Qiang Yue | Big Data Analytics | Global Data Innovation Recognition Award

Posted on by ScienceFather

Prof. Qiang Yue | Big Data Analytics | Global Data Innovation Recognition Award

College of Water Conservancy and Civil Engineering, Shandong Agricultural University | China

Publication Profile

Scopus

PROF. QIANG YUE – A LEADER IN BIG DATA ANALYTICS AND WATER CONSERVANCY RESEARCH 🌐💧

INTRODUCTION 🌟

Prof. Qiang Yue is a prominent academic and researcher at the College of Water Conservancy and Civil Engineering, Shandong Agricultural University, China. Specializing in Big Data Analytics, Prof. Yue has contributed significantly to the field of water conservancy and civil engineering, focusing on the integration of data science and engineering for sustainable solutions. His interdisciplinary approach is helping shape the future of water management systems and infrastructure development.

EARLY ACADEMIC PURSUITS 🎓

Prof. Yue’s academic journey began with a strong foundation in civil engineering and water conservancy. After completing his undergraduate degree, he pursued advanced studies in related fields, obtaining a Master’s and PhD with a focus on big data analytics and its applications in civil engineering and water resources management. His rigorous academic training set the stage for his future contributions to both engineering and data science.

PROFESSIONAL ENDEAVORS 💼

As a faculty member at Shandong Agricultural University, Prof. Yue has played a key role in developing research programs and teaching in the fields of water conservancy and civil engineering. His work bridges the gap between traditional engineering methods and modern data analytics, incorporating advanced technologies like machine learning and AI in the optimization of water resources and infrastructure planning. Prof. Yue has also collaborated with national and international research institutions, contributing to various large-scale projects focused on water management and sustainable civil engineering practices.

CONTRIBUTIONS AND RESEARCH FOCUS ON Big Data Analytics 🔬

Prof. Yue’s research interests lie at the intersection of Big Data Analytics and civil engineering, particularly in the optimization of water conservancy systems. His work focuses on the application of machine learning algorithms, predictive analytics, and real-time data collection to improve the efficiency of water resource management, flood control, and infrastructure development. Additionally, his research aims to enhance the sustainability of civil engineering projects through data-driven decision-making, making significant strides toward smart cities and sustainable environmental practices.

IMPACT AND INFLUENCE 🌍

Prof. Yue’s research has had a profound impact on both the academic community and the industry. His innovative use of Big Data Analytics in water conservancy and civil engineering has transformed how data is used in real-time decision-making, helping optimize water resource management on a large scale. His work influences policy decisions, infrastructure development projects, and sustainability strategies, improving water conservation efforts in China and beyond. Prof. Yue has also mentored a generation of engineers and researchers, sharing his knowledge and experience to cultivate future leaders in the field.

ACADEMIC CITATIONS AND PUBLICATIONS 📚

Prof. Yue has authored numerous papers in high-impact journals, with a focus on Big Data Analytics and its applications in water management and civil engineering. His publications cover topics such as predictive modeling, real-time water quality monitoring, and optimization of water distribution systems using machine learning. His research is widely cited in the academic community, reflecting the significance of his work in the integration of Big Data with engineering practices.

HONORS & AWARDS 🏆

Prof. Yue’s exceptional contributions to Big Data Analytics and water conservancy have earned him various honors and awards, including:

  • Best Paper Award, International Conference on Water Management and Engineering (2022)
  • Outstanding Researcher Award, Shandong Agricultural University (2021)
  • Excellence in Teaching Award, College of Water Conservancy and Civil Engineering (2020)
  • Innovation in Data Science Award (2019)

LEGACY AND FUTURE CONTRIBUTIONS 🔮

Prof. Yue’s work is paving the way for the next generation of engineers who will rely on data analytics to create sustainable and efficient infrastructure solutions. His future contributions promise to further the development of smart cities, improve water resource management, and enhance the overall resilience of urban environments to climate change. As he continues to innovate and mentor young engineers, his legacy will endure, shaping the future of civil engineering and environmental sustainability.

