Zhaozhen Jiang | Computer Science | Best Research Article Award

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Dr. Zhaozhen Jiang | Computer Science | Best Research Article Award

Assistant Researcher | Naval Submarine Academy | China

Dr. Zhaozhen Jiang is a distinguished researcher at the Navy Submarine Academy in Qingdao, China, specializing in intelligent systems, maritime navigation, and dynamic target search. His research focuses on the development of advanced path-planning algorithms and neural network–based optimization techniques for complex maritime environments. He has published extensively and collaborated widely with researchers across multiple disciplines, reflecting a strong commitment to interdisciplinary innovation. His recent work on GBNN-based maritime dynamic target search demonstrates a focus on enhancing operational decision-making and situational awareness in challenging naval contexts. Through his research, he aims to advance autonomous maritime systems and contribute to safer, more efficient naval operations, while fostering technological progress with meaningful societal impact.

Citation Metrics (Scopus)

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37

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Featured Publications

Sarbajit Paul Bappy | Computer Science | Research Excellence Award

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Mr. Sarbajit Paul Bappy | Computer Science | Research Excellence Award

Teaching Assistant | Daffodil International University | Bangladesh

Sarbajit Paul Bappy is an emerging researcher in computer science with a growing focus on applied machine learning, medical image analysis, and agricultural informatics. He is currently serving as a Teaching Assistant in the Department of Computer Science and Engineering at Daffodil International University, Bangladesh, where he has been contributing to academic instruction and research support since 2025. Alongside his professional role, he is pursuing his undergraduate degree in Computer Science and Engineering at the same institution, demonstrating a strong integration of academic excellence and early-career research productivity. His scholarly work includes peer-reviewed publications and openly accessible datasets that address critical challenges in healthcare diagnostics and smart agriculture. Notably, he co-authored SkinVisualNet: A Hybrid Deep Learning Approach Leveraging Explainable Models for Identifying Lyme Disease from Skin Rash Images (MAKE, 2025), which combines deep learning with explainable AI techniques to enhance early disease detection. He also contributed significantly to the dataset Jackfruit AgroVision, a comprehensive benchmark for disease detection in jackfruit and its leaves, supporting advancements in precision agriculture and food-security research. His collaborations span multidisciplinary teams involving experts such as Amir Sohel, Rittik Chandra Das Turjy, Md Assaduzzaman, Ahmed Al Marouf, Jon George Rokne, and Reda Alhajj, illustrating his ability to contribute within diverse international research groups. Through his ongoing work in AI-driven health diagnostics, dataset development, and sustainable agricultural technology, Bappy aims to advance research that supports societal well-being, improves disease detection accuracy, and contributes to innovation within global machine learning communities.

Profiles: Google Scholar | ORCID | LinkedIn

Featured Publications

1. Sohel, A., Turjy, R. C. D., Bappy, S. P., Assaduzzaman, M., Marouf, A. A., Rokne, J. G., & Alhajj, R. (2025). SkinVisualNet: A Hybrid Deep Learning Approach Leveraging Explainable Models for Identifying Lyme Disease from Skin Rash Images. Machine Learning and Knowledge Extraction, 7(4), 157. https://doi.org/10.3390/make7040157  MDPI+1

2. Sohel, A., Bijoy, M. H. I., Turjy, R. C. D., & Bappy, S. P. (2025). Jackfruit AgroVision: A Extensive Dataset for Jackfruit Disease and Leaf Disease Detection using Machine Learning. Mendeley Data. https://doi.org/10.17632/pt647jfn52.1

Lili Zhan | Artificial Intelligence | Best Researcher Award

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Assoc. Prof. Dr. Lili Zhan | Artificial Intelligence | Best Researcher Award

Associate Professor| Shandong University of Science and Technology | China

Assoc. Prof. Dr. Lili Zhan is a researcher whose work spans remote sensing, Arctic cryosphere monitoring, computer vision, and artificial intelligence–enhanced educational systems. Her scholarship incorporates both physical environmental analysis and advanced data-driven methodologies, with representative contributions including sensitivity analyses of microwave brightness temperature to variations in snow depth on Arctic sea ice, a deep-learning-based remote-sensing scene-classification framework employing EfficientNet-B7, and an improved YOLOv7 instance-segmentation method for ship detection in complex SAR imagery Lili-Zhan. She has also contributed to the design and implementation of intelligent teaching models grounded in contemporary AI and data-centric approaches, demonstrating interdisciplinarity across geospatial sciences and educational technology Lili-Zhan Across these domains, her work reflects a sustained commitment to methodological innovation, integrating state-of-the-art neural architectures with domain-specific challenges in environmental monitoring and maritime situational awareness. Her collaborations often bridge academic research groups focused on cryosphere change, Earth observation, and applied machine learning, enabling the development of tools that support improved climate understanding, maritime safety, and digital-education modernization. Although publication and citation metrics are not specified in the available document, the range of research topics and representative studies indicates a growing scholarly profile with contributions positioned at the intersection of remote-sensing physics and intelligent systems engineering. Collectively, her work holds global societal relevance: enhancing the accuracy of cryospheric measurements supports climate-model improvement and polar-region policy planning; advancing ship-detection techniques contributes to marine governance, environmental protection, and emergency response; and promoting AI-supported pedagogical frameworks aids the digital transformation of education.

Profile: Scopus 

Featured Publications

Zhan, L. (Year). SAR ship target instance segmentation based on SISS-YOLO. Journal Name, Volume(Issue), pages.

Lili Zhan’s work advances the precision of remote-sensing analytics and intelligent detection systems, strengthening global capabilities in environmental monitoring and maritime safety. Her innovations support science-driven decision-making with direct benefits for climate resilience and societal securit

Mona Almutairi | Artificial Intelligence | Best Researcher Award

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Ms. Mona Almutairi | Artificial Intelligence | Best Researcher Award

Shaqra University | Saudi Arabia

Ms. Mona Almutairi is a highly motivated computer science graduate with a strong academic foundation and practical experience in system engineering and data management. She completed her Bachelor’s degree in Computer Science from Shaqra University in 2019 with an impressive GPA of 4.19 out of 5, demonstrating consistent academic excellence. Her professional experience includes serving as a System Engineer at the Ministry of Economy and Planning, where she contributed to optimizing systems operations and enhancing digital workflows, as well as volunteering as a Data Entry Assistant at the Ministry of Health, where she efficiently managed and organized large datasets with accuracy and confidentiality. She further enriched her technical expertise through professional courses in Software Engineering from the Saudi Digital Academy and Web Development from the Ministry of Communications and Information Technology, equipping her with up-to-date industry knowledge and coding proficiency. Her research interests lie in software development, data analysis, and emerging technologies that integrate innovation with societal advancement. Ms. Almutairi’s research skills include proficiency in data analysis tools, problem-solving, and the ability to apply algorithmic thinking to real-world challenges. She is also adept at using Microsoft Office and has strong communication, teamwork, and adaptability skills, making her a collaborative and reliable professional. Her dedication to learning and excellence has been recognized through various academic and professional achievements, reflecting her commitment to continuous improvement. Overall, Ms. Almutairi is a forward-thinking computer scientist who combines technical knowledge, analytical capabilities, and professional experience to drive innovation in the field of information technology.

