Mitsuru Endo | Computational Theory | Best Researcher Award

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Prof. Dr. Mitsuru Endo | Computational Theory | Best Researcher Award

Professor Emeritus| Tokyo Institute of Technology | Japan

Mitsuru Endo has made distinguished contributions to applied mechanics and vibration engineering, focusing on the dynamic behavior of continua and structures and the development of advanced noise and vibration control systems. His work bridges theoretical mechanics and practical applications in acoustic control, offering innovative solutions for vibration reduction in engineering systems. Endo has pioneered the extension of Southwell-Dunkerley methods for synthesizing frequencies, contributing to a deeper understanding of vibrational modes in complex systems. His research on flexural vibrations of rotating rings and deformation theories for beams, plates, and cylindrical shells has advanced modeling precision in mechanical structures. By introducing alternative formulations for Timoshenko beam and Mindlin plate models, Endo improved computational accuracy in vibration analysis. His innovative “one-half order shear deformation theory” redefined how transverse shear deformation is represented in structural mechanics, influencing global research on elasticity and composite structures. Endo’s extensive publications in leading journals such as the Journal of Sound and Vibration and the International Journal of Mechanical Sciences have established a strong foundation for future explorations in vibration modeling, acoustic optimization, and structural mechanics. His studies integrate both analytical and experimental perspectives, driving advancements in passive and active noise control technologies essential to aerospace, automotive, and civil engineering applications. The recognition of his work through multiple prestigious awards underscores his impact in mechanical sciences and engineering research, with 440 citations, 64 documents, and an h-index of 8.

Profiles: Scopus | ORCID
Featured Publication

Endo, M. (2013). Study on direct sound reduction structure for reducing noise generated by vibrating solids. Journal of Sound and Vibration, 332, 2643–2658. 5 citations

Endo, M. (2015). Study on an alternative deformation concept for the Timoshenko beam and Mindlin plate models. International Journal of Engineering Science, 87, 32–56. 34 citations

Endo, M. (2016). An alternative first-order shear deformation concept and its application to beam, plate and cylindrical shell models. Composite Structures, 146, 50–61. 17 citations

Endo, M. (n.d.). Study on the characteristics of noise reduction effects of a sound reduction structure. Conference Paper. 1 citation

Fu Chaotian | Software Engineering | Best Researcher Award

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Dr. Fu Chaotian | Software Engineering | Best Researcher Award

Researcher | China Coal Technology and Engineering Group Shenyang Research Institute Co., Ltd. | China

Tian Fuchao, a distinguished researcher and chief scientist at the China Coal Technology and Engineering Group Shenyang Research Institute Co., Ltd., has established a remarkable career focusing on mine fire and gas disaster prevention under coupled conditions, industrial environmental gas spectroscopy, and advanced instrument development. His extensive research has led to the successful completion of 34 major research projects, the publication of 87 peer-reviewed journal papers, 5 books, and 69 patents, showcasing a strong integration of theory and industrial application. With an SCI h-index of 16, his work demonstrates both depth and impact within the field of coal mine safety and gas control technologies. Tian Fuchao has played a central role in developing state-of-the-art scientific instruments such as the TZX-1000 atmospheric environment monitoring system, TZX-3000 intelligent gas adsorption-desorption platform, and TZX-7000 laser-based multi-parameter detection system, which have been widely adopted across China. His research collaborations with the National Natural Science Foundation of China have focused on the mechanisms of gas desorption and spontaneous combustion in coal under multi-field coupling, contributing significantly to understanding disaster mechanisms in deep mining environments. Additionally, his editorial roles in Journal of China Coal Society and China Safety Science Journal reflect his leadership in advancing scientific communication. As a professional member of the China Occupational Safety and Health Association’s Youth Committee, Tian Fuchao continues to promote innovation and safety culture in industrial research. His ongoing efforts toward coupling analysis, predictive modeling, and intelligent monitoring technologies mark him as a leading figure in coal mine safety and environmental engineering. Tian Fuchao’s pioneering research continues to advance global understanding of energy safety and sustainable industrial operations, with 1,140 citations from 1,000 documents, 98 publications, and an h-index of 19.

Profiles:  Scopus | ORCID
Featured Publication

Thermal stability of acidified coal under coupled pressure and temperature effects. Thermal Science and Engineering Progress.

