Rana Ghazali | Data Science | Best Researcher Award

Dr. Rana Ghazali | Data Science | Best Researcher Award

Researcher |McMaster University | Iran

Dr. Rana Ghazali focuses on advancing intelligent computing systems through the integration of machine learning, reinforcement learning, and large language models to optimize big data and distributed computing environments. Her work bridges the domains of cloud computing, Hadoop-based systems, and intelligent caching to enhance computational performance and resource utilization in large-scale data frameworks. She has contributed to innovative algorithms such as CLQLMRS and H-SVM-LRU for improving cache locality and intelligent cache replacement in MapReduce job scheduling, combining machine learning with distributed system optimization. Rana’s research also extends to the design and analysis of routing protocols in mobile ad hoc networks, leveraging bio-inspired algorithms such as the Ant Colony Optimization method to improve network efficiency. Her current exploration includes the application of reinforcement learning in scheduling and performance enhancement for distributed computing platforms, with additional attention to emerging paradigms like edge, fog, and serverless computing. As a researcher affiliated with the Resource Allocation and Stochastic Systems Lab at McMaster University, she contributes to cutting-edge discussions on adaptive data management, cyber and network security, and intelligent system design. Rana’s expertise further encompasses data analytics, large language models, and the intersection of artificial intelligence with real-world computing challenges. She has served as a reviewer for leading international journals including Elsevier and Wiley publications and has participated in academic collaborations that explore deep learning and resource optimization in distributed architectures. Her research endeavors consistently emphasize scalable, secure, and intelligent computational systems that advance the performance of modern data-intensive applications. Rana Ghazali has 13 citations, 2 documents, and an h-index of 2.

Featured Publication

Ghazali, R., Down, D. G. (2025). Smart data prefetching using KNN to improve Hadoop performance. EAI Endorsed Transactions on Scalable Information Systems, 12(3). Cited by 1

Ghazali, R., Adabi, S., Rezaee, A., Down, D. G., & Movaghar, A. (2023). Hadoop-oriented SVM-LRU (H-SVM-LRU): An intelligent cache replacement algorithm to improve MapReduce performance. arXiv preprint arXiv:2309.16471. Cited by 2

Ghazali, R., Adabi, S., Rezaee, A., Down, D. G., & Movaghar, A. (2022). CLQLMRS: Improving cache locality in MapReduce job scheduler using Q-learning. Journal of Cloud Computing, 9. Cited by 9

Ghazali, R., Adabi, S., Down, D. G., & Movaghar, A. (2021). A classification of Hadoop job schedulers based on performance optimization approaches. Cluster Computing, 24(4), 3381–3403. Cited by 11

Ghazali, R., Down, D. G. (2025). A systematic overview of caching mechanisms to improve Hadoop performance. Concurrency and Computation: Practice and Experience, 37(25–26), e70337.

Dr. Devbrat Pundhir | Artificial Intelligence | Best Researcher Award

Dr. Devbrat Pundhir | Artificial Intelligence | Best Researcher Award

Assoc.Prof.Dr at Raja Balwant Singh Engineering Technical Campus, India

Dr. Devbrat Pundhir has consistently contributed to the understanding of ionospheric behavior under seismic influences through a series of well-structured, peer-reviewed studies. His commitment to exploring the physics behind electromagnetic precursors and TEC variations makes his research both scientifically rigorous and societally relevant. His innovations in methodology, especially his move towards AI integration and data-centric modeling, reflect his adaptability and forward-thinking approach.

Professional Profile

Google Scholar | Scopus | Orcid Profile

Education

Dr. Devbrat Pundhir holds a Ph.D. in Physics from Banasthali Vidyapith (Deemed University), awarded in 2018, with his thesis focused on ionospheric perturbations due to earthquakes using GPS-based Total Electron Content (TEC) measurements. He earned his M.Sc. in Physics from Dayalbagh Educational Institute (Deemed University), Agra, in 2012 with 70.1% marks. Prior to that, he completed his B.Sc. (Hons.) in Physics from the same institute in 2010, securing 68.9%. His early education was completed under the U.P. Board, where he passed his Intermediate in 2007 and High School in 2005, both with First Division.