Profiles: Google Scholar | ORCID

Featured Publications

Almutairi, M., & Dardouri, S. (2025). Intelligent hybrid modeling for heart disease prediction. Information, 16(10), 869. Citations: 1

CHENGZU DONG | Computer Science | Best Researcher Award

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Prof . CHENGZU DONG | Computer Science | Best Researcher Award

Assistant Professor at Lingnan University , Hong Kong

Dr. Chengzu Dong is a highly accomplished early-career researcher specializing in cybersecurity, AI, blockchain, IoT, UAVs, and edge computing. Currently an Assistant Professor at Lingnan University, he has published over 30 peer-reviewed papers in prestigious Q1 journals and Core A/A* conferences, showcasing his strong research productivity and interdisciplinary expertise. His collaborations with CSIRO and industry partners reflect a robust blend of academic rigor and applied impact. Dr. Dong has received multiple accolades, including best paper awards, hackathon honors, and scholarships, highlighting his innovation and leadership potential. In addition to research, he has made significant contributions to teaching, mentoring, and curriculum development across several international institutions. While he could further enhance his profile through principal investigator roles and broader international visibility, his achievements and contributions make him a strong candidate for the Best Researcher Award, particularly in emerging areas of intelligent systems, secure computing, and next-generation network technologies.

Professional Profile 

Education🎓

Dr. Chengzu Dong has a strong and diverse educational background in computer science and information technology. He earned his Ph.D. from Deakin University, Australia, specializing in blockchain, AI, UAVs, edge computing, IoT, Web3, and the Metaverse. During his Ph.D. studies (2021–2024), he conducted extensive research in next-generation technologies, contributing significantly to academic and applied fields. Prior to that, he completed a Bachelor of Computer Science (Honours) at Swinburne University of Technology in 2020, where he deepened his expertise in software development and systems engineering. He also holds a Bachelor of Information Technology from Deakin University (2016–2019), which laid the foundation for his interests in cybersecurity and emerging technologies. His education reflects a consistent focus on interdisciplinary innovation and a strong grounding in both theoretical knowledge and practical applications. Dr. Dong’s academic journey across top Australian universities has prepared him well for a career in high-impact, technology-driven research and teaching.

Professional Experience📝

Dr. Chengzu Dong brings a rich and diverse professional background in academia, research, and industry. He is currently serving as an Assistant Professor at Lingnan University, Hong Kong, where he teaches and develops courses in blockchain, data mining, machine learning, and cybersecurity. Prior to this, he held multiple academic roles at Deakin University, including seminar lecturer, academic tutor, course developer, and capstone mentor, contributing significantly to curriculum innovation and student mentorship. His research experience includes collaborations with CSIRO, Australia’s leading scientific agency, where he worked on blockchain and AI projects. He also held positions as a research assistant at Swinburne University and Deakin University, and worked in software development roles at Artchain Global, Creative Geelong, and FPT Software. These roles highlight his strong technical skills and ability to bridge academia and industry. Dr. Dong’s professional journey reflects a well-rounded portfolio of teaching, research, and applied innovation in emerging technologies.

Research Interest🔎

Dr. Chengzu Dong’s research interests lie at the intersection of emerging technologies and intelligent systems, with a strong focus on cybersecurity, blockchain, artificial intelligence (AI), Internet of Things (IoT), unmanned aerial vehicles (UAVs), edge computing, Web3, and the Metaverse. His work aims to address critical challenges in data privacy, secure communication, and decentralized systems through the integration of blockchain and federated learning frameworks. He is particularly passionate about developing secure and efficient architectures for UAV delivery systems and smart edge networks, making his research highly relevant to real-world applications. Dr. Dong’s interdisciplinary approach combines theoretical advancements with practical implementations, as demonstrated by his collaborations with CSIRO and numerous industry partners. His contributions not only advance academic knowledge but also provide innovative solutions to pressing technological issues in digital security and autonomous systems. This diverse and forward-looking research portfolio positions him as a thought leader in next-generation computing and intelligent infrastructure.

Award and Honor🏆

Dr. Chengzu Dong has received numerous awards and honors in recognition of his academic excellence, research impact, and innovative contributions to emerging technologies. He was the recipient of the prestigious Deakin University Postgraduate Research Scholarship and a CSIRO Top-up Scholarship, supporting his advanced research in blockchain and AI. His work has earned best paper awards at international conferences such as IEEE IAS GLOBCONHT 2023, and he has achieved first runner-up prizes in blockchain hackathons in both Thailand and Australia. Dr. Dong is a certified member of the Australian Computer Society and holds various professional certifications, including Cisco CCNET and Certificate IV in Training and Assessment. His academic excellence was further recognized with the Golden Key Top 15% Student Award. He has also received recognition as a journal and conference reviewer, including a free ACM membership. These accolades collectively highlight his leadership, innovation, and dedication to research excellence and professional development.

Research Skill🔬

Dr. Chengzu Dong possesses a comprehensive set of research skills that span theoretical development, applied experimentation, and interdisciplinary collaboration. He is highly proficient in blockchain technology, artificial intelligence, federated learning, and cybersecurity frameworks, with a particular focus on secure systems for UAVs and edge computing environments. Dr. Dong demonstrates strong technical expertise in programming languages such as Python, Node.js, and React, along with experience in data analytics, machine learning model development, and system architecture design. His ability to design privacy-preserving frameworks and implement decentralized solutions reflects his strength in combining research theory with practical outcomes. Additionally, his experience working with organizations like CSIRO showcases his capability to collaborate on large-scale, real-world projects. Dr. Dong is also skilled in academic writing and publishing, with over 30 high-quality publications in top-tier journals and conferences. His strong analytical mindset, problem-solving ability, and innovation make him a highly capable and impactful researcher in advanced computing domains.

Conclusion💡

Dr. Chengzu Dong exemplifies the qualities of an outstanding researcher and academic, making him a highly suitable candidate for the Best Researcher Award. His extensive contributions to cutting-edge areas such as blockchain, AI, cybersecurity, and UAV systems reflect both depth and breadth in research expertise. With over 30 high-impact publications, multiple international awards, and active collaborations with renowned institutions like CSIRO, Dr. Dong has demonstrated consistent research excellence and innovation. His ability to translate theoretical knowledge into practical solutions for real-world challenges, especially in emerging technologies, underscores his relevance and leadership in the field. Additionally, his dedication to teaching and mentoring at multiple universities enhances his influence in shaping future researchers and professionals. Dr. Dong’s interdisciplinary skills, academic achievements, and forward-thinking research agenda not only position him as a leader in his domain but also affirm his deserving candidacy for this prestigious recognition.

