Hadi Gokcen | Engineering | Best Researcher Award

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Prof. Hadi Gokcen | Engineering | Best Researcher Award

Professor | Gazi University Industrial Engineering Department | Turkey

Dr. Hadi Gökçen, affiliated with Gazi University, Ankara, Turkey, is a distinguished researcher recognized for his influential contributions to industrial engineering, operations research, and computational intelligence. With 51 published documents, an h-index of 23, and more than 1,920 citations from 1,367 citing documents, his scholarly impact spans data-driven decision systems, intelligent manufacturing, and applied artificial intelligence. His recent works reflect a strong integration of machine learning, optimization, and sustainability in solving real-world industrial and economic problems. In Computational Economics , he introduced a hybrid machine learning model that combines clustering and stacking ensemble approaches for improved real estate price prediction. His research published in Applied Sciences Switzerland, proposed a dynamic scheduling method for identical parallel-machine environments through a multi-purpose intelligent utility framework. In Flexible Services and Manufacturing Journal, he presented innovative balancing and sequencing strategies for mixed-model parallel robotic assembly lines, emphasizing energy-efficient production. Further, his Survey Review paper applied hybrid unsupervised learning to identify sub-real estate markets, enhancing prediction accuracy and market segmentation. His contribution to developing a Digital Transformation Perception Scale underscores his focus on organizational innovation and industrial adaptation within the Industry paradigm. Dr. Gökçen’s interdisciplinary research bridges artificial intelligence, optimization, and digital transformation, advancing the understanding and implementation of intelligent, sustainable, and adaptive systems in engineering and economic domains.

Profiles : ORCID | Scopus | Google Scholar 

Featured Publications

1. Demirel, N. Ö., & Gökçen, H. (2008). A mixed integer programming model for remanufacturing in reverse logistics environment. The International Journal of Advanced Manufacturing Technology, 39(11), 1197–1206.
Cited By : 258

2. Demirel, E., Demirel, N., & Gökçen, H. (2016). A mixed integer linear programming model to optimize reverse logistics activities of end-of-life vehicles in Turkey. Journal of Cleaner Production, 112, 2101–2113.
Cited By : 247

3. Gökçen, H., Ağpak, K., & Benzer, R. (2006). Balancing of parallel assembly lines. International Journal of Production Economics, 103(2), 600–609.
Cited By : 226

4. Gökçen, H. (2007). Yönetim bilgi sistemleri. Ankara: Palme Yayıncılık.
Cited By : 217

5. Erel, E., & Gökçen, H. (1999). Shortest-route formulation of mixed-model assembly line balancing problem. European Journal of Operational Research, 116(1), 194–204.
Cited By : 189

Mohammad Taghilou | Engineering | Best Researcher Award

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Assoc. Prof. Dr. Mohammad Taghilou | Engineering | Best Researcher Award

Associate professor | University of Zanjan | Iran

Dr. Mohammad Taghilou is an Associate Professor in the Department of Mechanical Engineering at the University of Zanjan, Iran. His research expertise lies in heat transfer, phase change problems, energy storage, and porous media, with an emphasis on the lattice Boltzmann method (LBM) and its applications in thermal systems. Over his academic career, he has authored impactful studies published in leading journals such as Applied Thermal Engineering, Computers & Mathematics with Applications, and the International Journal of Thermal Sciences. His most cited works explore PCM solidification, nanofluid-based heat exchangers, and the thermal behavior of energy storage systems. Dr. Taghilou’s studies significantly contribute to advancing thermal management technologies, including applications in lithium-ion batteries, heat sinks, and double-pipe exchangers, with an aim to enhance energy efficiency and system reliability. His collaborations with international scholars from institutions such as the University of Tehran, Aalto University (Finland), and the University of Technology Sydney have expanded the interdisciplinary reach of his research. With 541 total citations, an h-index of 15, and an i10-index of 16, his work demonstrates both academic impact and global relevance. Through innovative numerical modeling and experimental approaches, Dr. Taghilou continues to advance understanding in phase-change thermal systems and nanomaterial-enhanced heat transfer, fostering sustainable energy applications and modern engineering solutions.

