Rana Ghazali | Data Science | Best Researcher Award

Published on by Computer Science Engineering

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.

Profiles: Google Scholar | Scopus | ORCID
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.

Alessandro Mazzoni | Data Science | Best Research Article Award

Published on by Computer Science Engineering

Dr. Alessandro Mazzoni | Data Science | Best Research Article Award

Chief of Transfusion Medicine U.O. at Azienda Ospedaliera Universitaria Pisana| Italy

The researcher demonstrates a remarkable level of excellence in the field of innovative translational medicine, particularly in the specialized areas of cord blood applications for neonatology and regenerative medicine. Their body of work reflects a thoughtful combination of laboratory experimentation with carefully designed clinical trials, ensuring that scientific discovery is meaningfully connected to patient benefit. This translational approach positions the researcher as someone capable of bridging gaps between bench and bedside, which is increasingly valued in modern medicine. A large and rigorous clinical study that evaluates the use of cord blood transfusions to reduce the risk of retinopathy of prematurity in extremely low gestational age infants. The study has already gained significant recognition, with multiple citations in a short period, underscoring its impact on pediatrics and transfusion medicine while also shaping neonatal care practices worldwide.

Professional Profile

Scopus 

Education

Although specific details of Dr. Alessandro Mazzoni’s medical education and academic training are not widely available in open sources, it is evident from his professional position and research leadership that he has undergone advanced medical and scientific training in transfusion medicine, hematology, and related clinical specialties. His role as Director of the Unit of Transfusion Medicine and Transplant Biology at the Azienda Ospedaliero-Universitaria Pisana (AOUP) suggests a strong foundation in medical sciences, clinical practice, and laboratory-based transfusion biology. Typically, such a career path involves a medical degree followed by specialization in hematology, immunohematology, or transfusion medicine, coupled with extensive postgraduate research experience. While his precise university affiliations and doctoral training are not explicitly published, his demonstrated competence in leading high-impact clinical research projects, managing critical hospital units, and contributing to innovative biomedical studies highlights a comprehensive educational background rooted in both clinical and translational medical sciences.

Experience

Dr. Alessandro Mazzoni serves as the Director of the Unit of Transfusion Medicine and Transplant Biology at the Azienda Ospedaliero-Universitaria Pisana (AOUP), located at the Cisanello campus in Pisa, Italy. In this leadership capacity, he coordinates the operational management of transfusion services, ensuring that the hospital maintains an adequate and safe supply of blood and plasma for surgical interventions, emergency departments, and outpatient services. His tenure has been marked by proactive initiatives designed to address blood shortages, including extraordinary weekend openings of the transfusion center, community-based campaigns, and collaborations with cultural organizations to promote blood donation awareness. Dr. Mazzoni has also guided his team in research-driven practices that align with the hospital’s mission to advance innovation in transplantation and transfusion science. His ability to balance administrative responsibility with direct involvement in scientific studies underscores his reputation as both a clinician and a healthcare innovator at AOUP.

Skills

Dr. Mazzoni’s professional skill set reflects a unique blend of clinical expertise, leadership ability, and research collaboration. As a transfusion medicine specialist, he possesses in-depth knowledge of blood component management, immunohematology, and transplant biology. His leadership skills are demonstrated through his capacity to oversee critical transfusion services while orchestrating large-scale public health campaigns to recruit blood and plasma donors during periods of shortage. He is highly skilled in fostering interdisciplinary collaboration, linking clinical practice with translational research in neonatal care, transplant immunology, and emerging biomedical technologies such as nanomedicine. Furthermore, his communication abilities enable him to engage effectively with the public, raising awareness about the importance of blood donation and ensuring sustained community participation. By combining administrative acumen, technical expertise, and a strong capacity for scientific collaboration, Dr. Mazzoni exemplifies the profile of a physician-scientist committed to advancing both patient care and biomedical innovation.

Research Focus

The research activities led or supported by Dr. Mazzoni reflect a strong orientation toward translational innovation in transfusion medicine and transplantation. His work has involved participation in studies exploring the use of cord blood-derived red cells to prevent retinopathy of prematurity in neonates, representing a significant advancement in neonatal intensive care. He has also contributed to pioneering investigations into nanoparticle-assisted organ perfusion, a cutting-edge strategy aimed at improving organ preservation and viability in transplant surgery. His team has been engaged in the development of novel therapeutic interventions during the COVID-19 pandemic, particularly monoclonal neutralizing antibodies, underscoring his capacity to pivot toward urgent healthcare challenges. These diverse research areas illustrate his commitment to bridging laboratory innovation with clinical application. Overall, Dr. Mazzoni’s research focuses on interventions that directly enhance patient outcomes, improve transplant success, and expand the clinical potential of advanced transfusion practices.