Explosion behavior of premixed LPG-hydrogen/air mixtures in a square duct. Physics of Fluids.

Dynamic viscosity evolution characteristics of ScCO₂ and its effects on carbon geological sequestration efficiency. Energy.

Precise gas control technology for fault fracture zones in deep roadways. Physics of Fluids.

Roof fracture dynamics and synergistic control strategies for mitigating coal mine gas disasters in goaf regions. Mining, Metallurgy and Exploration.

Arif Basgumus | Mobile Computing | Best Researcher Award

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Dr. Arif Basgumus | Mobile Computing | Best Researcher Award

Associate Professor | Bursa Uludag University | Turkey

Dr. Arif Basgumus is a distinguished Associate Professor at Bursa Uludag University, whose research profoundly advances wireless communication, signal processing, and next-generation network systems. His extensive contributions encompass cognitive radio networks, non-orthogonal multiple access (NOMA), reconfigurable intelligent surfaces (RIS), cooperative communications, integrated sensing and communication (ISAC), and physical layer security. Dr. Arif Basgumus has developed robust models for interference alignment, hybrid RF/VLC systems, and UAV-assisted network architectures, contributing significantly to 5G and 6G technology evolution. His studies integrate theoretical modeling with artificial intelligence applications, enhancing the efficiency and reliability of communication frameworks. Actively collaborating with industrial partners such as ASELSAN, HAVELSAN, and TUSAŞ, he bridges academic innovation with practical defense and aerospace applications. His authorship spans influential journals including IEEE Access, IET Communications, and Digital Signal Processing, reflecting a consistent research impact in signal optimization, deep learning-aided communications, and security enhancement in RIS-assisted systems. He has guided numerous graduate theses, emphasizing interdisciplinary approaches across electrical, electronics, and computer engineering. His projects funded by TUBITAK and other research councils explore UAV communication, smart vehicle systems, and optical sensor networks, fostering sustainable and intelligent connectivity. Dr. Arif Basgumus has also co-authored several books and chapters on communication systems, cognitive networks, and artificial intelligence in engineering. His long-standing involvement in international collaborations and IEEE activities highlights a leadership role in shaping the technological foundations of future communication infrastructures, with 256 citations, 48 documents, and an h-index of 10 (View h-index).

Profiles:  Google Scholar | Scopus | ORCID
Featured Publication

Alakoca, H., Namdar, M., Aldirmaz-Colak, S., Basaran, M., & Basgumus, A. (2022). Metasurface manipulation attacks: Potential security threats of RIS-aided 6G communications. IEEE Communications Magazine, 61(1), 24–30. Citations: 43

Bayhan, E., Ozkan, Z., Namdar, M., & Basgumus, A. (2021). Deep learning-based object detection and recognition of unmanned aerial vehicles. In Proceedings of the 3rd International Congress on Human-Computer Interaction, Optimization and Robotic Applications. Citations: 41

Ozkan, Z., Bayhan, E., Namdar, M., & Basgumus, A. (2021). Object detection and recognition of unmanned aerial vehicles using Raspberry Pi platform. In Proceedings of the 5th International Symposium on Multidisciplinary Studies and Innovative Technologies. Citations: 34

Altuncu, A., & Basgumus, A. (2005). Gain enhancement in L-band loop EDFA through C-band signal injection. IEEE Photonics Technology Letters, 17(7), 1402–1404. Citations: 27

Basgumus, A., Durak, F. E., Altuncu, A., & Yilmaz, G. (2015). A universal and stable all-fiber refractive index sensor system. IEEE Photonics Technology Letters, 28(2), 171–174. Citations: 26

Umakoglu, I., Namdar, M., Basgumus, A., Kara, F., Kaya, H., & Yanikomeroglu, H. (2021). BER performance comparison of AF and DF assisted relay selection schemes in cooperative NOMA systems. In Proceedings of the 2021 IEEE International Black Sea Conference on Communications and Networking. Citations: 22

Mustafa Namdar | High Performance Computing | Best Researcher Award

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Assoc. Prof. Dr . Mustafa Namdar | High Performance Computing | Best Researcher Award