Profiles: ORCID | Scopus | Google Scholar | ResearchGate | LinkedIn

Featured Publications

1.Sajedi, R., Osanloo, B., Talati, F., & Taghilou, M. (2016). Splitter plate application on the circular and square pin fin heat sinks.  Cited by : 70

2.Taghilou, M., & Rahimian, M. H. (2014). Investigation of two-phase flow in porous media using lattice Boltzmann method. Cited By : 49

3.Talati, F., & Taghilou, M. (2015). Lattice Boltzmann application on the PCM solidification within a rectangular finned container. Cited By : 44

4.Taheri, A. A., Abdali, A., Taghilou, M., Alhelou, H. H., & Mazlumi, K. (2021). Investigation of mineral oil-based nanofluids effect on oil temperature reduction and loading capacity increment of distribution transformers.
Cited By : 40

5.Taghilou, M., & Khavasi, E. (2020). Thermal behavior of a PCM filled heat sink: The contrast between ambient heat convection and heat thermal storage. Cited By : 36

Mohammed M Alenazi | Computer Science and Artificial Intelligence | Best Researcher Award

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Dr. Mohammed M Alenazi | Computer Science and Artificial Intelligence | Best Researcher Award

Assistance Professor | University of Tabuk | Saudi Arabia

Dr. Mohammed M. Alenazi is an Assistant Professor of Computer Engineering at the University of Tabuk, Saudi Arabia, whose research focuses on the intersection of energy-efficient communication networks, machine learning, and distributed systems. His work advances intelligent computing architectures that optimize performance, reduce energy consumption, and enable sustainability in next-generation networks. Dr. Alenazi has contributed to several impactful studies, including energy-efficient neural network embedding in IoT over passive optical networks, distributed machine learning in cloud–fog environments, and AI-driven frameworks for 6G-IoT-based remote cardiac monitoring. His research extends to federated learning for low-latency IoT communications, hybrid cloud edge architectures for real-time cryptocurrency forecasting with blockchain integration, and machine learning-optimized energy management for resilient residential microgrids with electric vehicle integration. His scholarly output, cited over 50 times with an h-index of 4 and i10-index of 3, reflects growing recognition in the domains of sustainable networking and intelligent systems. Dr. Alenazi’s work combines AI, IoT, and cloud–fog computing to create adaptive, energy-aware solutions for smart environments, healthcare, and industrial systems. Through his innovative contributions, he continues to enhance the efficiency, reliability, and intelligence of modern communication infrastructures, positioning his research at the forefront of AI-powered green networking and distributed intelligence for the evolving digital ecosystem.

Profiles : ORCID | Scopus | Google Scholar | ResearchGate

Featured Publications

1. Alenazi, M. M., Yosuf, B. A., El-Gorashi, T., & Elmirghani, J. M. H. (2020). Energy efficient neural network embedding in IoT over passive optical networks. Cited By : 13

2.Yosuf, B. A., Mohamed, S. H., Alenazi, M. M., El-Gorashi, T. E. H., & Elmirghani, J. M. H. (2021). Energy-efficient AI over a virtualized cloud fog network. Cited By : 12

3.Alenazi, M. M., Yosuf, B. A., Mohamed, S. H., El-Gorashi, T. E. H., & Elmirghani, J. M. H. (2021). Energy-efficient distributed machine learning in cloud fog networks. Cited By : 10

4.Banga, A. S., Alenazi, M. M., Innab, N., Alohali, M., Alhomayani, F. M., Algarni, M. H., et al. (2024). Remote cardiac system monitoring using 6G-IoT communication and deep learning. Cited By : 6

5.Alenazi, M. M., Yosuf, B. A., Mohamed, S. H., El-Gorashi, T. E. H., & Elmirghani, J. M. H. (2022). Energy efficient placement of ML-based services in IoT networks. Cited By : 4