Publications Top Noted✍

  • Title: BBM: A Blockchain-Based Model for Open Banking via Self-Sovereign Identity
    Authors: C. Dong, Z. Wang, S. Chen, Y. Xiang
    Year: 2020
    Citations: 32

  • Title: A Novel Security Framework for Edge Computing Based UAV Delivery System
    Authors: A. Yao, F. Jiang, X. Li, C. Dong, Y.X. Jia, X.L. Gang Li
    Year: 2021
    Citations: 28

  • Title: Enhancing Quality of Service Through Federated Learning in Edge-Cloud Architecture
    Authors: J. Zhou, S. Pal, C. Dong, K. Wang
    Year: 2024
    Citations: 22

  • Title: A Blockchain-Aided Self-Sovereign Identity Framework for Edge-Based UAV Delivery System
    Authors: C. Dong, F. Jiang, X. Li, A. Yao, G. Li, X. Liu
    Year: 2021
    Citations: 20

  • Title: Optimizing Performance in Federated Person Re-Identification Through Benchmark Evaluation for Blockchain-Integrated Smart UAV Delivery Systems
    Authors: C. Dong, J. Zhou, Q. An, F. Jiang, S. Chen, L. Pan, X. Liu
    Year: 2023
    Citations: 15

  • Title: Continuous Authentication for UAV Delivery Systems Under Zero-Trust Security Framework
    Authors: C. Dong, F. Jiang, S. Chen, X. Liu
    Year: 2022
    Citations: 15

  • Title: A Privacy-Preserving Location Data Collection Framework for Intelligent Systems in Edge Computing
    Authors: A. Yao, S. Pal, X. Li, Z. Zhang, C. Dong, F. Jiang, X. Liu
    Year: 2024
    Citations: 11

  • Title: A Framework for User Biometric Privacy Protection in UAV Delivery Systems with Edge Computing
    Authors: A. Yao, S. Pal, C. Dong, X. Li, X. Liu
    Year: 2024
    Citations: 11

Muhsin Vanolya | Engineering | Best Researcher Award

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Dr. Muhsin Vanolya | Engineering | Best Researcher Award

General Manager at Su Ekosistem Enerji, Turkey

Muhsin Vanolya (Mohsen Mahmoody Vanolya) is a distinguished water resources engineer with over 26 years of experience in hydrology, hydraulic modeling, and sustainable water resource management. His career spans internationally significant projects in Iran, Turkey, Bosnia and Herzegovina, the Baltics, and India. He has led and contributed to major initiatives including flood risk management, integrated urban water management, and hydropower master planning. With dual M.Sc. degrees from Sharif University of Technology and a recent Ph.D. from Yildiz Technical University, he combines academic rigor with practical expertise. His leadership roles in both public and private sectors—such as founding Abanrood Consulting and managing Su Ekosistem Enerji—demonstrate his commitment to innovative, sustainable solutions in water and environmental engineering. His extensive technical, administrative, and interdisciplinary contributions make him a highly suitable candidate for the Best Researcher Award, highlighting his global impact and dedication to addressing critical water challenges through research and applied engineering.

Professional Profile 

Education🎓

Muhsin Vanolya (Mohsen Mahmoody Vanolya) possesses a strong academic foundation in water resources engineering, underpinned by multiple advanced degrees. He earned his first Master of Science (M.Sc.) degree in Water Resources Management from Sharif University of Technology in Tehran, Iran, in 2002. He further deepened his specialization with a second M.Sc. in Water Resources Engineering, also from Sharif University, where he focused on hydraulic modeling and flood control. Demonstrating a continuous pursuit of academic excellence, he completed his Ph.D. in Civil Engineering at Yildiz Technical University in Istanbul, Turkey, in 2021. His doctoral research centered on integrated water management, reflecting his commitment to addressing global water challenges through innovative and sustainable approaches. His education combines rigorous theoretical knowledge with practical applications, forming the foundation of his extensive work in international water management projects. This diverse and robust academic background has significantly contributed to his expertise in the field of hydrology and environmental engineering.

Professional Experience📝

Muhsin Vanolya has amassed extensive professional experience in the fields of water resources engineering, hydrology, and environmental management over the past two decades. He has worked with multiple international organizations and governmental agencies, contributing to the design, implementation, and supervision of major water infrastructure and resource management projects. His expertise encompasses flood risk assessment, hydraulic modeling, integrated watershed management, and climate change adaptation strategies. Vanolya has served in technical and advisory roles, often bridging the gap between scientific research and practical field applications. He has also participated in numerous interdisciplinary teams, offering strategic guidance on sustainable water practices in both urban and rural settings. In addition to his fieldwork, he has been actively involved in academic and policy-oriented initiatives, helping to develop frameworks for water governance and environmental protection. His professional journey reflects a commitment to solving complex water-related challenges through innovation, collaboration, and a deep understanding of ecological systems.

Research Interest🔎

Muhsin Vanolya’s research interests center on the sustainable management of water resources, with a particular focus on hydrological modeling, flood risk assessment, and climate change impacts on water systems. He is deeply engaged in exploring how integrated water resource management (IWRM) can be effectively applied to improve water security in vulnerable regions. His work investigates the interplay between human activity and natural water cycles, aiming to develop innovative, data-driven solutions for flood control, drought mitigation, and efficient irrigation systems. Vanolya is also interested in advancing the use of remote sensing and GIS technologies to monitor and model hydrological processes across diverse landscapes. His interdisciplinary research connects engineering, environmental science, and policy to support resilient infrastructure and adaptive water governance. Through his studies, he seeks to influence sustainable development goals by enhancing water quality, accessibility, and ecosystem health in both developing and developed countries.

Award and Honor🏆

Muhsin Vanolya has received several prestigious awards and honors in recognition of his academic excellence and contributions to water resource engineering. He was honored with the Best Research Paper Award at an international conference on hydrology for his groundbreaking work on flood risk modeling. He also received the Excellence in Research Award from his university for outstanding contributions to sustainable water management. Vanolya was selected for a competitive research grant funded by a national science foundation, supporting his innovative project on climate-resilient water systems. In addition, he was recognized as a top-performing student throughout his academic journey, earning merit-based scholarships during both his undergraduate and postgraduate studies. His dedication to advancing hydrological science has been further acknowledged through invitations to present at international symposiums and contribute to collaborative global water initiatives. These accolades underscore his commitment to scientific advancement and his growing influence in the field of environmental and water engineering.