FINAL NOTE 📌

Prof. Qiang Yue’s career has been defined by his commitment to applying cutting-edge technology to real-world problems in water conservancy and civil engineering. His research is reshaping how engineers and policymakers approach water management and sustainability. His ability to blend Big Data Analytics with traditional engineering disciplines is a testament to his vision for the future of infrastructure and environmental protection.

 TOP NOTES PUBLICATIONS 📚

Dynamic health prediction of plain reservoirs based on deep learning algorithms
    • Authors: Z., Zhu; Zhaohui, H.; Wu, Hao; Z., Zhang, Zhicheng; R., Wang, Rui; Q., Yue, Qiang
    • Journal: Engineering Applications of Artificial Intelligence
    • Year: 2025
Recognition and quantification of apparent damage to concrete structure based on computer vision
    • Authors: J., Liu, Jiageng; H., Sun, Hongyu; Q., Yue, Qiang; Y., Jia, Yanyan; S., Wang, Shaojie
    • Journal: Measurement: Journal of the International Measurement Confederation
    • Year: 2025

Neyara Radwan | Innovation in Data Analysis | Outstanding Scientist Award

Posted on by ScienceFather

Dr. Neyara Radwan | Innovation in Data Analysis | Outstanding Scientist Award

Liwa College, ABU Dhabi | United Arab Emirates

Publication Profile

Orcid

Scopus

Research Gate

Google scholar

👩‍🏫 Summary

Dr. Neyara Radwan is an accomplished academic and researcher specializing in Industrial Engineering, Lean Manufacturing, Sustainable Systems, and Renewable Energy. Currently an Associate Professor at Liwa College in Abu Dhabi, UAE, she has an impressive academic history with roles across several prestigious institutions globally, including in Egypt, Saudi Arabia, and India. With a passion for sustainable development and advanced engineering systems, her research focuses on optimization, supply chain management, solid waste management, and energy systems.

🎓 Education

Dr. Radwan holds a Ph.D. in Production Engineering from Benha University, Egypt (2008), with a thesis on CAD of Electro-Chemical Honing Machining and Statistical Modeling. She also earned her M.A. in Production Engineering and Mechanical Design from Mansoura University, Egypt (2004), focusing on utilizing computer-aided expert systems for power transmission shaft design. Additionally, she completed her B.A. in the same field from Mansoura University, where she designed belt conveyors for a sugar factory project.

💼 Professional Experience

Dr. Radwan has an extensive career in academia. She is currently an Associate Professor at Liwa College in Abu Dhabi (2023–Present). Before this, she served as an Associate Professor at the Mechanical Department of Suez Canal University, Egypt (2012–2023), and as a Quality Assurance Officer and Assistant Professor at King Abdulaziz University, Jeddah, KSA (2014–2021). She has also held part-time roles in various academic institutions in Egypt, focusing on industrial engineering and mechanical design.

🏅 Awards & Recognition

Dr. Radwan’s dedication to education and research has earned her numerous awards, including the Excellence in Education Development Award (NCRDSIMS, India, 2018), the Global Service to Humanity Award (ADlafrica, 2021), and the Golden Academic Award (Tradepreneur Global, 2022). She has also been recognized for her outstanding academic leadership, receiving the Global Excellence in Academic Leadership Award (2024) and the Most Outstanding Engineering Educator and Writer Award (2024). Her contributions have been consistently celebrated through international accolades and recognitions.

🔧 Technical Skills

Dr. Radwan’s technical expertise spans several cutting-edge areas, including Optimization, Lean Manufacturing, and Sustainable Engineering. She is skilled in Renewable Energy Systems, Artificial Intelligence Applications in Engineering, Supply Chain Management, and Solid Waste Management. Additionally, her proficiency in CAD Modeling and Statistical Process Control allows her to explore and implement advanced solutions for sustainable systems and optimal operations.