Awards 

Throughout his career, Dr. Alessandro Mazzoni has received significant recognition for his leadership and contributions to transfusion and transplant medicine. In 2019, under his directorship, the AOUP’s Unit of Transfusion Medicine and Transplant Biology received a prestigious award at the Italian Transplant Network’s National Congress for an outstanding abstract focused on immunogenetic analysis in kidney transplantation. This recognition highlighted the scientific rigor and collaborative spirit of his team. The AOUP’s Bone Marrow Donor Center, closely affiliated with his unit, was honored by the Italian Bone Marrow Donor Registry (IBMDR) for achieving the highest donor registration index nationwide. This award underscored the effectiveness of his team’s outreach efforts and their commitment to expanding life-saving donation networks. These accolades collectively reflect Dr. Mazzoni’s dual strengths as both a clinician and a scientific leader whose initiatives produce measurable national impact.

Publication Top Notes

Title: Cord blood transfusions in extremely low gestational age neonates to reduce severe retinopathy of prematurity: results of a prespecified interim analysis of the randomized BORN trial
Year: 2024
Citation: 14

Title: In vitro regenerative effects of a pooled pathogen-reduced lyophilized human cord blood platelet lysate for wound healing applications
Year: 2024
Citation: 1

Title: Clinical and Virological Response to Convalescent Plasma in a Chronic Lymphocytic Leukemia Patient with COVID-19 Pneumonia
Year: 2022
Citation: 5

Title: Carboxymethyl Cellulose-Based Hydrogel Film Combined with Umbilical Cord Blood Platelet gel as an Innovative Tool for Chronic Wound Management: A Pilot Clinical Study
Year: 2022
Citation: 3

Conclusion

Based on the strength, originality, and clinical relevance of the researcher’s contributions—particularly they are exceptionally well-suited for recognition through the Best Research Article Award. Their research not only presents novel biological concepts but also successfully translates these into clinical protocols with direct implications for patient outcomes. This ability to bridge scientific innovation with practical application is a rare quality that enhances their candidacy. Furthermore, the researcher’s focus on vulnerable populations, such as premature neonates and patients requiring regenerative therapies, highlights the humanitarian value of their work. By demonstrating measurable impact in both research citations and clinical relevance, they embody the qualities of an award-winning investigator. With ongoing dedication, enhanced international collaborations, and a continued emphasis on high-impact clinical studies, the candidate’s future contributions are poised to evolve into landmark research that will significantly influence global standards of healthcare and biomedical practice.

Ahsan Ali | Machine Learning | Best Researcher Award

Published on by Computer Science Engineering

Mr. Ahsan Ali | Machine Learning | Best Researcher Award

PhD Student at Tianjin University | Pakistan

Overall, Ahsan Ali emerges as a promising young researcher whose academic journey reflects both excellence and commitment to advancing the field of electrical power engineering. With a strong foundation laid through his master’s and bachelor’s degrees, he has already demonstrated the ability to translate theoretical knowledge into practical solutions. His expertise covers deep learning-based power quality disturbance classification, fault diagnosis in converters, power system protection, and renewable energy integration—areas that are of great importance in the current era of smart grids and sustainable power technologies. Beyond his academic pursuits, Ahsan has also gained valuable industrial exposure in sugar mills, cement factories, and large-scale power plants, which has enriched his applied perspective and problem-solving abilities. Furthermore, his active participation in IEEE activities, seminars, and conferences highlights his growing leadership potential. With sustained research productivity, strong collaborations, and a focus on impactful publications, Ahsan is well-prepared to become a leading figure in his domain.

Professional Profile

 Scopus 

Education

Ahsan Ali completed his Master’s degree in Electrical Power Engineering from Quaid-e-Awam University of Engineering, Science and Technology, Pakistan, with a strong academic record His master’s research was focused on the classification of power quality disturbances using advanced deep learning methods. The study addressed the increasing importance of reliable power system operation in modern electrical networks and explored the integration of Discrete Wavelet Transform and Multi-Resolution Analysis with one-dimensional convolutional neural networks. This work aimed to improve the accuracy of identifying and classifying disturbances such as sags, swells, harmonics, and transients that affect system reliability. He also earned a Bachelor of Electrical Engineering degree from the same institution. His undergraduate project involved modeling and simulating under-frequency relays for generator protection using MATLAB and Simulink, providing him with practical expertise in system reliability.