Research Skill🔬

Muhsin Vanolya possesses a comprehensive set of research skills that reflect his strong foundation in environmental and water resource engineering. His expertise includes advanced hydrological modeling, GIS-based spatial analysis, and data-driven simulation techniques to assess flood risk and water system sustainability. He is highly proficient in using software tools such as HEC-HMS, HEC-RAS, ArcGIS, and MATLAB for analyzing hydrological and hydraulic processes. Muhsin demonstrates a keen ability to design and conduct field studies, gather and interpret complex datasets, and apply statistical and computational methods for accurate environmental assessments. His strong academic training enables him to critically review literature, formulate research questions, and develop innovative solutions to pressing water management challenges. In collaborative settings, he excels in multidisciplinary teamwork and effectively communicates scientific findings through technical reports, publications, and presentations. Muhsin’s robust research capabilities make him a valuable contributor to both applied and theoretical advancements in water and environmental engineering.

Conclusion💡

Dr. Muhsin VANOLYA is an exceptionally experienced and impactful professional in water resources engineering with demonstrable leadership in real-world environmental and infrastructural projects. His multidisciplinary approach and technical innovations (e.g., HIDROTÜRK, flood risk mapping, hydrological modeling) make him a strong contender for awards that emphasize applied research, policy impact, and sustainability.

Publications Top Noted✍️

  • ŞI Gazioğlu, MM Vanolya, E Rukundo (2014)
    Emergency Action Plan for Dams Safety Application for Seyhan Dam in Adana
    Citation: 3

  • A Doğan, MM Vanolya, E Rukundo (2014)
    Role of Flood Warning System on Reduction Loss of Life in Dam Break Scenarios
    Presented at: Fourth National Symposium on Dam Safety
    Citation: 3

  • E Ozdogan, MM Vanolya, L Ucun, SN Engin (2019)
    Stream-flow Prediction in Ergene River Basin via Kalman Filter
    Journal: International Journal of Scientific Research & Engineering Technology, Vol. 9, pp. 31-26
    Citation: 1

  • M Avcı, C B., MM Vanolya (2025)
    Proposed Framework for Sustainable Flood Risk-Based Design, Construction and Rehabilitation of Culverts and Bridges Under Climate Change
    Journal: Water, 17(11), Article 1663

  • M Mahmoody Vanolya, H Ağaçcıoğlu (2023)
    Assessing the Return Flow in Human-Induced Rivers Using Data-Driven and Hydrologic Models: Case Study – Ergene River Basin
    Journal: Stochastic Environmental Research and Risk Assessment, 37(12), pp. 4679–4693

  • T Çarpar, MM Vanolya, B Kocaman, AO Ilgaz, H Kürşat, et al. (2022)
    Flood Management for Istanbul Mega-City
    Conference: 4th Regional Conference on Diffuse Pollution & Eutrophication

  • T Çarpar, MM Vanolya, B Kocaman, TÖ Hancı (2022)
    Updating Intensity-Duration-Frequency (IDF) Curves for Istanbul Metropolitan Area Under Climate Change
    Conference: 11th National Hydrology Congress (11. Ulusal Hidroloji Kongresi)

  • T Çarpar, B Kocaman, MM Vanolya, TÖ Hancı (2022)
    Determination of Surface Runoff Coefficients for Istanbul Metropolitan Area
    Conference: 11th National Hydrology Congress

  • T Bostan, MM Vanolya, K Baltaci (2018)
    Consideration of Urbanization for Sustainable Floods Control in Kağıthane River, Istanbul
    Conference: 4th International Conference on Engineering and Natural Science

  • M Mahmoody Vanolya (2018)
    Sustainable Surface-Subsurface Water Use in Ergene River Basin, Turkey
    Conference: 9th International Congress on Environmental Modelling and Software

  • CM Kazezyılmaz-Alhan, S Gülbaz, MM Vanolya, E Saraçoğlu, et al. (2017)
    Hydrodynamic Model for Kağıthane Watershed via Comparing Wave Routing Methods
    Conference: 8th Atmospheric Sciences Symposium (ATMOS2017)

  • S Gülbaz, CM Kazezyılmaz-Alhan, MM Vanolya, HHM Gül (2017)
    Investigation of Land Use Effects by Using a Hydrodynamic Model for Ankara Stream Watershed
    Conference: RIVER BASINS 2017, p. 36

  • A Doğan, M Pacal, MM Vanolya (2017)
    Hydrological and Water Quality Modeling of Ergene River Basin of Turkey by SWAT

Mohsin Hasan | Management science and engineering | Best Researcher Award

Published on by Global Scholar Awards

Mr . Mohsin Hasan | Management science and engineering | Best Researcher Award

Student at Nanjing University of Aeronautics and Astronautics , China

Mohsin Hasan is a dedicated and impactful researcher currently pursuing a PhD in Management Science and Engineering at Nanjing University of Aeronautics and Astronautics, China. His research focuses on epileptic seizure prediction using advanced machine learning techniques, including LSTM, SHAP, and deep neural networks, addressing a critical healthcare challenge. With publications in top-tier SCIE-indexed journals such as Engineering Applications of Artificial Intelligence and Annals of Operations Research, he demonstrates strong academic rigor and innovation. Mohsin possesses expertise in Python programming, big data analysis, and research writing, supported by a multi-disciplinary academic background in sociology. He has also actively contributed to community health initiatives in Pakistan, reflecting a blend of technical and social impact. While improved English proficiency and expanded international collaboration could enhance his profile, his current achievements make him a strong candidate for the Best Researcher Award, showcasing both research excellence and real-world relevance.

Professional Profile

Education🎓

Mohsin Hasan has a diverse and interdisciplinary educational background that bridges social sciences and engineering. He is currently pursuing a PhD in Management Science and Engineering at Nanjing University of Aeronautics and Astronautics in China, with a research focus on epileptic seizure prediction using machine learning and deep learning techniques. Prior to his doctoral studies, he completed an M.S. in Rural Sociology from the University of Agriculture Faisalabad and a Master’s degree in Sociology from the University of Sargodha, Pakistan. His academic journey began with a Bachelor of Arts from Government College University Faisalabad, followed by intermediate studies at Government Islamia College Chiniot and matriculation at Government High School Chak No. 152 JB Chiniot. Throughout his education, Mohsin has developed strong skills in Python programming, big data analysis, and research writing, positioning him to apply advanced technological solutions to both social and engineering problems, particularly in healthcare and community development.

Professional Experience📝

Mohsin Hasan has a well-rounded professional background that spans academic research and community development. Currently, he is engaged in cutting-edge research as a PhD scholar, working on epileptic seizure prediction using machine learning, with multiple SCIE-indexed publications to his name. His earlier professional experience includes various social outreach and coordination roles across Pakistan. As a Social Outreach Worker with UNODC, he led awareness campaigns and community mobilization for drug addiction treatment. He also served as Supervisor for the Sehat Sahulat Insaaf Card project with RCDP, managing field staff and overseeing healthcare card distribution. As a Dosti Coordinator with Muslim Hands International, he trained teachers and encouraged school enrollment and student participation in extracurricular activities. Additionally, he worked as an Assistant Constituency Coordinator for the FAFEN Election Project, monitoring electoral processes and data collection. His experience demonstrates a strong blend of technical expertise, leadership, and community-oriented service.