👩‍🏫 Teaching Experience

Dr. Radwan has taught at top-tier universities across multiple countries, specializing in Industrial Management, Mechanical Engineering, and Sustainable Systems. Her teaching includes overseeing quality assurance in MBA/EMBA programs, and she is passionate about helping students connect theoretical knowledge with practical, real-world applications. She is recognized for her engaging teaching style and her ability to inspire the next generation of engineers and leaders.

🔬 Research Interests

Dr. Radwan’s research interests are wide-ranging, with a primary focus on Sustainability, Renewable Energy, and Optimization. Her work also delves into Circular Economy, Waste Management, Energy Systems, and Artificial Intelligence applications in engineering. She is particularly dedicated to researching how these fields intersect with global goals like the Sustainable Development Goals (SDGs), striving for impactful, real-world solutions to critical environmental and societal challenges.

Publication Top Notes

Development of artificial intelligence techniques in Saudi Arabia: the impact on COVID-19 pandemic. Literature review
    • Authors: NB Al-Jehani, ZA Hawsawi, N Radwan, M Farouk
    • Journal: Journal of Engineering Science and Technology
    • Citation: 12
    • Year: 2021 🗓️
Characterizing land use/land cover change dynamics by an enhanced random forest machine learning model: a Google Earth Engine implementation
    • Authors: CB Pande, A Srivastava, KN Moharir, N Radwan, L Mohd Sidek, …
    • Journal: Environmental Sciences Europe
    • Citation: 11
    • Year: 2024 🗓️
Heat transfer analysis of single-walled carbon nanotubes in Ellis’s fluid model: Comparative study of uniform and non-uniform channels
    • Authors: M Irfan, I Siddique, M Nazeer, S Saleem, N Radwan
    • Journal: Case Studies in Thermal Engineering
    • Citation: 10
    • Year: 2024 🗓️
Dynamics of magnetized viscous dissipative material of hybrid nanofluid with irregular thermal generation/absorption
    • Authors: M Yasir, S Saleem, M Khan, N Radwan
    • Journal: Case Studies in Thermal Engineering
    • Citation: 8
    • Year: 2024 🗓️
Assessment of groundwater potential zone mapping for semi-arid environment areas using AHP and MIF techniques
    • Authors: SP Shinde, VN Barai, BK Gavit, SA Kadam, AA Atre, CB Pande, SC Pal, …
    • Journal: Environmental Sciences Europe
    • Citation: 8
    • Year: 2024 🗓️
A comparative study based on performance and techno-economic analysis of different strategies for PV-Electrolyzer (green) hydrogen fueling incinerator system
    • Authors: OM Butt, MS Ahmad, TK Lun, HS Che, H Fayaz, N Abd Rahim, KKK Koziol, …
    • Journal: Waste Management
    • Citation: 8
    • Year: 2023 🗓️

Alireza sobbouhi | Predictive Modeling Innovations | Best Researcher Award

Posted on by ScienceFather

Dr. Alireza sobbouhi | Predictive Modeling Innovations | Best Researcher Award

shahid beheshti university | Iran

Author Profile

Early Academic Pursuits 📚

Dr. Alireza Sobbouhi’s academic journey began at Shahid Beheshti University in Iran, where he developed a strong foundation in mathematics, statistics, and computational sciences. His early fascination with complex systems and data-driven decision-making led him to specialize in predictive modeling. This interest propelled him into graduate studies, where he focused on developing and applying sophisticated techniques for forecasting and analyzing data.

Professional Endeavors 💼

Dr. Sobbouhi’s career blends academic achievements with professional success. As a professor at Shahid Beheshti University, he has been deeply involved in teaching, research, and industry collaboration. His role in academia extends beyond teaching as he works on impactful projects that link predictive modeling with real-world applications, from healthcare to finance. His expertise has also made him a sought-after consultant, furthering his reach and influence in both academia and industry.

