Mr. Ehab Elhosary | Vision and Language | Research Excellence Award

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Rim Bakhat | Benchmark Datasets and Evaluation Methods | Research Excellence Award

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Dr. Rim Bakhat | Benchmark Datasets and Evaluation Methods | Research Excellence Award

University of Malaga | Spain

Dr. Rim Bakhat is a researcher in economic sciences and sustainable development at Abdel Malek Essaadi University, specializing in sustainable logistics, supply chain management, and multi-criteria decision-making (MCDM). She has authored numerous peer-reviewed publications, with over , demonstrating solid academic impact. Her work integrates advanced methodologies such as AHP, VIKOR, and fuzzy systems to address real-world challenges in energy, transport, and manufacturing sectors. She has collaborated internationally, notably on tourism sustainability and blockchain adoption studies. Her research contributes to improving decision-making processes and promoting sustainable practices in emerging economies, aligning with global sustainability and digital transformation goals.

Citation Metrics (Scopus)

90

60

30

0

Citations
89

Documents
6

h-index
4

🟦 Citations 🟥 Documents 🟩 h-index

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Featured Publications


An application of fuzzy integrated model in green supplier selection.

– Mathematical Problems in Engineering, 2019, 4256359. (2019). Cited By: 44

Risk assessment of a wind turbine using an AHP-MABAC approach with grey system theory: A case study of Morocco.

– Mathematical Problems in Engineering, 2020, 2496914. (2020). Cited By: 22

An integrated CRITIC-VIKOR model for overtourism assessment in Spain: Post-COVID-19 sustainable actions.

– International Journal of Multicriteria Decision Making, 9(2), 87–107. (2022).  Cited By: 11

Yi Qian | Benchmark Datasets and Evaluation Methods | Research Excellence Award

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Prof. Yi Qian | Benchmark Datasets and Evaluation Methods | Research Excellence Award

University of British Columbia | Canada

Dr. Yi Qian is an accomplished researcher in econometrics, marketing science, and applied statistics, affiliated with the University of British Columbia. With a strong portfolio of peer-reviewed publications and several hundred citations, her work focuses on endogeneity correction, causal inference, and consumer behavior analytics. She has introduced advanced methodologies, including copula-based regressors and semiparametric estimation techniques, published in leading journals such as Journal of Marketing Research, Marketing Science, and Statistics in Medicine. Collaborating with scholars like Hui Xie and Fan Yang, her research delivers impactful insights for policy design, healthcare evaluation, and data-driven decision-making.

Citation Metrics (Scopus)

600

400

200

0

Citations
466

Documents
21

h-index
9

🟦 Citations 🟥 Documents 🟩 h-index

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        View Google Scholar Profile

Featured Publications


Impacts of entry by counterfeiters.

– The Quarterly Journal of Economics, 123(4), 1577–1609. (2008). Cited By: 218

Brand management and strategies against counterfeits.

– Journal of Economics & Management Strategy, 23(2), 317–343. (2014). Cited By: 168

Factors affecting the effectiveness of cause-related marketing: A meta-analysis.

– Journal of Business Ethics, 175(2), 339–360. (2022). Cited By: 120

Signaling virtuous victimhood as indicators of Dark Triad personalities.

– Journal of Personality and Social Psychology, 120(6), 1634–1661. (2021).  Cited By: 119

Usama Aslam | Benchmark Datasets and Evaluation Methods | Research Excellence Award

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Mr. Usama Aslam | Benchmark Datasets and Evaluation Methods | Research Excellence Award

Southeast University | China

Mr. Usama Aslam is an emerging researcher in Electrical Engineering at Southeast University, specializing in cyber-physical power systems, smart grid security, and Virtual Power Plants (VPP). He has authored and co-authored multiple publications, including peer-reviewed journal articles and several under-review works in leading outlets such as Elsevier and IEEE, with a growing citation record. His research integrates artificial intelligence, optimization, and energy systems to enhance grid resilience, battery longevity, and renewable integration. Through international collaborations, his work contributes to developing secure, efficient, and sustainable energy infrastructures, addressing critical challenges in modern power systems and supporting global energy transition goals.

Citation Metrics (Scopus)

15

10

5

0

Citations
10

Documents
6

h-index
2

🟦 Citations 🟥 Documents 🟩 h-index

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Featured Publications


Dual closed-loop vector PI control and deadbeat current control of permanent magnet synchronous motor.