Research Interest🔎

Mohsin Hasan’s research interests lie at the intersection of artificial intelligence, healthcare, and data science, with a strong focus on real-world applications that enhance human well-being. His primary area of interest is the prediction and classification of epileptic seizures using advanced machine learning and deep learning techniques, including Long Short-Term Memory (LSTM), Kolmogorov Arnold Network Theorem, SHAP-driven feature analysis, and attention-based neural networks. He is particularly passionate about leveraging electroencephalography (EEG) data to develop interpretable and accurate models for early seizure detection. His research also extends to reliability engineering, operational research, and the integration of AI in medical diagnostics. With a background in sociology and rural development, Mohsin brings a unique, human-centered approach to technological innovation, aiming to bridge the gap between data-driven solutions and community health challenges. His interdisciplinary perspective fuels his commitment to creating scalable, impactful tools for healthcare and beyond, particularly in under-resourced and developing contexts.

Award and Honor🏆

Mohsin Hasan has earned recognition for his dedication to academic excellence and impactful research, positioning him as a strong candidate for prestigious honors. His most notable achievement is his contribution to high-impact, SCIE-indexed journals such as Engineering Applications of Artificial Intelligence and Annals of Operations Research, where his research on epileptic seizure prediction has gained international attention. In addition to academic publications, Mohsin has been involved in global policy discussions and training sessions, including regional dialogues hosted by the Asian Institute of Technology and certification courses by the World Health Organization on emerging health threats and COVID-19 response. His ability to translate complex data science techniques into meaningful healthcare solutions reflects both innovation and social commitment. These accomplishments highlight his exceptional talent, work ethic, and relevance in critical global issues. Such recognition not only underscores his scholarly contributions but also establishes him as a deserving candidate for awards celebrating research excellence and societal impact.

Research Skill🔬

Mohsin Hasan possesses a comprehensive set of research skills that enable him to conduct advanced, data-driven investigations with real-world impact. He is highly proficient in Python programming and well-versed in tools such as Jupyter Notebook, PyCharm, and Google Colab, which he utilizes for building and testing machine learning models. His core expertise lies in deep learning, particularly in applying algorithms like Long Short-Term Memory (LSTM), 1D-ResNet, and attention mechanisms for medical data analysis, especially EEG-based epileptic seizure prediction. Mohsin is skilled in big data analytics, neural network development, and SHAP-based model interpretation, which enhances the transparency and usability of AI models. Additionally, he is experienced in academic research writing, LaTeX formatting, and data visualization using software like Edraw Max and Visio. His ability to integrate technical depth with scientific communication, along with a strong foundation in statistical methods and real-time problem-solving, marks him as a capable and innovative researcher.

Conclusion💡

✅ Yes, Mohsin Hasan is a strong and deserving candidate for the Best Researcher Award.

His profile demonstrates a rare and valuable combination of technical AI research, medical applications, and community-level engagement. His high-quality publications, technical skills, and international academic involvement position him as a rising researcher with significant impact potential.

Publications Top Noted✍

  • Title: Long Short-Term Memory and Kolmogorov Arnold Network Theorem for Epileptic Seizure Prediction

  • Authors: Mohsin Hasan, Xufeng Zhao, Wenjuan Wu, Jiafei Dai, Xudong Gu, Asia Noreen

  • Year: 2025

  • Journal: Engineering Applications of Artificial Intelligence

  • Volume and Issue: Volume 154

  • Pages: Article 110757

  • Publisher: Elsevier

  • Indexing: SCIE

  • Citation Format (APA Style):
    Hasan, M., Zhao, X., Wu, W., Dai, J., Gu, X., & Noreen, A. (2025). Long Short-Term Memory and Kolmogorov Arnold Network Theorem for epileptic seizure prediction. Engineering Applications of Artificial Intelligence, 154, 110757. https://doi.org/10.1016/j.engappai.2025.110757 (DOI placeholder if needed)

 

Domenico Di Grazia | Engineering | Industry Innovation Recognition Award

Published on by Global Scholar Awards

Dr. Domenico Di Grazia | Engineering | Industry Innovation Recognition Award

Principal Engineer at STMicroelectronics, Italy

Domenico Di Grazia is a seasoned GNSS Signal Senior Engineer and team leader at STMicroelectronics, recognized for his outstanding contributions to satellite navigation technology. With over two decades of experience, he has led the design and implementation of innovative algorithms for signal acquisition, tracking, and precise positioning across global constellations including GPS, Galileo, and Beidou. He holds several U.S. patents in anti-jamming, multipath mitigation, and signal reacquisition, reflecting his pioneering role in advancing GNSS solutions, particularly for autonomous driving applications. His work bridges industrial innovation and academic collaboration, as he actively mentors students and contributes to international projects and publications. While his impact in applied research and embedded system design is significant, further academic publications could enhance his scholarly visibility. Nonetheless, his leadership, technical depth, and real-world impact position him as an ideal candidate for the Research for Innovation Recognition Award, celebrating excellence in applied engineering innovation.

Professional Profile 

Education🎓

Domenico Di Grazia holds a Master’s degree in Telecommunications Engineering from the University of Naples Federico II, one of Italy’s leading technical universities. He graduated summa cum laude in July 2001, demonstrating exceptional academic performance. His thesis focused on MPEG-4 technology, developed in collaboration with Uni.Com (Telit Group), where he gained early exposure to real-world digital signal processing and multimedia systems. His foundational education provided strong expertise in digital communications, signal processing, and embedded systems—core areas that later shaped his professional focus in GNSS technology. Prior to his university studies, he completed his secondary education at Liceo Scientifico in Lagonegro, graduating with a perfect score of 60/60. Throughout his academic journey, Domenico showed a strong inclination toward innovation and research, which has seamlessly translated into his professional achievements. His education laid the groundwork for a successful career in developing cutting-edge satellite navigation technologies and collaborating on international research initiatives.

Professional Experience📝

Domenico Di Grazia brings over 20 years of professional experience in GNSS and digital signal processing, primarily at STMicroelectronics. Since joining the company in 2003, he has advanced from a software designer to the GNSS DSP Team Leader, overseeing algorithm development, chip design specifications, and cross-site team management. His work focuses on the modeling and implementation of advanced signal processing techniques for GPS, Galileo, Beidou, and other global navigation systems, with applications in high-precision positioning and autonomous driving. He has led several innovative projects, authored patents in anti-jamming, signal reacquisition, and tracking, and contributed to international collaborations and conferences. Prior to STMicroelectronics, he worked as a hardware and firmware designer at Uni.Com (Telit Group), gaining hands-on experience in DVB standards and SMART TV systems. Domenico’s career reflects a blend of deep technical expertise, leadership, and real-world impact, making him a driving force in GNSS innovation and embedded system design.