Amanpreet Kaur | Blockchain and Deep Learning | Best Researcher Award

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Dr. Amanpreet Kaur | Blockchain and Deep Learning | Best Researcher Award

Professor | Chitkara University | India

Dr. Amanpreet Kaur is an accomplished researcher in computer science with expertise in artificial intelligence, blockchain, IoT, big data analytics, and machine learning. She earned her PhD in computer science from Jaipur National University after completing advanced degrees including M.Tech, M.Sc. in computer science, B.C.A., and a diploma in computer engineering. Her professional journey includes teaching, mentoring, and supervising M.Tech and Ph.D. scholars in cutting-edge research projects such as deep learning for healthcare, blockchain-based security frameworks, and network optimization. She has authored 64 publications in reputed IEEE and Scopus indexed journals and conferences, showcasing her consistent contributions to the academic community. Her research interests lie in deep learning, data security, smart networks, and sustainable computing technologies. She has been an active member of several professional organizations including IRED, IAENG, SDIWC, and CSTA, and holds multiple certifications such as MCP, Java, Python, and Software Testing, which strengthen her applied research profile. Her work reflects a strong blend of academic scholarship, technical expertise, and leadership, enabling her to play a key role in advancing research and guiding future professionals. She is recognized for her dedication to fostering innovation and contributing to the growth of the computer science domain. Her research impact is demonstrated by 722 citations across 57 documents with an h-index of 9.

Profiles : ORCID | Scopus | Google Scholar

Featured Publications

1.Amanpreet Kaur, S. S., Singh, G., Kukreja, V., Yoon, B., & Sharma, S. (n.d.). Adaptation of IoT with blockchain in food supply chain management: An analysis-based review in development, benefits and potential applications. Sensors, 22(21).

2.Kukreja, V. S., Sharma, R., Kaur, A., & Sachdeva, R. K. (n.d.). Deep neural network for multi-classification of parsley leaf spot disease detection. In Proceedings of the 2nd International Conference on Advance Computing and Innovative Technologies.

3.Kaur, A., Dhaka, V. S., & Singh, G. (n.d.). ACO agent-based routing in AOMDV environment. MATEC Web of Conferences, 57, 02005.

4.Bathla, N., Kaur, A., & Singh, G. (n.d.). Relative inspection of TCP variants Reno, New Reno, SACK, Vegas i8285n AODV. International Journal of Research in Engineering and Applied Sciences, 4.

5.Bathla, N., Kaur, A., & Singh, G. (n.d.). Congestion control techniques in TCP: A critique. In Proceedings of the 3rd National Conference of Advances and Research in Engineering.

Dayu Jia | Big Data Management | Best Researcher Award

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Mr. Dayu Jia | Big Data Management | Best Researcher Award

Associate Professor | Liaoning University | China

Dr. Jia Dayu is an Associate Professor and Master’s Supervisor at the School of Information Science, Liaoning University. He completed his Ph.D. in Computer Science at Northeastern University under the guidance of Prof. Wang Guoren and further gained international experience as a joint Ph.D. student at the National University of Singapore under Prof. Ooi Beng Chin. He also worked as a postdoctoral fellow at the School of Information Science and Engineering, Northeastern University. Dr. Jia has been actively involved in national, provincial, and ministerial research projects and has collaborated on international research initiatives. His research focuses on big data management, blockchain data analysis, and artificial intelligence, with expertise in scalable storage, secure data retrieval, and privacy-preserving techniques. He has published 21 high-quality papers in reputed journals and conferences, including Q1 journals such as Advanced Materials and Light: Science & Applications, and has served as the first or corresponding author on 12 publications in prestigious venues like JCST, WWW, and Software Journal. Dr. Jia has also been granted 13 national invention patents, demonstrating his innovative contributions, and has hosted or participated in six funded research projects. His skills include blockchain architecture design, data analytics, AI-driven optimization, and secure distributed systems. His work has earned recognition with 176 citations by 14 documents and an h-index of 5, reflecting the impact and relevance of his research in the academic community.

