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

Werner E.G. Müller | Open Source | Best Scholar Award

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Prof. Werner E.G. Müller | Open Source | Best Scholar Award

Prof. Dr. Dr. h.c | Mainz University Medical Center | Germany

Prof Werner E. G. Müller is a leading researcher in biochemistry, molecular medicine, and regenerative medicine, with pioneering contributions spanning virology, marine biotechnology, biomineralization, nanomedicine, and translational biomedical research. His work has been instrumental in the development of antiviral and anticancer therapeutics, including ara-A, ara-C, and Bleomycin, while also establishing the biomedical relevance of inorganic polyphosphates for tissue regeneration. Müller has led independent research groups and coordinated numerous international and EU-funded projects, advancing both fundamental science and clinical applications. His research integrates molecular mechanisms with practical strategies to enhance drug development, tissue engineering, and regenerative therapies, establishing innovative platforms that bridge academic research with industrial and translational opportunities. As a prolific scholar, Müller has published over 1,200 SCI-indexed articles and more than 20 monographs, contributing to multiple international patents that translate scientific discoveries into therapeutic applications. His investigations in marine biotechnology have opened new pathways for understanding biomineralization processes and their application in regenerative medicine, while his work in nanomedicine provides novel insights into drug delivery, biomaterials, and cellular repair mechanisms. Müller has also played a central role in mentoring future leaders in science, supervising more than 70 PhD students and over 100 Master’s and Bachelor’s theses, cultivating the next generation of experts in biochemistry, molecular medicine, and biotechnology. Recognition of his research includes prestigious awards, an ERC Advanced Grant, three ERC Proof-of-Concept Grants, and international honors, highlighting his influence as a pioneer and global bridge-builder in multiple biomedical fields. The impact of his work continues to shape strategies for disease treatment, tissue regeneration, and biotechnology innovation. Müller’s research has achieved 38,701 citations, 1,125 published documents, and an h-index of 89, demonstrating the profound and sustained global impact of his scientific contributions.

Profile:  Scopus 
Featured Publication

Freeze-cast composites of alginate/pyrophosphate-stabilized amorphous calcium carbonate: From the nanoscale structuration to the macroscopic properties. ACS Biomaterials Science & Engineering, volume, page range. Citations: 1

Janus orthogonal nanofiber membrane containing CPP@PDA for skull base reconstruction. Journal of Materials Science and Technology, volume, page range. Citations: 2

Cell migration, DNA fragmentation and antibacterial properties of novel silver doped calcium polyphosphate nanoparticles. Scientific Reports, volume, page range. Citations: 8

Polyphosphate nanoparticles: Balancing energy requirements in tissue regeneration processes. Journal Name, volume, page range. Citations: 8

Evaluation of a novel triplex immunochromatographic test for rapid simultaneous detection of norovirus, rotavirus, and adenovirus on a single strip test. Journal of Infection and Public Health, volume, page range. Citations: 3

Nadiia Konovenko | Education Technology | Women Researcher Award

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Dr. Nadiia Konovenko | Education Technology | Women Researcher Award

Odesa National University of Technology | Ukraine

Dr Nadiia Konovenko is a docent of the Department of Physical and Mathematical Sciences at Odesa National University of Technology, Ukraine, with extensive contributions to the study of algebras of differential invariants, Lobachevsky geometry, differential geometry, 2F-planar mappings, and quasi-geodesic mappings. Her research is notable for discovering fields of rational differential invariants for the actions of Lie pseudogroups on planar webs, enabling a classification of planar 3-webs with respect to symplectic and conformal Lie pseudogroups. Nadiia Konovenko has successfully completed 20 research projects and is currently working on two more, continuously enriching the mathematical sciences domain with new insights and methods. She is the author of the book “Differential Invariants and sl2 Geometry” published by Naukova Dumka and has published 20 papers in indexed journals, demonstrating consistent productivity and impact. Beyond her publications, she serves as the managing editor of the journal “Proceedings of the International Geometry Center” and is a member of the editorial board of “Automation of Technological and Business Processes,” actively shaping the dissemination of high-quality research. Nadiia Konovenko is also chair of the organizing committee and a member of the international scientific committee of the conference “Algebraic and Geometric Methods of Analysis,” which brings together leading researchers to advance knowledge in geometry and related fields. Her collaborations include participation in programs such as “Infinite-dimensional Riemannian Geometry with Applications to Image Matching and Shape Analysis” at the Erwin Schrödinger International Institute for Mathematical Physics, Vienna, and engagement in the X and XI Summer Schools on Algebra, Topology, and Analysis. As a full member of the Kyiv Mathematical Society, Nadiia Konovenko continues to play a vital role in advancing geometric theory and its applications. Her research impact is reflected by 17 citations in 13 documents and an h-index of 2.