Contributions and Research Focus On Predictive Modeling Innovations🔬

Dr. Sobbouhi’s research is rooted in the advancement of predictive modeling. His contributions have introduced new methodologies to improve the accuracy and efficiency of data analysis in various domains. Some key areas of focus include:

  • Development of Predictive Algorithms: Crafting algorithms that provide more precise predictions in economic, healthcare, and environmental sectors.
  • Machine Learning Integration: Exploring ways to integrate machine learning techniques into predictive models for better data interpretation and forecasting.
  • Big Data Analytics: Focusing on scalable approaches to handle and analyze massive datasets to uncover patterns that traditional models might miss.

Impact and Influence 🌍

Dr. Sobbouhi’s work has had a profound impact, not only in academia but also across various industries. His innovative contributions to predictive modeling and machine learning have influenced numerous researchers and professionals in fields ranging from economics to environmental science. His approach to enhancing model reliability and interpretability has set new standards and inspired further research in data science. The applications of his work continue to improve decision-making processes worldwide.

Academic Cites 📑

Dr. Sobbouhi’s research has been extensively cited in scholarly articles, journals, and conferences, indicating the high regard in which his work is held. His studies on predictive analytics and statistical modeling have been foundational, influencing a wide range of studies in machine learning and data science. The frequency of his citations reflects the relevance and significance of his contributions to the broader scientific community.

Technical Skills 🧑‍💻

Dr. Sobbouhi possesses a diverse and deep technical skill set that includes:

  • Programming: Expertise in Python, R, and MATLAB for data analysis and modeling.
  • Statistical Modeling: Advanced proficiency in developing and applying statistical techniques for prediction and forecasting.
  • Machine Learning: Expertise in applying machine learning algorithms to large datasets to uncover trends and make predictions.
  • Data Visualization: Strong skills in visualizing complex datasets to facilitate understanding and decision-making.

These technical competencies allow him to tackle complex datasets and develop state-of-the-art predictive models.

Teaching Experience 🏫

As an educator, Dr. Sobbouhi has taught a variety of courses on statistics, data science, and machine learning at Shahid Beheshti University. His teaching style blends theoretical knowledge with practical applications, ensuring students are well-prepared for the real-world challenges of the data science field. Dr. Sobbouhi has also supervised many graduate students, guiding them in their research and helping to shape the next generation of data scientists.

Legacy and Future Contributions 🔮

Dr. Sobbouhi’s legacy is built on his innovative contributions to predictive modeling and data science. His ability to bridge the gap between academic theory and industry application has had a lasting influence on both fields. Looking ahead, Dr. Sobbouhi is expected to continue making groundbreaking advancements in predictive analytics, particularly in the integration of AI and machine learning into real-world applications. His future research will likely shape the development of new predictive tools, influencing a wide range of industries for years to come.

Notable Publications  📑 

A novel predictor for areal blackout in power system under emergency state using measured data
    • Authors: Not provided in the source, but typically listed in the full article.
    • Journal: Electric Power Systems Research
    • Year: 2025
A novel SVM ensemble classifier for predicting potential blackouts under emergency condition using on-line transient operating variables
    • Authors: Not provided in the source, but typically listed in the full article.
    • Journal: Electric Power Systems Research
    • Year: 2025 (April issue)
Transient stability improvement based on out-of-step prediction
    • Authors: Not provided in the source, but typically listed in the full article.
    • Journal: Electric Power Systems Research
    • Year: 2021
Transient stability prediction of power system; a review on methods, classification and considerations
    • Authors: Not provided in the source, but typically listed in the full article.
    • Journal: Electric Power Systems Research
    • Year: 2021
Online synchronous generator out-of-step prediction by electrical power curve fitting
    • Authors: Alireza Sobbouhi (main author)
    • Journal: IET Generation, Transmission and Distribution
    • Year: 2020
Online synchronous generator out-of-step prediction by ellipse fitting on acceleration power – Speed deviation curve
    • Authors: Alireza Sobbouhi (main author)
    • Journal: International Journal of Electrical Power and Energy Systems
    • Year: 2020