Profile : Scopus 

Featured Publication

1. Jia, D., Hu, Y., Huang, M., Zhang, J., He, G., Xu, S., Liu, S., & Wang, X. (2025). Security risks and solutions of concurrent PBFT. Expert Systems with Applications, 294, 128737.

Sakshi Dua | Engineering | Best Researcher Award

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Assoc. Prof. Dr. Sakshi Dua | Engineering | Best Researcher Award

Associate Professor | Lovely Professional University | India

Dr. Sakshi Dua is an accomplished academic and researcher currently serving as Associate Professor at the School of Computer Applications, Lovely Professional University, Jalandhar-Phagwara, Punjab, India. She holds a Ph.D. in Computer Science and has over 14 years of professional experience as Assistant Professor before her current role. Her research interests span artificial intelligence, Internet of Things, Arduino, machine learning, fuzzy systems, network operating systems, and database management systems. She has contributed as Guest Editor for reputed ABDC and Scopus-indexed journals, authored book chapters with CRC Press, Taylor & Francis, and IGI Global, and is actively involved in book editorial projects with CRC Press and Emerald. She has published widely in SCIE, Scopus, ABDC, and UGC-indexed journals, as well as in IEEE and Springer conferences, and has presented her research internationally. Her contributions extend to applied innovation with patents and copyrights in diverse areas such as smart healthcare, ICT, and IoT-based solutions. She has chaired sessions at IEEE conferences, delivered workshops and FDPs, and guided students through impactful academic and research projects. Her skills include advanced data analysis, algorithm design, applied AI and IoT development, research writing, and academic leadership. Dr. Sakshi Dua has earned recognition through her impactful scholarly work, editorial leadership, and strong community engagement. She has received 71 citations by 9 documents with an h-index of 1.

Profile :  Scopus

Featured Publication

1. Dua, S. (2025). Blockchain-based node authentication algorithm for securing electronic health record data transmission.

Jaime Martinez Valderrama | Land Use Planning | Best Researcher Award

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Dr. Jaime Martinez Valderrama | Land Use Planning | Best Researcher Award

Tenured Scientist | Estación Experimental de Zonas Áridas (EEZA-CSIC) | Spain 

Dr. Jaime Martínez Valderrama is a tenured scientist at the Estación Experimental de Zonas Áridas, CSIC, Spain, with expertise in land degradation, desertification, and sustainable dryland management. He earned his PhD in Agricultural Economics and Social Sciences from the Universidad Politécnica de Madrid, where his doctoral work focused on modeling agricultural systems in fragile environments. His professional experience spans over two decades, including leadership in national and international research projects such as the Atlas of Desertification of Spain, collaborations with the Chinese Academy of Sciences, and European initiatives addressing global change in drylands. He has worked extensively on integrating ecological and socioeconomic models to guide environmental policy, advised government ministries and regional agencies, and engaged in consultancy for private sector sustainability projects. His research interests include desertification risk assessment, climate change adaptation, land use planning, and the socio-ecological dynamics of drylands, with strong emphasis on linking science and policy. He is also active in science communication through books, blogs, and contributions to popular science platforms, reflecting his commitment to connecting research with society. His skills include integrated modeling, ecological risk analysis, sustainability assessment, and interdisciplinary approaches to land management, supported by a robust record of publications in high-impact journals such as Science, Nature Sustainability, and Science of the Total Environment. He has received recognition for his contributions to sustainable land management and continues to expand international collaborations. His academic impact is reflected in 1,257 citations by 64 documents with an h-index of 20.

Profiles : ORCID | Scopus | Google Scholar

Featured Publications

1. Maestre, F. T., Le Bagousse-Pinguet, Y., Delgado-Baquerizo, M., Eldridge, D. J., … (2022). Grazing and ecosystem service delivery in global drylands. Science, 378(6622), 915–920.