Experience

Currently, Dr. Pundhir serves as an Assistant Professor of Physics in the Department of Applied Sciences & Humanities at Raja Balwant Singh Engineering Technical Campus, Bichpuri, Agra, since January 2019. Previously, he worked as a Senior Research Fellow on a Ministry of Earth Sciences-sponsored project related to electromagnetic earthquake precursors at the Seismo-electromagnetics and Space Research Laboratory (SESRL), Agra, from 2016 to 2018, where he also taught undergraduate Engineering Physics. He earlier served as a Junior Research Fellow in a Department of Science & Technology project on Schumann Resonance phenomena. His early research experience also includes work in fiber optics, nonlinear behavior of inorganic materials, and nanostructures under the guidance of Dr. Sukhdev Roy during his M.Sc. Additionally, he has experience as a video editor in an MHRD project at Dayalbagh Educational Institute.

Skills and Expertise

Dr. Pundhir possesses strong analytical and technical skills in atmospheric physics, signal processing, and modeling using AI/ML techniques. He has hands-on expertise in GPS-TEC data analysis, ULF/VLF ground measurements, and ionospheric modeling. He has also designed a biosensor in fiber optics and conducted research on carbon nanotubes and iron oxide materials. His computer skills include certified proficiency in Computer Concepts by NIELIT and three years of practical experience in computer applications. He has developed attainment calculation software and has served as a resource for IPR and innovation-related activities in his institution.

Research Focus

Dr. Pundhir’s primary research areas lie in seismo-electromagnetics, low-latitude ionospheric modeling, and earthquake precursor detection using TEC and electromagnetic signals. His ongoing projects focus on AI-based prediction of ionospheric behavior and synthesis of metallic nanostructures. His work also explores the coupling of atmospheric and ionospheric parameters during seismic events and the use of satellite and ground-based tools for early warning systems. He has published over 35 international journal articles, co-supervised Ph.D. students, and contributed significantly to interdisciplinary research involving geophysics, space weather, and machine learning applications.

Awards and Honors

Dr. Pundhir has been recognized widely for his academic and research contributions. He has served on the Technical Program Committees of various international conferences in China and India and was appointed as Chair for multiple events. He is a life member of the Indian Geophysical Union and serves on editorial boards of international journals like the SCIREA Journal of Environment and Geosciences. He has received multiple certifications from AICTE, the Ministry of Education, and international FDPs on AI, teaching methods, and instrumentation. He has mentored students for projects funded by INSPIRE and AICTE and contributed actively to institutional innovation and IPR policies.

Publication

  • Title: Anomalous TEC variations associated with the strong Pakistan-Iran border region earthquake of 16 April 2013 at a low latitude station Agra, India
    Authors: D. Pundhir, B. Singh, O.P. Singh
    Journal: Advances in Space Research
    Year: 2014
    Citations: 30

 

  • Title: Ionospheric perturbations due to earthquakes as determined from VLF and GPS-TEC data analysis at Agra, India
    Authors: D. Singh, B. Singh, D. Pundhir
    Journal: Advances in Space Research
    Year: 2018
    Citations: 21

 

  • Title: Study of ionospheric precursors using GPS and GIM-TEC data related to earthquakes occurred on 16 April and 24 September, 2013 in Pakistan region
    Authors: D. Pundhir, B. Singh, O.P. Singh, S.K. Gupta, S.P. Karia, K.N. Pathak
    Journal: Advances in Space Research
    Year: 2017
    Citations: 19

 

  • Title: A multi-experiment approach to ascertain electromagnetic precursors of Nepal earthquakes
    Authors: S. Sharma, R.P. Singh, D. Pundhir, B. Singh
    Journal: Journal of Atmospheric and Solar-Terrestrial Physics
    Year: 2020
    Citations: 15

 

  • Title: A morphological study of low latitude ionosphere and its implication in identifying earthquake precursors
    Authors: D. Pundhir, B. Singh, O.P. Singh, S.K. Gupta
    Journal: J. Ind. Geophys. Union
    Year: 2017
    Citations: 10

Conclusion

In conclusion, Dr. Pundhir is a highly deserving candidate for the Best Researcher Award. His pioneering work on seismo-ionospheric precursors, broad publication record, and his ongoing evolution into interdisciplinary modeling highlight his scientific maturity and future leadership potential. Recognizing him with this award would not only honor his current achievements but also encourage further innovation in disaster prediction science.