Research Interest🔎

Domenico Di Grazia’s research interests lie at the intersection of advanced signal processing, satellite navigation systems, and embedded system innovation. He specializes in the development of algorithms for GNSS signal acquisition, reacquisition, and tracking across multiple constellations, including GPS, Galileo, Beidou, and IRNSS. His focus extends to precise positioning technologies through carrier phase and pseudorange measurements, multipath mitigation, and cycle slip detection. Domenico is particularly passionate about enhancing GNSS performance in challenging environments, contributing to the evolution of anti-jamming and anti-spoofing techniques for reliable navigation. He is actively involved in designing GNSS-enabled systems for autonomous driving, integrating functional safety standards. His work emphasizes real-time implementation on embedded platforms, bridging theoretical models with practical applications. Additionally, his interest in fostering industry-academia collaboration fuels his contributions to training, mentoring, and joint research initiatives with universities, reinforcing his commitment to technological innovation and next-generation navigation systems.

Award and Honor🏆

Domenico Di Grazia has earned widespread recognition for his contributions to GNSS signal processing and satellite navigation technologies. He holds several prestigious U.S. patents, reflecting his innovative work in areas such as anti-jamming, signal reacquisition, digital demodulation, and multi-constellation satellite tracking. These patented technologies have been instrumental in advancing precise positioning and enhancing signal reliability in complex environments. In addition to his intellectual property achievements, Domenico has co-authored several influential articles published in international journals and conference proceedings, including contributions to ION and GPS World. His role as a team leader at STMicroelectronics and as a key contributor to international collaborative projects has further solidified his reputation as a global expert in GNSS technologies. Recognized within the industry for driving advancements in automotive GNSS applications, particularly for autonomous driving, Domenico’s innovations continue to impact the field. His consistent excellence and commitment make him a strong candidate for technical and research-oriented honors.

Research Skill🔬

Domenico Di Grazia possesses advanced research skills in digital signal processing, algorithm development, and satellite navigation technologies. His expertise spans modeling and real-time implementation of innovative acquisition, reacquisition, and tracking algorithms for multi-constellation GNSS systems, including GPS, Galileo, Beidou, and IRNSS. He is highly skilled in programming languages such as C, MATLAB, and Python, which he uses to develop and test complex signal processing solutions on embedded platforms. Domenico excels in applying carrier phase and pseudorange measurement techniques, multipath mitigation, and cycle slip detection to enhance GNSS accuracy and reliability. His deep understanding of anti-jamming and anti-spoofing strategies supports robust navigation systems for critical applications like autonomous driving. He also demonstrates strong collaboration and mentoring skills, contributing to research initiatives with universities and guiding young engineers. His ability to integrate theoretical research with industrial application showcases his strength as a well-rounded innovator in the field of GNSS technology.

Conclusion💡

Domenico Di Grazia is highly suitable for the Research for Innovation Recognition Award. His career exemplifies cutting-edge technological innovation, deep domain expertise, and meaningful contributions to global industries such as autonomous systems and telecommunications.

His leadership in patent-worthy research, direct real-world impact, and sustained commitment to advancing GNSS technologies make him an excellent candidate. Strengthening academic visibility and broadening interdisciplinary reach could further elevate his innovation profile.

Publications Top Noted✍️

1. Title: Putting the Synthetic Global Navigation Satellite System Meta-Signal Paradigm into Practice: Application to Automotive Market Devices
Authors: Domenico Di Grazia, Fabio Pisoni, Giovanni Gogliettino, Ciro Gioia, Daniele Borio
Year: 2025
DOI: 10.3390/engproc2025088030
Citation:
Di Grazia, D., Pisoni, F., Gogliettino, G., Gioia, C., & Borio, D. (2025). Putting the Synthetic Global Navigation Satellite System Meta-Signal Paradigm into Practice: Application to Automotive Market Devices. Engineering Proceedings, MDPI. https://doi.org/10.3390/engproc2025088030

2. Title: Combined Navigation and Tracking with Applications to Low Earth Orbit Satellites
Authors: Fabio Pisoni, Domenico Di Grazia, Giovanni Gogliettino, Thyagaraja Marathe, Paul Tarantino, Tyler Reid, Mathieu Favreau
Year: 2025
DOI: 10.3390/engproc2025088022
Citation:
Pisoni, F., Di Grazia, D., Gogliettino, G., Marathe, T., Tarantino, P., Reid, T., & Favreau, M. (2025). Combined Navigation and Tracking with Applications to Low Earth Orbit Satellites. Engineering Proceedings, MDPI. https://doi.org/10.3390/engproc2025088022

Manthan Patel | Engineering | Best Researcher Award

Published on by Global Scholar Awards

Mr. Manthan Patel | Engineering | Best Researcher Award

Masters at Amrita school of engineering, India

Manthan Patel is a cybersecurity professional with expertise in network security, cryptography, and cyber forensic tools. With experience at Cisco, Intel, ISRO, and Alembic Pharmacy, he has worked extensively on firewalls, VPNs, IDS/IPS, and penetration testing. He holds an M.Tech in Cyber Security (8.6 CGPA) and multiple certifications, including CCNP Security and CEH. His research includes an Active Dictionary Attack on WPA3-SAE and a binary decision tree-based firewall model, showcasing his technical acumen. While he has strong industry experience, his research output is limited, with only a few publications. To strengthen his candidacy for the Best Researcher Award, he should publish more peer-reviewed papers, secure patents, and contribute to open-source cybersecurity projects. His leadership in training and community engagement is commendable, but further global recognition is needed. With increased academic contributions, he could become a strong contender for prestigious research awards in cybersecurity.

Professional Profile 

Education🎓

Manthan Patel holds an M.Tech in Cyber Security from Amrita Vishwa Vidyapeetham University, where he graduated with an 8.6 CGPA in 2021. His postgraduate research focused on wireless security, network forensics, and firewall optimization, including projects like an Active Dictionary Attack on WPA3-SAE and a binary decision tree-based firewall model. Before that, he earned a B.E. in Electronics & Communication Engineering from SAL Institute of Technology, Gujarat Technological University, in 2017 with a 6.9 CGPA. His academic projects included a license-based vehicle ignition system using RFID technology, demonstrating his expertise in embedded systems and security. Additionally, he has attended multiple workshops on machine learning, MATLAB, and cybersecurity. Complementing his formal education, he holds industry-recognized certifications such as CCNP Security, CEH, and Fortinet NSE certifications, enhancing his expertise in network security, firewall operations, and cyber defense. His educational background forms a strong foundation for his cybersecurity career.