2. Ibáñez, J., Martínez, J., & Schnabel, S. (2007). Desertification due to overgrazing in a dynamic commercial livestock–grass–soil system. Ecological Modelling, 205(3), 277–288.

3. Ibáñez, J., Valderrama, J. M., & Puigdefábregas, J. (2008). Assessing desertification risk using system stability condition analysis. Ecological Modelling, 213(2), 180–190.

4. Hirche, A., Salamani, M., Abdellaoui, A., Benhouhou, S., & Valderrama, J. M. (2011). Landscape changes of desertification in arid areas: The case of south-west Algeria. Environmental Monitoring and Assessment, 179(1), 403–420.

5.Martínez-Valderrama, J., Ibáñez, J., Del Barrio, G., Sanjuán, M. E., Alcalá, F. J., … (2016). Present and future of desertification in Spain: Implementation of a surveillance system to prevent land degradation. Science of the Total Environment, 563, 169–178.

Gamal Khater | Environmental Science | Best Researcher Award

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Prof. Dr. Gamal Khater | Environmental Science | Best Researcher Award

Professor | National Research Centre | Egypt

Prof. Dr. Gamal Khater is a distinguished researcher specializing in applied mineralogy, glass technology, and ceramic materials. He completed his B.Sc. in Geology and Chemistry from Mansoura University, followed by M.Sc. and Ph.D. degrees in Geology from Ain Shams University. He has extensive professional experience as a professor emeritus at the National Research Centre, with prior roles including technical expertise and consultancy in Saudi Arabia, executive advisor positions, and industrial project leadership. His research interests focus on glass-ceramics, industrial waste valorization, dental and bioactive glasses, refractory ceramics, and radiation shielding applications, integrating both academic and industrial applications. He has been recognized with multiple awards, including national and international honors for research excellence, environmental management, and innovation, and holds patents related to high-performance basaltic glass and industrial glass marble production. He has supervised numerous Ph.D. and M.Sc. theses, contributed to international collaborations, and actively participates in professional societies such as the Mineralogical Society of Egypt and the Egyptian Geological Society. His research skill set includes materials characterization, crystallization studies, thermal and electrical property evaluation, and development of sustainable industrial applications from natural and industrial wastes. His work has achieved 1,163 citations by 896 documents, with 58 h-index and 20 documents, reflecting a high level of impact and international recognition in his field.

Profiles : ORCID | Scopus

Featured Publications

1. Khater, G. A., Abu Safiah, M. O., & Hamzawy, E. M. A. (2015). Augite-anorthite glass-ceramics from residues of basalt quarry and ceramic wastes. Processing and Application of Ceramics.

2. Khater, G. A., & Morsi, M. M. (2011). Glass-ceramics based on spodumene-enstatite system from natural raw materials. Thermochimica Acta.

3. Khater, G. A. (2010). Diopside-anorthite-wollastonite glass-ceramics based on waste from granite quarries. Glass Technology: European Journal of Glass Science and Technology Part A.

4. Khater, G. A. (2010). Glass-ceramics in the CaO-MgO-Al2O3-SiO2 system based on industrial waste materials. Journal of Non-Crystalline Solids.

5. Khater, G. A., & Idris, M. H. (2009). Effect of some nucleating agents on crystallizing phases and microstructure in Li2O-BaO-Al2O3-SiO2 system. Ceramics International.