– Sukkur IBA Journal of Emerging Technologies, 7(2), 40–56. (2024). Cited By; 5

Optimal scheduling of electric vehicle aggregators in residential areas: A cost minimization approach.

– Sukkur IBA Journal of Emerging Technologies, 8(1), 62–69. (2026). Cited By: 4

Nisharg Nargund | Document Image Analysis | Young Researcher Award

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Mr. Nisharg Nargund | Document Image Analysis | Young Researcher Award

Undergrad Researcher | Kalinga Institute of Industrial Technology | India

Mr. Nisharg Nargund is an emerging researcher in artificial intelligence and machine learning at the Kalinga Institute of Industrial Technology (KIIT), Bhubaneswar, India. His research focuses on large language models, retrieval-augmented generation, transformer architectures, and multi-agent AI systems. He has authored Ten scholarly and professional publications, with 2 Scopus-indexed documents receiving 19 citations and an h-index of 1. His work has been presented at leading international conferences, earning Best Paper and Best Poster awards. Through academic collaborations, industry internships, and open-source projects, his research contributes to scalable, ethical, and societally impactful AI solutions in education, language technology, and industry.

 

Citation Metrics (Scopus)

30

20

10

0

Citations
19

Documents
2

h-index
1

🟦 Citations 🟥 Documents 🟩 h-index

View Scopus Profile
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Featured Publications


Deep learning in Industry 4.0: Transforming manufacturing through data-driven innovation.

– In Distributed Computing and Intelligent Technology: 20th International Conference, ICDCIT 2024, Bhubaneswar, India, January 17–20, 2024, Proceedings. (2024). Cited By : 31

Conversational text extraction with large language models using retrieval-augmented systems.

– In Proceedings of the 6th International Conference on Computational Intelligence and Networks . (2025). Cited By : 5

Innovative fusion of LSTM and Bi-GRU networks for enhanced hate speech detection in social media.

– International Research Journal of Modernization in Engineering Technology and Science (IRJMETS). (2024). 

Emmanuel Ukekwe | Data Analytics | Best Researcher Award

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Dr. Emmanuel Ukekwe | Data Analytics | Best Researcher Award

Senior Lecturer | University of Nigeria | Nigeria

Dr. Emmanuel Ukekwe is a dedicated researcher and academic with expertise in artificial intelligence, expert systems, data science, computational programming, and software engineering, with a focus on applying intelligent technologies to solve societal problems. He obtained his Bachelor of Science in Computer/Statistics, Master of Science, and Ph.D. in Computer Science from the University of Nigeria, Nsukka, where he has grown into a respected lecturer and researcher. His professional journey includes roles as Senior Lecturer, Lecturer, and Instructor, as well as administrative positions such as Acting Head of Department and Acting Dean, demonstrating both academic and leadership excellence. His research interests span the application of machine learning and Python programming in data-driven problem solving, optimization models, recommender systems, and educational technologies. He has published extensively in recognized journals and conferences indexed in Scopus, covering healthcare systems, telecommunications, student performance, and COVID-19 analytics. He has been actively involved in university committees, curriculum development, and community-based research projects, and is a member of organizations such as the National Biotechnology Development Agency and the Technical Committee on UNESCO-HP projects. His skills include statistical analysis, software development, and advanced computational modeling, reflecting strong technical and analytical capabilities. His academic and research contributions have been recognized with professional memberships and community service engagements, marking him as an influential contributor to both academia and society. His research profile records 4 citations, 8 documents, and an h-index of 1.

Profiles: Google Scholar | Scopus | ORCID | ResearchGate

Featured Publications

  1. Okereke, G. E., Bali, M. C., Okwueze, C. N., Ukekwe, E. C., Echezona, S. C., & Ugwu, C. I. (2023). K-means clustering of electricity consumers using time-domain features from smart meter data. Journal of Electrical Systems and Information Technology, 10(1), 2.

  2. Ukekwe, E. C., Obayi, A. A., Johnson, A., Musa, D. A., & Agbo, J. C. (2025). Optimizing data and voice service delivery for mobile phones based on clients’ demand and location using affinity propagation machine learning. Journal of the Nigerian Society of Physical Sciences, 7(2), 2109.

  3. Ukekwe, E. C., Ezeora, N. J., Obayi, A. A., Asogwa, C. N., Ezugwu, A. O., Adegoke, F. O., Raiyetumbi, J., & Tenuche, B. (2025). Examining the impact of mathematics ancillary courses on computational programming intelligence of computer science students using machine learning techniques. Computer Applications in Engineering Education, 33(4), e70054.

