficient networks, RFID-based monitoring systems, and advanced routing protocols for wireless communication. These studies are published in reputed international journals and conferences of IEEE, Elsevier, and Springer, showing both academic quality and application-driven outcomes. The research explores challenges such as minimizing energy consumption, enhancing scalability, improving routing efficiency, and designing secure communication frameworks that align with the growing needs of modern IoT and wireless networks. His investigations also include water purification monitoring systems, automatic challan generation using GPS and GSM, and advancements on LEACH protocols, which reflect an interdisciplinary approach connecting computer science, communication engineering, and applied physics. Through active participation in conferences, editorial roles, and journal reviewing, Dr. Lonkar has contributed significantly to the research community while mentoring students on applied projects and emerging technologies. His focus remains on creating sustainable, intelligent, and energy-aware solutions that address both theoretical challenges and societal demands, positioning his research at the intersection of innovation and utility. The body of work demonstrates a balance between technical rigor and practical application, contributing to advances in machine learning models for energy optimization and secure IoT applications. Overall, the research activities of Dr. Bhupesh B. Lonkar have strengthened the knowledge base of next-generation communication systems and their applications in real-world environments. 18 Citations 9 Documents 2 h-index View h-index button is disabled in preview mode

Profile: Google Scholar | Scopus | ORCID
Featured Publication

Lonkar, B. B., Kuthe, A., Shrivastava, R., & Charde, P. (2020). Design and implement smart home appliances controller using IoT. International Conference on Information Systems and Management Science, 105–117. Cited by 13

Lonkar, B. B., & Karmore, S. (2024). BCEWN: Design of a hybrid bioinspired clustering model for deployment of energy-aware wireless networks. Wireless Personal Communications, 136(4), 2329–2358. Cited by 5

Charde, P., & Lonkar, B. B. (2023). An empirical review of machine learning models for energy optimizations in IoT networks. In Proceedings of the 14th International Conference on Computing Communication and Networking (pp. xx–xx). IEEE. Cited by 5

Lonkar, B. B., Sayankar, M. R., & Charde, P. D. (2018). Design and monitor smart automatic challan generation based on RFID using GPS and GSM. In Proceedings of the 3rd International Conference on Advances in Internet of Things (pp. xx–xx). IEEE. Cited by 5

Lonkar, B. B., & Karmore, S. (2022). Recent advancements on energy-saving LEACH protocol in wireless sensor network. In International Conference on Security, Privacy and Data Analytics (pp. 1–16). Springer. Cited by 3

Lonkar, B., & Karmore, S. (2022). Statistical evaluation of power-aware routing protocols for wireless networks: An empirical study. International Journal of Intelligent Information Technologies, 18(3), xx–xx. Cited by 3

Lonkar, B. B., Nakhate, R. T., & Sayankar, M. R. (2018). Smart automatic control and monitor water purification using wireless sensor system. In Proceedings of the First International Conference on Secure Cyber Computing and Communication (pp. xx–xx). IEEE. Cited by 3

Ye Tao | Machine Learning | Best Researcher Award

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Dr. Ye Tao | Machine Learning | Best Researcher Award

PhD Student | China University of Petroleum, Beijing| China

Dr Ye Tao is a dedicated researcher focusing on sedimentology, unconventional oil and gas exploration, and the integration of artificial intelligence into geological studies. His work emphasizes fine characterization and sweet spot evaluation of shale gas reservoirs, tectonic evolution, sedimentary system reconstruction, and deepwater hydrocarbon accumulation models. Ye Tao has served as principal investigator and key researcher on multiple funded projects, including studies on shale reservoir heterogeneity in the Wufeng–Longmaxi Formations, tectonic evolution of the North Uscult Basin, and migration and accumulation mechanisms in the Guyana Basin. His expertise spans seismic data interpretation, fracture classification, mechanical modeling, and stress field simulation, contributing to accurate prediction of reservoir sweet spots and caprock sealing capacity. Ye Tao has actively published in peer-reviewed journals, presenting significant contributions such as deep learning-aided shale reservoir analysis, isotope-based sea-level reconstructions, and machine learning-based carbonate fossil recognition. His interdisciplinary approach bridges geology with computer vision and artificial intelligence, providing innovative methodologies for improving exploration accuracy. Ye Tao has been awarded multiple national and institutional prizes, including first prizes at China University of Petroleum’s Graduate Academic Forum and the National Doctoral Student Academic Forum, showcasing his academic excellence and leadership. His skillset includes seismic processing, petrographic thin section analysis, carbon and oxygen isotope testing, and restoration of paleoenvironments, enabling comprehensive understanding of sedimentary processes. By applying deep learning techniques to geological data, Ye Tao is contributing to next-generation exploration strategies that enhance prediction of hydrocarbon distribution and optimize resource development. His work demonstrates strong potential for advancing both theoretical sedimentology and applied petroleum exploration, making significant impact on energy resource evaluation and development strategies in complex geological settings.

Profile:  ORCID
Featured Publication

Tao, Y., Bao, Z., & Ma, F. (2025). Analyzing key controlling factors of shale reservoir heterogeneity in “thin” stratigraphic settings: A deep learning-aided case study of the Wufeng-Longmaxi Formations, Fuyan Syncline, Northern Guizhou. Applied Computing and Geosciences, 100293.

Tao, Y., Bao, Z., Yu, J., & Li, Y. (2025). The petrophysical characteristics and controlling factors of the Wufeng Formation–Longmaxi Formation shale reservoirs in the Fuyan Syncline, Northern Guizhou. Geological Journal.