Hatice Sena Cinarli | Physiotherapy | Best Researcher Award

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Assist. Prof. Dr. Hatice Sena Cinarli | Physiotherapy | Best Researcher Award

Assistant Professor | kocaeli Health and Technology University | Turkey 

Dr. Hatice Sena Çınarlı is an Assistant Professor of Physiotherapy and Rehabilitation at Kocaeli University of Health and Technology, where she also serves as Vice Dean of the Faculty of Health Sciences. She completed her BSc in Physiotherapy and Rehabilitation at Ege University, MSc in Cardiopulmonary Physiotherapy at Dokuz Eylül University, and PhD in Physiotherapy and Rehabilitation at İnönü University with a thesis on thoracolumbar fascia release and pulmonary function in stroke patients. Her professional experience includes teaching a wide range of courses such as cardiopulmonary rehabilitation, orthopedic rehabilitation, kinesiology, neurophysiological approaches, and ethics in physiotherapy, while actively contributing to administrative and academic leadership. Her research interests cover cardiopulmonary rehabilitation, neurophysiological rehabilitation, functional assessment, exercise-based interventions, disability care, and the integration of artificial intelligence and technology in rehabilitation practices. She has published several articles in international peer-reviewed and Scopus-indexed journals, authored book chapters, and presented research at global conferences. Recognized for her scholarly contributions, she is actively involved in collaborative research and community-oriented projects. Her research skills include designing and conducting clinical trials, applying physiotherapy evaluation methods, developing innovative rehabilitation protocols, and analyzing patient outcomes with evidence-based approaches. Through her academic achievements, research productivity, and leadership, she continues to advance physiotherapy and rehabilitation sciences while contributing significantly to both patient care and scientific knowledge.

Profile: ORCID

Featured Publication

1. Çınarlı, H. S., Tokgöz, G., Akyol, B., Aygören, C., Beykümül, A., Larsen, M. N., Krustrup, P., França, C., Gouveia, É. R., & Çınarlı, F. S. (2025). Associations between pulmonary function and muscle strength in Turkish national karate athletes. Journal of Clinical Medicine, 14(18), 6370.

Jun Peng | Big Data Analysis | Best Researcher Award

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Prof. Jun Peng | Big Data Analysis | Best Researcher Award

Professor | Ningbo University | China

Prof. Jun Peng is a distinguished scholar in the field of educational technology with expertise in big data in education, artificial intelligence in learning, blended learning, and curriculum design. He earned his PhD in Education from the University of Hong Kong and has built a strong academic career through teaching, research, and international collaborations. Currently serving as a professor and doctoral supervisor at Ningbo University, he has also contributed to the University of Hong Kong and the City University of Macau in research and teaching capacities. His professional experience includes leading several funded projects across China and Macau, with a focus on AI integration in education and innovative digital learning models. His research interests span online learning environments, project-based education, and sustainable approaches to technology-enhanced learning, reflected in numerous publications in leading SSCI, SCI, and Scopus-indexed journals such as Computers & Education, Education and Information Technologies, and Sustainability. Recognized with multiple commendations for research excellence, he has also received awards for educational innovation and course design. Prof. Peng is active in academic service as an editorial board member, peer reviewer for reputed journals, and keynote speaker at international conferences. His research skills include quantitative and qualitative analysis, big data applications, machine learning for education, and curriculum development. With a proven record of impactful research, leadership, and mentoring, he continues to advance the field of educational technology while contributing to the global academic community.

Profile: ORCID

Featured Publications

1.Shu, X., Peng, J., & Wang, G. (2023). Deciding alone or with others: Employment anxiety and social distance predict intuitiveness in career decision making. International Journal of Environmental Research and Public Health, 20(2), 1484.
2. Su, B., & Peng, J. (2023). Sentiment analysis of comment texts on online courses based on hierarchical attention mechanism. Applied Sciences, 13(7), 4204.
3. Zhou, J., Ran, F., Li, G., Peng, J., Li, K., & Wang, Z. (2022). Classroom learning status assessment based on deep learning. Mathematical Problems in Engineering, 2022, 7049458.
4. Peng, J., Yuan, B., Sun, M., Jiang, M., & Wang, M. (2022). Computer-based scaffolding for sustainable project-based learning: Impact on high- and low-achieving students. Sustainability, 14(19), 12907.
5. Li, Y., & Peng, J. (2022). Evaluation of expressive arts therapy on the resilience of university students in COVID-19: A network analysis approach. International Journal of Environmental Research and Public Health, 19(13), 7658.