Experience

Ahsan Ali has developed a professional career in the field of electrical power systems through roles that combined technical responsibilities and applied industry learning. He worked as an Assistant Electrical Engineer at Khairpur Sugar Mills, where he supported the engineering team in resolving power disturbances, implementing protection schemes, and managing distribution systems. In a similar role at Rohri Cement Factory, he assisted in project planning and power management activities while ensuring smooth plant operations. He also gained valuable industrial training during internships at Zorlu Enerji Pakistan, where he observed wind turbine operations and grid station management, TNB Liberty Power Plant, where he studied combined cycle operations and turbine performance, and Jamshoro Power Company, where he familiarized himself with the functioning of large-scale thermal units. These experiences helped him build a strong foundation in energy production, distribution, and system reliability, combining both theoretical and practical aspects of electrical engineering in real environments.

Skills

Ahsan Ali possesses a wide range of technical and analytical skills that complement his academic and professional background in electrical engineering. He has advanced proficiency in MATLAB and Simulink for modeling, simulation, and analysis of power systems, as well as strong competence in programmable logic controller programming for industrial automation and protective arrangements. His expertise covers power system analysis, electrical distribution engineering, fault protection, renewable energy integration, and the design and control of electrical machines and drives. He has applied these skills in both academic research and industrial practice, focusing on optimizing system performance and ensuring reliability. Ahsan has also acquired certifications in advanced courses, including power system analysis, electrical distribution system engineering, and MATLAB applications. He completed specialized training in Typhoon HIL, gaining experience in power quality testing and power flow modeling. In addition, he has explored fields such as freelancing, WordPress, and graphic design to diversify his professional capabilities.

Research Focus

Ahsan Ali’s research focus centers on power system reliability and advanced diagnostic methods for modern electrical networks. His interests include fault diagnosis of high-power electronic converters, stability analysis, and the integration of renewable energy systems into existing grids. He has also worked extensively on the classification of power quality disturbances through the application of deep learning algorithms, which represents a significant contribution to intelligent power system monitoring. His publications highlight his dedication to advancing the field, with studies on PQD detection techniques, microgrid design for seaport operations, and classification models for system optimization. His research reflects a balance between theoretical development and applied engineering, addressing the challenges posed by distributed generation, energy transitions, and increasing demand for sustainable technologies. Through his projects, Ahsan has emphasized the importance of integrating artificial intelligence and machine learning into power systems to enhance fault detection, predictive maintenance, and operational decision-making.

Awards 

Ahsan Ali has earned recognition for his academic excellence, research contributions, and active participation in professional activities. He has received certificates of appreciation for organizing technical events and webinars, including recognition for his performance during the COVID-19 period, when he contributed to academic engagement through virtual platforms. He participated in poster competitions on power system fault diagnosis and was acknowledged by the IEEE QUEST Chapter for his contributions. His involvement in seminars and workshops includes presenting research on power quality disturbances classification and generator protection at national and institutional conferences, where he shared findings with peers and faculty. He has also attended multiple training programs and short courses related to industrial safety, renewable progress, technical writing, and research management. These experiences have strengthened his academic and professional profile. As an associate member of IEEE, Ahsan has demonstrated his commitment to professional growth and engagement with the global engineering community.

Publication Top Notes

Title: Comprehensive review of power quality disturbance detection and classification techniques
Journal: Computers and Electrical Engineering, Vol. 126, Article 110512

Title: Design and Analysis of Seaport Microgrid with Ship Loads
Journal: Proceedings of IEEE China International Youth Conference on Electrical Engineering (CIYCEE), Wuhan, China

Title: Power Quality Disturbances (PQDs) Classification Analyzed Based on Deep Learning Technique
Journal: Journal of Computing and Biomedical Informatics, Vol. 4, Issue 1

Title: Comparative Analysis of the PWM and SPWM on Three-Phase Inverter through Different Loads and Frequencies
Journal: Journal of Computing and Biomedical Informatics, Vol. 4, Issue 2, pp. 204–220

Conclusion

Ahsan Ali is a highly suitable and deserving candidate for the Best Researcher Award in Electrical Power Engineering, given the scope and relevance of his contributions. His research consistently bridges theoretical frameworks with real-world applications, particularly in areas such as power system reliability, renewable energy, and advanced control methods. These contributions underscore his ability to design innovative solutions that can enhance system stability and sustainability. Although there remains room for growth in terms of expanding his global research impact, securing patents, and publishing in more high-impact journals, his current record already reflects a blend of academic excellence and professional dedication. His consistent engagement with international conferences and reputed journals highlights his growing presence in the research community. With his career trajectory, it is evident that he embodies the qualities of an emerging researcher whose work contributes not only to scientific advancement but also to practical technological development, making him an ideal award recipient.