Assoc. Prof. Dr | Kutahya Dumlupinar University| Turkey

Dr. Mustafa Namdar has established a distinguished research profile in advanced wireless communications and network technologies, focusing on cognitive radio networks, cooperative communications, relay networks, interference alignment, non-orthogonal multiple access (NOMA), reconfigurable intelligent surfaces (RIS), and integrated sensing and communication (ISAC). His work emphasizes innovative solutions to enhance spectral efficiency, reliability, and performance in next-generation communication systems. Dr. Namdar has contributed extensively to the development of receiver diversity and dispersed spectrum sensing techniques, enabling efficient utilization of available spectrum and minimizing interference in dynamic network environments. His research integrates theoretical modeling with practical system design, addressing complex challenges in 5G and emerging 6G wireless technologies. He has actively collaborated on projects related to cooperative relay networks and interference management, which are critical for optimizing throughput and ensuring robust connectivity in dense network scenarios. In addition to his contributions to physical layer design, Dr. Namdar explores the potential of reconfigurable intelligent surfaces and ISAC frameworks to simultaneously support communication and sensing functionalities, offering a transformative approach for intelligent wireless networks. His work has been recognized through multiple awards, including the Outstanding Reviewer Award from Elsevier-AEU Journal and IEEE SIU Conference accolades, reflecting both the quality and impact of his research in the international community. Dr. Namdar’s expertise in NOMA and interference alignment provides practical solutions for multi-user communication scenarios, significantly advancing spectral efficiency and network capacity. He has also played a pivotal role in the technical evaluation of numerous research projects and has contributed as a reviewer and TPC member across prestigious IEEE conferences and journals, ensuring high standards in scholarly communications. His ongoing research aims to drive the evolution of future wireless networks with integrated sensing, enhanced resource allocation, and next-generation communication protocols. 272 Citations, 54 Documents, 10 h-index, View h-index.

Profiles:  Google Scholar | Scopus
Featured Publication

Alakoca, H., Namdar, M., Aldırmaz-Çolak, S., Basaran, M., Basgumus, A., & … (2023). Metasurface manipulation attacks: Potential security threats of RIS-aided 6G communications. IEEE Communications Magazine, 61(1), 24–30. 43 citations

Bayhan, E., Ozkan, Z., Namdar, M., & Basgumus, A. (2021). Deep learning based object detection and recognition of unmanned aerial vehicles. 2021 IEEE 3rd International Congress on Human-Computer Interaction. 41 citations

Ozkan, Z., Bayhan, E., Namdar, M., & Basgumus, A. (2021). Object detection and recognition of unmanned aerial vehicles using Raspberry Pi platform. 2021 IEEE 5th International Symposium on Multidisciplinary Studies and … 34 citations

Namdar, M., & Ilhan, H. (2018). Exact closed-form solution for detection probability in cognitive radio networks with switch-and-examine combining diversity. IEEE Transactions on Vehicular Technology, 67(9), 8215–8222. 23 citations

Namdar, M., Ilhan, H., & Durak-Ata, L. (2016). Optimal detection thresholds in spectrum sensing with receiver diversity. Wireless Personal Communications, 87, 63–81. 23 citations

Umakoglu, I., Namdar, M., Basgumus, A., Kara, F., Kaya, H., & Yanikomeroglu, H. (2021). BER performance comparison of AF and DF assisted relay selection schemes in cooperative NOMA systems. 2021 IEEE International Black Sea Conference on Communications and … 22 citations

Caitlin Kent | Open Source | Best Researcher Award

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Ms. Caitlin Kent | Open Source | Best Researcher Award

Honours Student | University of Wollongong | Australia

Ms. Caitlin Kent has built a distinguished career in nursing and health research, with a particular focus on global and tropical health, immunisation programs, and community-based research. Her role at the Menzies School of Health Research demonstrates expertise in coordinating participant recruitment, conducting mixed-methods and qualitative research, and presenting findings to stakeholders and policy partners. Caitlin’s work contributes to the advancement of public health initiatives aimed at addressing disease prevention and improving healthcare outcomes in diverse populations. Her professional experience spans both clinical and research settings, including emergency departments, acute care, and neurological wards, where she has developed critical skills in patient management, leadership, and interdisciplinary collaboration. As part of the “B Part of it NT” Meningococcal B vaccine study, Caitlin engaged in public health research focused on vaccination coverage and disease control in Northern Territory communities. Her work as a Nurse Immuniser during the Covid-19 and Influenza vaccination rollout further reflects her dedication to preventive healthcare and rural outreach. In addition to her clinical expertise, Caitlin’s engagement in leadership and mentorship programs—such as the Menzies Leadership Development Program, Emerging Research Leadership Program, and Catalyse Mentorship Program—highlights her commitment to advancing research capacity and promoting women in STEMM. Her recognition through academic awards and participation in professional development programs underscores a strong foundation in evidence-based practice and applied health research. Through her ongoing Honours in Nursing and active involvement in multidisciplinary research initiatives, Caitlin continues to contribute to improving healthcare delivery, fostering community health awareness, and strengthening the integration of clinical practice with research innovation across Australia’s tropical and remote health landscape.