Profile:  Google Scholar | Scopus | ORCID
Featured Publication

Konovenko, N. G. (2004). 2F-planar mappings of Riemannian spaces preserving a generalized f-structure. Proceedings of the International Laptev Geometry Seminar, 8. Citations: 8

Konovenko, N., & Lychagin, V. (2011). On projective classification of plane curves. Global and Stochastic Analysis, 1(2), 1–24. Citations: 7

Konovenko, N., & Lychagin, V. (2016). Invariants of projective actions and their application to recognition of fingerprints. Analysis and Mathematical Physics, 6(1), 95–107. Citations: 6

Konovenko, N. G. (2013). Differential invariants and sl2-geometry. Kyiv: Naukova Dumka Publishing House, National Academy of Sciences of Ukraine. Citations: 6

Konovenko, N. (2010). Projective structures and algebras of their differential invariants. Acta Applicandae Mathematicae: An International Survey Journal on Applying Mathematics, 110(1), 167–185.  Citations: 6

Khaista Rahman | Artificial Intelligence| Best Paper Award

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Dr. Khaista Rahman | Artificial Intelligence| Best Paper Award

Assistant Professor | Shaheed Benazir Bhutto University Sheringal | Pakistan 

Dr. Khaista Rahman is a distinguished researcher specializing in fuzzy set theory, fuzzy logic, aggregation operators, and artificial intelligence-based decision support systems, with a strong focus on solving decision-making problems under uncertainty. His work explores advanced mathematical structures like Pythagorean fuzzy numbers, interval-valued fuzzy models, and complex fuzzy systems to create robust solutions for multi-attribute group decision-making processes. Dr. Rahman has published extensively on generalized and induced aggregation operators, developing new models that enhance decision accuracy and reliability in diverse applications such as plant location selection, hospital siting during COVID-19, vaccine selection, and railway optimization problems. His research integrates t-norm and t-conorm-based approaches, Einstein hybrid operators, and logarithmic intuitionistic fuzzy techniques to handle complex decision environments. He has also supervised several M.Phil., M.Sc., and BS scholars, contributing significantly to academic mentorship and knowledge dissemination. Recognized among the top 2% scientists worldwide by Stanford University from 2022 to 2025, he has made substantial contributions to granular computing, soft computing, and intelligent systems literature. His work during the COVID-19 pandemic stands out for developing emergency response models using complex fuzzy information to predict and manage disease spread in Pakistan. As Principal Investigator of a funded project on complex intelligent decision support models, Dr. Rahman has bridged theoretical advancements with practical implementations, making his research highly impactful. With an H-index of 26 and over 1900 citations, his scholarly influence spans mathematics, operations research, and computational intelligence, providing frameworks that empower policymakers and industries to make optimal decisions in uncertain and dynamic scenarios. Dr. Khaista Rahman has achieved 776 citations across 532 documents with an impressive h-index of 16.

Profile:  Scopus | ORCID
Featured Publication

  1. Rahman, K., & Khishe, M. (2024). Confidence level based complex polytopic fuzzy Einstein aggregation operators and their application to decision-making process [Retracted]. Scientific Reports, 14(1), 15253.

  2. Rahman, K., & Khishe, M. (2024). Retraction Note: Confidence level based complex polytopic fuzzy Einstein aggregation operators and their application to decision-making process. Scientific Reports, 14(1).

  3. Rahman, K., et al. (2025). Unraveling vegetation diversity and environmental influences in the Sultan Kha Valley, Dir Upper, Pakistan: An advanced multivariate analysis approach. Polish Journal of Environmental Studies.

  4. Rahman, K. (2024). Some new types induced complex intuitionistic fuzzy Einstein geometric aggregation operators and their application to decision-making problem. Neural Computing and Applications.