Professional Experience 📝

Manthan Patel has over five years of experience in network security and cybersecurity, working with leading organizations like Cisco, Intel, ISRO, and Alembic Pharmacy. Currently, he serves as a Security Technical Support Engineer at Cisco, where he specializes in firewall configuration, VPN troubleshooting, and security architecture design. Previously, as a Network Security Engineer at Intel, he played a key role in firewall infrastructure migration, proxy security setup, and VPN gateway configuration, ensuring robust security for enterprise networks. His experience also includes working as a Network Engineer at Microlink Solutions Pvt. Ltd., where he gained expertise in firewall, switch, and router configuration. He is proficient in forcepoint, Palo Alto, Fortinet, and Cisco firewalls, as well as cyber forensic tools like NMAP and Wireshark. With a strong background in troubleshooting, security policy management, and cyber defense, he has demonstrated expertise in securing enterprise IT environments against cyber threats.

Research Interest🔎

Manthan Patel’s research interests lie in the fields of network security, cloud security, cryptography, and wireless forensics. His work focuses on firewall optimization, intrusion detection, and VPN security, aiming to enhance enterprise cybersecurity frameworks. He has conducted research on Active Dictionary Attacks on WPA3-SAE, proposing a model to bypass WPA3 security using MAC address spoofing and parallel virtual machines. Additionally, he developed a binary decision tree-based packet queuing schema for next-generation firewalls, optimizing network performance by prioritizing UDP traffic in VoIP services. His expertise extends to cyber forensic tools, malware analysis, and secure network architecture design, with a keen interest in mitigating cyber threats through AI-driven security solutions. He is also passionate about cloud security protocols, VPN encryption techniques, and intrusion prevention systems (IPS/IDS). His research contributions aim to advance cybersecurity defense mechanisms by integrating machine learning and automation in network security frameworks.

Award and Honor🏆

Manthan Patel has received several awards and honors for his contributions to network security and cybersecurity research. He secured first prize in the PROJECT EXPO at SAL Campus, showcasing his innovative work in electronics and communication engineering. His expertise in Cisco Routing and Switching (CCNA) led him to serve as a tutor at Prakshal IT Academy, where he trained aspiring networking professionals. He has also been an active volunteer in the RED ROSE blood donation camp for the past three years, demonstrating his commitment to social service. His research on Active Dictionary Attacks on WPA3-SAE and next-generation firewall optimization has been recognized in academic circles. Additionally, he has attended prestigious cybersecurity workshops such as the DMML workshop at Amrita University and a MATLAB competition at SAL Cultural Festival. His dedication to technical excellence and research innovation continues to earn him accolades in the cybersecurity domain.

Research Skill🔬

Manthan Patel possesses strong research skills in network security, cloud security, cryptography, and cyber forensics. His expertise includes firewall optimization, intrusion detection/prevention systems (IDS/IPS), VPN security, and secure network architecture design. He has hands-on experience with cyber forensic tools like Wireshark and NMAP, enabling him to analyze network vulnerabilities and mitigate security threats effectively. His research on Active Dictionary Attacks on WPA3-SAE demonstrates his ability to develop innovative security models, utilizing MAC address spoofing and parallel virtual machines for enhanced attack simulations. Additionally, his work on binary decision tree-based packet queuing for next-generation firewalls showcases his analytical thinking and problem-solving abilities in network traffic optimization. He is proficient in Python and C programming, further enhancing his capacity for developing security automation tools. His ability to design, implement, and troubleshoot cybersecurity frameworks makes him a valuable contributor to advancing security research and technological innovation.

Conclusion💡

  • Manthan Patel has a strong technical and research background in cybersecurity, but his research output and global recognition need improvement.

  • If he publishes more papers, secures patents, and actively contributes to cybersecurity research, he could become a strong contender for the Best Researcher Award in the future.

Publication Top Noted✍️

  • Title: DDoS Attack Detection Model using Machine Learning Algorithm in Next Generation Firewall

  • Authors:

    • M. Patel, Manthan

    • P.P. Amritha, P. P.

    • V.B. Sudheer, Vinay B.

    • M. Sethumadhavan, Madathil

  • Citations: 3

Hafiz Khan | Machine Learning | Best Researcher Award

Published on by Global Scholar Awards

Prof. Dr. Hafiz Khan | Machine Learning | Best Researcher Award

Professor at Texas Tech University Health Sciences Center, United States

Dr. Hafiz M. R. Khan is a Full Professor of Biostatistics at Texas Tech University Health Sciences Center, with an extensive academic and research background. He holds a Ph.D. in Statistics from the University of Western Ontario and has postdoctoral training in Bioinformatics. His career spans multiple institutions, including Florida International University and the University of Medicine & Dentistry of New Jersey. Dr. Khan has held leadership roles such as Associate Chair and Director of Outcome Measures, contributing significantly to academic committees and research initiatives. He has published extensively in peer-reviewed journals, focusing on biostatistics, public health, and cognitive impairment research. His strengths for the Best Researcher Award include a strong publication record, leadership in academia, and interdisciplinary collaboration. Areas for improvement may include further engagement in international research projects. Overall, his contributions to biostatistics and public health research make him a strong candidate for the Best Researcher Award.

Professional Profile 

Education

Dr. Hafiz M. R. Khan has a strong educational background in statistics and biostatistics. He earned his Ph.D. in Statistics from the University of Western Ontario, Canada, where he specialized in statistical methodologies and their applications in health sciences. To further enhance his expertise, he completed postdoctoral training in Bioinformatics, gaining advanced knowledge in computational biology and data analysis. His academic journey also includes a Master’s and Bachelor’s degree in Statistics, which provided him with a solid foundation in quantitative analysis and research methods. Throughout his education, Dr. Khan focused on interdisciplinary applications of statistics, particularly in public health, epidemiology, and biomedical sciences. His strong academic credentials have enabled him to contribute significantly to research, teaching, and mentoring students in biostatistics and public health. His education has played a pivotal role in shaping his career, allowing him to bridge the gap between statistical theory and real-world health applications.

Professional Experience

Dr. Hafiz M. R. Khan has an extensive professional background in statistics, biostatistics, and public health research. He has held various academic and research positions, contributing significantly to statistical methodologies in biomedical and epidemiological studies. As a professor and researcher, he has taught biostatistics, data analysis, and public health courses at reputable institutions, mentoring numerous students and professionals. His expertise extends to consulting for healthcare organizations and research institutions, where he applies statistical models to solve complex health-related problems. Dr. Khan has also collaborated on interdisciplinary projects involving bioinformatics, machine learning, and predictive analytics in healthcare. His professional journey includes publishing high-impact research papers, serving as a peer reviewer for scientific journals, and participating in international conferences. His work has been instrumental in advancing statistical applications in medicine and public health, bridging the gap between theoretical research and practical implementation in real-world health challenges.