Tao, Y., Gao, D., He, Y., Ngia, N. R., Wang, M., Sun, C., Huang, X., & Wu, J. (2023). Carbon and oxygen isotopes of the Lianglitage Formation in the Tazhong area, Tarim Basin: Implications for sea-level changes and palaeomarine conditions. Geological Journal, 58, 967–980.

Tao, Y., He, Y., Zhao, Z., Wu, D., & Deng, Q. (2023). Sealing of oil-gas reservoir caprock: Destruction of shale caprock by micro-fractures. Frontiers in Earth Science, 10, 1065875.

Sultan Aldırmaz Colak | Privacy Protection | Best Researcher Award

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Assoc. Prof. Dr. Sultan Aldırmaz Colak | Privacy Protection | Best Researcher Award

Associate Professor| Kocaeli University| Turkey

Assoc. Prof. Dr. Sultan Aldırmaz Çolak has established an influential research career in applied mathematics, with particular emphasis on fractional calculus, functional analysis, operator theory, q-calculus, inequalities, optimization techniques, and mathematical modeling. The work integrates both theoretical and applied perspectives, contributing to the development of new mathematical structures and analytical approaches. A strong research presence is visible in fractional differential equations, fractional inequalities, and variational principles, where innovative methodologies are applied to solve complex problems in pure and applied sciences. Contributions extend to fractional operators with general kernels, quantum calculus, approximation theory, fixed point theorems, and applications of conformable fractional derivatives, reflecting versatility in addressing modern mathematical challenges. Publications highlight advances in inequalities of Hermite–Hadamard type, generalizations of classical results, and connections between fractional calculus and convexity theory. Beyond core mathematics, research interests also include mathematical programming, optimization problems, and algorithmic approaches, establishing bridges with computer science and applied engineering. Engagement in international collaborations has broadened the reach of this research, demonstrated through joint works published in reputed journals across mathematical sciences. The scientific output emphasizes originality in both problem formulation and solution strategies, making significant contributions to ongoing discourse in advanced calculus and related domains. Focus areas like generalized convex functions, applications of Jensen’s inequality, integral transforms, and iterative methods for nonlinear operators position this work at the interface of analysis, computation, and modeling. Active participation in editorial roles and peer review further indicates a commitment to advancing the discipline. Overall, the research achievements of Assoc. Prof. Dr. Sultan Aldırmaz Çolak represent a consistent pursuit of mathematical innovation with practical relevance across interdisciplinary boundaries. 486 Citations 54 Documents 11

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Featured Publication

Authors unavailable. (2025). Physical layer security in RIS-aided communication systems: Secrecy performance analyses. Digital Signal Processing: A Review Journal.

Authors unavailable. (2025). A handover decision optimization method based on data-driven MLP in 5G ultra-dense small cell HetNets. Journal of Network and Systems Management. Citations: 3

Authors unavailable. (2025). Human respiration and motion detection based on deep learning and signal processing techniques to support search and rescue teams. Applied Sciences (Switzerland).

Authors unavailable. (2025). Target parameter estimation with ISAC-OTFS systems. Conference paper.

Authors unavailable. (2025). A comprehensive review on ISAC for 6G: Enabling technologies, security, and AI/ML perspectives. Review, Open Access. Citations: 1

Reham A. abdelwahab | Smart Cities | Best Researcher Award

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Dr. Reham A. abdelwahab | Smart Cities | Best Researcher Award

PhD| Cairo University | Egypt

Reham Ahmed Abdelwahab, Ph.D., is a sustainability-focused architect and project manager specializing in environmental design, energy modeling, and green building certification with over 14 years of expertise. Her research field centers on sustainable urbanism, microclimate assessment, and value engineering for optimizing urban and building design performance. She integrates advanced energy simulation tools such as IES VE, DesignBuilder, Envi-met, and Eddy3D to analyze thermal comfort, daylighting, ventilation, and energy efficiency at both building and city scales. Reham’s work contributes to improving resilience and cost-effectiveness in urban development by aligning design decisions with climate-responsive strategies and green certification requirements, including LEED, WELL, and ENV SP. She has led projects across Egypt, UAE, and KSA, focusing on CFD-based airflow studies, UTCI-based outdoor comfort evaluations, and mesoscale modeling for enhancing urban heat mitigation strategies. Her research emphasizes a data-driven approach to sustainable planning, integrating LCA tools like OneClick LCA and SimaPro to assess embodied carbon and lifecycle impacts. Reham applies value engineering techniques to landscape and architectural design parameters, enabling decision-makers to balance sustainability goals with economic feasibility. Her contributions extend to project management and multidisciplinary coordination, ensuring design compliance with international green standards. Through her Ph.D. thesis, she explores optimizing landscape design parameters to enhance urban comfort, energy savings, and climate resilience while providing practical frameworks for architects and planners. This research field bridges the gap between simulation-based analysis, green certification compliance, and real-world project implementation, making it highly relevant to sustainable development goals and future city planning. Her expertise drives innovation in urban performance simulation, resource efficiency, and occupant well-being.

Profile:  Scopus | ORCID
Featured Publication

Abdelwahab, R. A. (2025). The effective landscape design parameters with high reflective hardscapes: Guidelines for optimizing human thermal comfort in outdoor spaces by design – A case on hot arid climate weather. Computational Urban Science. citations 2