  4. Ukekwe, E. C., Ogbonna, G. U. G., Adegoke, F. O., Okereke, G. E., & Asogwa, C. N. (2023). Clustering Nigeria’s IDP camps for effective budgeting and re-settlement policies using an optimized K-means approach. African Conflict & Peacebuilding Review, 13(2), 60–85.

  5. Okereke, G. E., Azegba, O., Ukekwe, E. C., Echezona, S. C., & Eneh, A. (2023). An automated guide to COVID-19 and future pandemic prevention and management. Journal of Electrical Systems and Information Technology, 10(1), 16.

Madhuri Rao | Machine Learning | Best Researcher Award

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Dr. Madhuri Rao | Machine Learning | Best Researcher Award

Senior Assistant Professor | MIT World Peace University | India

Dr. Madhuri Rao is a dedicated researcher and academic in computer science with expertise in wireless sensor networks, Internet of Things, artificial intelligence, blockchain, and cybersecurity, with her current work focusing on deep learning, cloud security, and healthcare applications. She earned her Ph.D. in Computer Science and Engineering from Biju Patnaik University of Technology, where her research emphasized energy-efficient object tracking in wireless sensor networks. Over her career, she has gained extensive professional experience as a faculty member, academic coordinator, research supervisor, and editorial board member, contributing significantly to both teaching and research. She has authored and co-authored numerous publications in reputed journals and conferences, including IEEE, Springer, Elsevier, and Scopus-indexed platforms, along with patents and book chapters that highlight her innovative approach. Her research interests span interdisciplinary applications of advanced technologies to address challenges in security, healthcare, and sustainability, with ongoing involvement in collaborative projects and international initiatives. She has received recognition through awards such as best paper honors and a best research scholar award, underscoring her contributions to the academic community. Her research skills include problem-solving, experimental design, data analysis, and guiding students at undergraduate, postgraduate, and doctoral levels, coupled with active roles as session chair, track chair, and guest lecturer in international conferences. She is also a life member of professional societies and holds certifications that strengthen her academic profile. Her impactful contributions are reflected in 116 citations and an h-index of 7.

Profile: Google Scholar | ORCID | ResearchGate | LinkedIn

Featured Publications

  1. Rao, M., & Kamila, N. K. (2021). Cat swarm optimization based autonomous recovery from network partitioning in heterogeneous underwater wireless sensor network. International Journal of System Assurance Engineering and Management, 1–15.

  2. Rao, M., Kamila, N. K., & Kumar, K. V. (2016). Underwater wireless sensor network for tracking ships approaching harbor. 2016 International Conference on Signal Processing, Communication, Power and Embedded System (SCOPES), 1098–1102. IEEE.

  3. Rao, M., & Kamila, N. K. (2018). Spider monkey optimisation based energy efficient clustering in heterogeneous underwater wireless sensor networks. International Journal of Ad Hoc and Ubiquitous Computing, 29(1–2), 50–63.

  4. Chaudhury, P., Rao, M., & Kumar, K. V. (2009). Symbol based concatenation approach for text to speech system for Hindi using vowel classification technique. 2009 World Congress on Nature & Biologically Inspired Computing (NaBIC), 1393–1396. IEEE.

  5. Kumar, K. V., Kumari, P., Rao, M., & Mohapatra, D. P. (2022). Metaheuristic feature selection for software fault prediction. Journal of Information and Optimization Sciences, 43(5), 1013–1020.

Reymark Delena | Data Analytics | Best Researcher Award

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Assist. Prof. Dr. Reymark Delena | Data Analytics | Best Researcher Award

Assistant Professor | Mindanao State University – Iligan Institute of Technology | Philippines

Assist. Prof. Dr. Reymark Delena is a dedicated researcher and academic with expertise in machine learning, IoT, climate informatics, data analytics, and smart systems. He earned a Master of Science in Information Technology from De La Salle University and a Bachelor’s degree in Information Systems from the University of Southern Mindanao, further supported by vocational training in ICT. He has served in various academic roles including Instructor, Assistant Professor, and currently contributes as a Senior Consultant in Smart Agriculture at PhilRice, while also engaging in teaching and mentoring at MSU. His professional journey includes roles as a software engineer and developer, providing him with a strong foundation in practical system development alongside research. His research interests cover smart agriculture, early detection systems, educational technologies, and sustainable digital solutions. He has actively participated in national and international conferences, presented research papers, and collaborated on funded projects such as RiceProTek and early fungal detection systems, reflecting his commitment to applied research with societal benefits. He possesses strong skills in programming, mobile and web development, data visualization, AI modeling, and technology management, making him versatile across academic and industry domains. His contributions have been recognized through invited talks, community workshops, and research forums, highlighting his academic leadership and service. His growing research impact is evident with 4 citations by 4 documents, 6 documents, and an h-index of 1.