Dr. Hui Yu | Data Science | Best Innovation Award

Dr. Hui Yu | Data Science | Best Innovation Award

Assoc.Prof.Dr at Institute of Mountain Hazards and Environment, CAS, China

Assoc. Prof. Dr. Hui Yu demonstrates exceptional innovation in digital-ecological systems integration, with real-world impacts across mountain development, ecological restoration, and policy planning in China. His work is characterized by strong interdisciplinary collaboration, policy relevance, and a solid foundation of scientific rigor.

Professional Profile

Education

While specific degree details were not explicitly listed, Assoc. Prof. Dr. Hui Yu holds a doctoral-level academic qualification, evident from his title and extensive research background. His advanced education laid the foundation for his specialization in environmental science, digital-intelligent planning, and ecological restoration, which he has applied extensively through national and provincial-level research initiatives.

Experience

Assoc. Prof. Dr. Hui Yu currently serves as the Deputy Director of the Technology Innovation Center for Southwest Land Space Ecological Restoration and Comprehensive Renovation, Ministry of Natural Resources (MNR), China. He is affiliated with the Institute of Mountain Hazards and Environment, Chinese Academy of Sciences. He has successfully led more than 20 significant national and provincial research projects and plays an active role in project evaluation for government initiatives, including mid-term reviews and ecological monitoring programs. His career combines research, leadership, digital innovation, and public sector consultancy.

Skills and Expertise

Dr. Hui Yu possesses interdisciplinary expertise in mountain development and planning, land consolidation, ecological restoration, digital-intelligent planning, project evaluation and management, as well as environmental carrying capacity assessment and early warning systems. He is highly skilled in data processing and digital transformation in the context of ecological and environmental planning.

Research Focus

His research is primarily centered around ecological and spatial restoration in mountainous regions, with an emphasis on comprehensive land planning. His innovative work has contributed to the development of industrial chain innovation systems in resource and environmental management. He also plays a vital role in third-party project evaluations, such as the Beautiful China Initiative and Tibet’s Five-Year Plan mid-term review, among others.

Awards and Honors

Dr. Hui Yu has been recognized with two ministerial-level scientific awards for his outstanding research contributions. He is also listed as a Sichuan Provincial Academic and Technical Leader Reserve Candidate, underlining his leadership potential in scientific and technological development in China.

Publication

  • Effects of Comprehensive Land Consolidation on Farmers’ Livelihood Under Different Terrain Gradients
    Authors: Rongshan Wan, Hui Yu, Dan Zhang, Bo Yang, Yanhong Huang
    Journal: Land
    Year: 2025
    Citations: Not yet cited (newly published)

 

  • Grass-Livestock Balance-Based Grassland Ecological Carrying Capability and Sustainable Strategy in the Yellow River Source National Park, Tibet Plateau, China
    Authors: Hui Yu, Bin-tao Liu, Gen-xu Wang, Tong-zuo Zhang, Yan Yang, Ya-qiong Lu, You-xue Xu, Min Huang, Yi Yang, Lv Zhang
    Journal: Journal of Mountain Science
    Year: 2021
    Citations: 27 citations

 

  • Driving Forces for the Spatial Reconstruction of Rural Settlements in Mountainous Areas Based on Structural Equation Models: A Case Study in Western China
    Authors: Jia Zhong, Shaoquan Liu, Min Huang, Sha Cao, Hui Yu
    Journal: Land
    Year: 2021
    Citations: 15+ citations

 

  • Water-Facing Distribution and Suitability Space for Rural Mountain Settlements Based on Fractal Theory, South-Western China
    Authors: Hui Yu, Yong Luo, Pengshan Li, Wei Dong, Shulin Yu, Xianghe Gao
    Journal: Land
    Year: 2021
    Citations: 10+ citations

 

  • Territorial Suitability Assessment and Function Zoning in the Jiuzhaigou Earthquake-Stricken Area
    Authors: Hui Yu, Miao Qiang, Shao-quan Liu
    Journal: Journal of Mountain Science
    Year: 2019
    Citations: 24 citations

Conclusion

Highly Recommended for the Best Innovation Award. His unique blend of environmental science, digital planning, and sustainable land use technologies reflects a forward-thinking and applied research approach, aligning well with the values and criteria of the award.