Jingteng Liu | Business Analytics | Best Researcher Award

Posted on by ScienceFather

Mr. Jingteng Liu | Business Analytics | Best Researcher Award

ESADE Business School, Spain

Author Profile

Google Scholar

🎓 Early Academic Pursuits

Mr. Jingteng Liu’s academic journey began at Northwestern Polytechnical University, where he studied Software Engineering. After completing two years, he transferred to Arizona State University (ASU), where he pursued a Bachelor of Science in Computational Mathematical Sciences from 2017 to 2022. Alongside this, he obtained a Certification in Applied Business Data Analytics (2018-2022). During this period, Mr. Liu laid the foundation for his academic success by immersing himself in subjects that bridged computer science, mathematics, and business analytics.

💼 Professional Endeavors

Mr. Liu’s career has been marked by various leadership roles, with a strong focus on data analysis, machine learning, and business strategy. As Co-Founder of Hans & Associates LLC since May 2017, he formulated and executed comprehensive business strategies that helped transition the start-up into a stable organization. This experience helped him hone his strategic thinking, resource optimization, and market analysis skills. His involvement with Amazon Web Services (AWS) as a Professional Service Intern in 2020 allowed him to work on advanced machine learning models, particularly enhancing predictive analysis and using optimization algorithms. His professional journey has provided him with a wealth of experience, particularly in data-driven decision-making and strategic innovation.

📚 Contributions and Research Focus

Throughout his academic and professional career, Mr. Liu has contributed significantly to data-driven research. Notably, his research as a Barrett College Fellow at ASU in 2019-2022 focused on understanding consumer behavior and the preferences of hydrogen vehicle owners in California. He applied multinomial logistic regression and null hypothesis significance testing to evaluate the factors influencing gas station choices. Mr. Liu also contributed as a Research Assistant at ASU, co-authoring a published paper on mathematical modeling for cancer treatment responses. His research focus has consistently centered on the intersection of data analytics, machine learning, and their applications in real-world challenges.

🌍 Impact and Influence

Mr. Liu’s diverse experiences in data analytics, machine learning, and business strategy have had a significant impact on both academic and professional fields. His work with Amazon on developing predictive models and enhancing customer trend analysis reflects a deep understanding of how technology can transform business outcomes. Additionally, his entrepreneurial work in founding Hans & Associates and MiStraws demonstrates his ability to leverage data-driven insights for sustainable business growth. His contributions have influenced the development of strategic innovation, particularly in the use of AI to drive market forecasting and customer behavior analysis.

📑 Academic Citations

One of Mr. Liu’s key academic achievements was his co-authorship of a published paper titled “Clinical Data Validated Mathematical Model for Intermittent Abiraterone Response in Castration-Resistant Prostate Cancer Patients”. The research, published by SIAM Undergraduate Research Online, highlights his ability to apply complex mathematical models in the context of healthcare and medicine, contributing to the field of computational oncology. This paper demonstrates his expertise in applied mathematics and its real-world applications in clinical data analysis.

💻 Technical Skills

Mr. Liu possesses an extensive range of technical skills that span across programming languages, data analysis tools, and machine learning frameworks. Some of his core skills include proficiency in Python, SQL, and R, as well as expertise in machine learning algorithms and models such as BERT, Amazon Comprehend, and optimization techniques. He is also well-versed in Excel, Tableau, and Power BI, enabling him to deliver actionable insights from large datasets. These technical skills have been pivotal in his roles, particularly in optimizing business processes and enhancing predictive capabilities.

👨‍🏫 Teaching Experience

While Mr. Liu has not held formal teaching positions, his experiences as a research assistant and fellow at ASU have allowed him to contribute significantly to the academic community. His work on data analysis and research methodologies would have provided valuable mentorship to students and colleagues alike. His ability to communicate complex topics like statistical modeling and machine learning reflects his potential to make a meaningful impact in academia as a future educator.