Profile:  ORCID
Featured Publication

Kent, C., & Halcomb, E. (2025). Nurses’ experiences of mental health care in the emergency department: An integrative review. Journal of Clinical Nursing, 34(9–10), 1–15.

Ying Yi Tan | Smart Manufacturing | Best Researcher Award

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Dr. Ying Yi Tan | Smart Manufacturing | Best Researcher Award

Research Fellow | Singapore University of Technology and Design | Singapore

Dr. Tan Ying Yi is a Research Fellow at the Singapore University of Technology and Design (SUTD) whose research lies at the intersection of digital fabrication, smart textiles, and computational design. The focus of his work is the development of digital knitting technologies and multi-material additive manufacturing methods for creating functional, mechanically graded, and intelligent textile-based systems. His investigations explore how knitted fabrics can be engineered with integrated electrical and mechanical properties, transforming traditional textiles into high-performance materials applicable to both architectural and biomedical domains. Ying Yi has played a significant role in advancing customized technical textiles for applications such as structural membranes, façade systems, prosthetic interfaces, and wearable technologies. His leadership in projects involving smart garments for body joint monitoring has contributed to innovations in digital health and human–machine interaction, demonstrating the potential of computational design and materials research to improve quality of life. Collaborative projects with institutions like SingHealth Polyclinics, Tan Tock Seng General Hospital, and Hyundai Motor Group have led to impactful real-world solutions such as smart knee braces for gait assessment and smart shirts for motion tracking. His work is characterized by an interdisciplinary approach, blending engineering precision, material science, and architectural design principles to create responsive systems that interact dynamically with users and environments. Recognized with awards for excellence in architectural membranes and advanced manufacturing, Ying Yi continues to contribute to the integration of digital fabrication, computational modeling, and soft robotics in technical textile research. His studies have been featured by major media outlets for their innovation and societal relevance, showcasing how fabric-based systems can bridge the gap between engineering and design. Citations 19 Documents 5 h-index View.

Profiles: Google Scholar | Scopus | ORCID
Featured Publication

Weeger, O., Sakhaei, A. H., Tan, Y. Y., Quek, Y. H., Lee, T. L., Yeung, S. K., & Kaijima, S. (2018). Nonlinear multi-scale modelling, simulation and validation of 3D knitted textiles. Applied Composite Materials, 25(4), 797–810. Citations: 43

Sakhaei, A. H., Kaijima, S., Lee, T. L., Tan, Y. Y., & Dunn, M. L. (2018). Design and investigation of a multi-material compliant ratchet-like mechanism. Mechanism and Machine Theory, 121, 184–197. Citations: 31

Gupta, S. S., Tan, Y. Y., Chia, P. Z., Pambudi, C. P., Quek, Y. H., Yogiaman, C., & Tracy, K. J. (2020). Prototyping knit tensegrity shells: A design-to-fabrication workflow. SN Applied Sciences, 2(6), 1062. Citations: 25

Do, H., Tan, Y. Y., Ramos, N., Kiendl, J., & Weeger, O. (2020). Nonlinear isogeometric multiscale simulation for design and fabrication of functionally graded knitted textiles. Composites Part B: Engineering, 202, 108416. Citations: 20

Gupta, U., Lau, J. L., Chia, P. Z., Tan, Y. Y., Ahmed, A., Tan, N. C., Soh, G. S., & Low, H. Y. (2023). All knitted and integrated soft wearable of high stretchability and sensitivity for continuous monitoring of human joint motion. Advanced Healthcare Materials, 12(21), 2202987. Citations: 17

Pal, A., Chan, W. L., Tan, Y. Y., Chia, P. Z., & Tracy, K. J. (2020). Knit concrete formwork. Proceedings of the 25th CAADRIA Conference, 1, 213–222. Citations: 7

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

Profile:  Google Scholar | Scopus | ORCID
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