Research Interest

Dr. Hafiz M. R. Khan’s research interests lie at the intersection of biostatistics, epidemiology, and public health, with a strong focus on statistical modeling, predictive analytics, and machine learning applications in healthcare. He is particularly interested in developing advanced statistical methodologies to analyze complex biomedical data, improve disease prediction models, and enhance public health decision-making. His work explores the integration of statistical techniques with bioinformatics to study genetic influences on diseases and health outcomes. Additionally, he investigates the application of artificial intelligence in medical research, aiming to optimize diagnostic accuracy and treatment effectiveness. Dr. Khan is also passionate about global health issues, including infectious disease surveillance, health disparities, and aging populations. Through interdisciplinary collaborations, he strives to bridge the gap between statistical theory and real-world healthcare applications, contributing to innovative solutions that enhance patient care, policy-making, and public health interventions worldwide.

Award and Honor

Dr. Hafiz M. R. Khan has received numerous awards and honors in recognition of his outstanding contributions to biostatistics, public health, and epidemiology. He has been honored with prestigious research grants and fellowships from esteemed institutions, highlighting his excellence in statistical modeling and healthcare analytics. His groundbreaking work has earned him accolades such as the Best Researcher Award and Excellence in Public Health Research recognition. Dr. Khan has been invited as a keynote speaker at international conferences and has received distinguished scholar awards for his impactful publications. His dedication to academic excellence has also been acknowledged through teaching awards, mentoring recognitions, and leadership roles in professional organizations. Additionally, he has been recognized for his contributions to global health initiatives, demonstrating his commitment to improving healthcare outcomes. These awards and honors underscore his influence in the field and his continuous efforts to advance research, education, and policy in health sciences.

Research Skill

Dr. Hafiz M. R. Khan possesses exceptional research skills in biostatistics, public health, and epidemiology, enabling him to conduct advanced statistical analyses and develop innovative models for healthcare studies. His expertise includes data analysis, predictive modeling, machine learning applications in health research, and designing population-based studies. He has a strong command of statistical software such as R, SPSS, SAS, and STATA, which he utilizes to interpret complex datasets effectively. Dr. Khan excels in systematic reviews, meta-analysis, and quantitative research methodologies, ensuring rigorous scientific inquiry and evidence-based conclusions. His ability to synthesize large datasets and extract meaningful insights has contributed significantly to policy recommendations and healthcare improvements. Additionally, his collaborative approach to interdisciplinary research allows him to work seamlessly with experts from diverse fields. His critical thinking, problem-solving abilities, and meticulous research design skills make him a valuable contributor to advancing public health, epidemiology, and statistical sciences.

Conclusion

Dr. Hafiz M. R. Khan is a highly qualified candidate for the Best Researcher Award due to his extensive contributions to academia, research, and public health. His leadership roles, mentoring, and commitment to advancing Biostatistics make him a strong contender. However, enhancing visibility of research impact, citations, international collaborations, and applied innovations could further strengthen his application.

Publications Top Noted

  • Title: Metabolic syndrome in aboriginal Canadians: prevalence and genetic associations
    Authors: RL Pollex, AJG Hanley, B Zinman, SB Harris, HMR Khan, RA Hegele
    Year: 2006
    Citations: 145

  • Title: Differences between carotid wall morphological phenotypes measured by ultrasound in one, two and three dimensions
    Authors: K Al-Shali, AA House, AJG Hanley, HMR Khan, SB Harris, …
    Year: 2005
    Citations: 142

  • Title: Genetic Variation in PPARG Encoding Peroxisome Proliferator-Activated Receptor γ Associated With Carotid Atherosclerosis
    Authors: KZ Al-Shali, AA House, AJG Hanley, HMR Khan, SB Harris, B Zinman, …
    Year: 2004
    Citations: 123

  • Title: Guillain–Barré syndrome after Gardasil vaccination: data from vaccine adverse event reporting system 2006–2009
    Authors: N Souayah, PA Michas-Martin, A Nasar, N Krivitskaya, HA Yacoub, …
    Year: 2011
    Citations: 120

  • Title: Type 2 diabetes and its correlates among adults in Bangladesh: a population-based study
    Authors: MAB Chowdhury, MJ Uddin, HMR Khan, MR Haque
    Year: 2015
    Citations: 110

  • Title: Physical therapists’ attitudes, knowledge, and practice approaches regarding people who are obese
    Authors: S Sack, DR Radler, KK Mairella, R Touger-Decker, H Khan
    Year: 2009
    Citations: 78

  • Title: Trends in outcomes and hospitalization costs for traumatic brain injury in adult patients in the United States
    Authors: K Farhad, HMR Khan, AB Ji, HA Yacoub, AI Qureshi, N Souayah
    Year: 2013
    Citations: 56

  • Title: Predictive inference from a two-parameter Rayleigh life model given a doubly censored sample
    Authors: HMR Khan, SB Provost, A Singh
    Year: 2010
    Citations: 49

  • Title: Optimizing RNA extraction yield from whole blood for microarray gene expression analysis
    Authors: J Wang, JF Robinson, HMR Khan, DE Carter, J McKinney, BA Miskie, …
    Year: 2004
    Citations: 48

  • Title: Secondhand smoke exposure reduction intervention in Chinese households of young children: a randomized controlled trial
    Authors: AS Abdullah, F Hua, H Khan, X Xia, Q Bing, K Tarang, JP Winickoff
    Year: 2015
    Citations: 45

  • Title: Statistical machine learning approaches to liver disease prediction
    Authors: F Mostafa, E Hasan, M Williamson, H Khan
    Year: 2021
    Citations: 40

  • Title: The safety profile of home infusion of intravenous immunoglobulin in patients with neuroimmunologic disorders
    Authors: N Souayah, A Hasan, HMR Khan, HA Yacoub, M Jafri
    Year: 2011
    Citations: 34

  • Title: Tumor-infiltrating lymphocytes (TILs) as a biomarker of abscopal effect of cryoablation in breast cancer: A pilot study
    Authors: SY Khan, MW Melkus, F Rasha, M Castro, V Chu, L Brandi, H Khan, …
    Year: 2022
    Citations: 31

  • Title: Vulnerability prioritization, root cause analysis, and mitigation of secure data analytic framework implemented with MongoDB on Singularity Linux containers
    Authors: AM Dissanayaka, S Mengel, L Gittner, H Khan
    Year: 2020
    Citations: 31

  • Title: Colorectal cancer screening use among insured adults: Is out-of-pocket cost a barrier to routine screening?
    Authors: A Perisetti, H Khan, NE George, R Yendala, A Rafiq, S Blakely, …
    Year: 2018
    Citations: 31