Profile: Google Scholar | Scopus | ORCID

Featured Publications

  1. Ampuan, A. D., & Deleña, R. D. (2024). A quantitative evaluation of online appointment system at Mindanao State University–Main Campus: Employing the system usability scale (SUS) and technology acceptance model (TAM). Proceedings of the 3rd International Conference on Digital Transformation and Applications (ICDXA).

  2. Delena, R. D., Tangkeko, M. S., & Sieras, J. C. (2023). From climate to crop: Unveiling the impact of agro-climate dataset on rice yield in Cotabato Province. Data in Brief, 51, 109754.

  3. Delena, R. D., Tangkeko, M. S., Ampuan, A. D., & Sieras, J. C. (2023). ARP Cotabato: Exploring seasonal climate and rice production in Cotabato Province through advanced data visualization and rapid analytics. Software Impacts, 17, 100546.

  4. Dia, N. J., Sieras, J. C., Khalid, S. A., Macatotong, A. H. T., Mondejar, J. M., & Delena, R. D. (2025). EduGuard RetainX: An advanced analytical dashboard for predicting and improving student retention in tertiary education. SoftwareX, 29, 102057.

  5. Gulam, S. B., & Delena, R. D. (2024). The development of a web-based Meranaw language lexicon using a rule-based morphological analyzer for Meranaw verbs: Dindiyorobasa App. Proceedings of the 3rd International Conference on Digital Transformation and Applications (ICDXA).

Dr. Moorthi K | Data Analytics | Best Researcher Award

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Dr. Moorthi K, Data Analytics, Best Researcher Award

Doctorate at Dr.N.G.P. Institute of Technology, India

Professional Profile

🌟 Summary:

Dr. K. Moorthi is an Associate Professor at Dr. N.G.P. Institute of Technology with 16 years of teaching and 1 year of industry experience. He holds a Ph.D. in Information and Communication Engineering from Anna University, Chennai, specializing in the impact of data science on the e-commerce industry. Dr. Moorthi has published extensively, with several papers indexed in Scopus, and holds multiple patents.

🎓 Education:

  • Ph.D. in Information and Communication Engineering, Anna University, Chennai, 2019
  • Masters in Software Engineering, 2010

💼 Professional Experience:

  • Associate Professor, Dr. N.G.P. Institute of Technology

🔬 Research Interests:

  • Data Science, specifically focusing on the e-commerce industry

📖 Publications Top Noted:

Paper Title: Electric Vehicles Charging System for Fast and Safe Charging using LSTM based Gradient Boosted Regression Tree
  • Authors: Moorthi, K.; Chougale, R.K.; Patel, P.A.; Raj, A.; Gangat, M.S.
  • Pages: 1289–1294
  • Year: 2023
  • Citations: 4
Paper Title: XAI Based Intelligent Systems for Society 5.0
  • Authors: Kiruthika, M.; Moorthi, K.; Anousouya Devi, M.; Abijah Roseline, S.
  • Pages: 295–326
  • Year: 2023
Paper Title: Human Activity Recognition in Video Surveillance Using Long-Term Recurrent Convolutional Network
  • Authors: Moorthi, K.; Kiruthika, M.; Sharan, S.; Muleva, A.
  • Pages: 1477–1482
  • Year: 2023
Paper Title: Novel Method for Recognizing Sign Language using Regularized Extreme Learning Machine
  • Authors: Moorthi, K.; Asokan, A.; Sri Sathya, K.B.; Kalpana, V.; Rastogi, R.
  • Pages: 434–440
  • Year: 2023
Paper Title: Improving business process by predicting customer needs based on seasonal analysis: The role of big data in e-commerce
  • Authors: Moorthi, K.; Srihari, K.; Karthik, S.
  • Journal: International Journal of Business Excellence
  • Pages:561–574
  • Year: 2020
  • Citations: 3