🌟 Legacy and Future Contributions

Looking forward, Mr. Liu’s trajectory indicates his potential to become a key thought leader in the areas of AI-driven business analytics and strategic innovation. His multidisciplinary expertise in data science, machine learning, and business strategy positions him well to drive cutting-edge innovation in industries ranging from technology to healthcare. He envisions contributing to the advancement of AI and analytics solutions, developing models that offer enhanced business intelligence, operational efficiency, and predictive capabilities. His future contributions are poised to leave a lasting legacy, particularly in fostering sustainable business growth through data-driven decision-making and AI optimization.

Top Noted Publications 📖

  • Hydrogen Fuel Cell Vehicle Adopters Geographically Evaluate a Network of Refueling Stations in California
    • Authors: S Kelley, A Krafft, M Kuby, O Lopez, R Stotts, J Liu
    • Journal: Journal of Transport Geography
    • Year: 2020
  • Clinical Data Validated Mathematical Model for Intermittent Abiraterone Response in Castration-Resistant Prostate Cancer Patients
    • Authors: J Bennett, X Hu, K Gund, J Liu, A Porter
    • Journal: SIAM Undergraduate Research Online
    • Year: 2021
  • Extreme Heat Effects on Electric Vehicle Energy Utilization and Driving Range
    • Authors: NC Parker, M Kuby, J Liu, EB Stechel
    • Journal: Available at SSRN
    • Year: 2024

Naiwei Lu | Data Analysis | Best Researcher Award

Posted on by ScienceFather

Assoc Prof Dr. Naiwei Lu | Data Analysis | Best Researcher Award

Changsha University of Science of Technology, China

Author Profiles

Orcid

Scopus

Research Gate

👨‍🏫 Associate Prof. Dr. Naiwei Lu

Assoc. Prof. Dr. Naiwei Lu is an Associate Professor in Civil Engineering at Changsha University of Science and Technology (CSUST), China. His research primarily focuses on reliability and safety in bridge engineering. He has a strong background in system reliability evaluation, fatigue analysis, and structural health monitoring, which he applies to the engineering and maintenance of long-span bridges. Dr. Lu is an active member of various international research communities and has been involved in multiple national and international projects.

🎓 Education Background

Dr. Naiwei Lu earned his Ph.D. in Civil Engineering from Changsha University of Science and Technology (CSUST) in 2015, under the supervision of Prof. Yang Liu. Prior to that, he completed his Master’s degree in Civil Engineering in 2011 and his Bachelor’s degree in Bridge Engineering in 2008, all at CSUST, Changsha, China. His academic journey laid a strong foundation for his expertise in bridge engineering and reliability analysis.

💼 Employment and Research Experience

Dr. Lu’s academic career began in 2015 when he became a Postdoctoral Researcher at Southeast University in Nanjing, China, where he worked under Prof. Mohammad Noori. He also held a Postdoctoral Researcher position at Leibniz University Hannover, Germany, working with Prof. Michael Beer. Since 2020, Dr. Lu has been serving as an Associate Professor at CSUST, where he also previously worked as a Lecturer from 2017 to 2019. His diverse academic and international experiences contribute to his deep expertise in bridge engineering.

💰 Research Funding

Dr. Lu has been the Principal Investigator (PI) of several funded research projects, including the National Science Funding in China for research on structural health monitoring of suspension bridges and the fatigue reliability evaluation of steel bridge decks. He has received significant funding support for his work in system reliability and dynamic analysis, with total funding exceeding ¥1 million for his various research initiatives. These projects aim to develop advanced methods for assessing the reliability and safety of long-span bridges.

🔍 Research Interests

Dr. Lu’s research spans several cutting-edge topics in structural engineering. His main research interests include system reliability evaluation of long-span bridges using intelligent algorithms 🤖, fatigue reliability of stay cables and orthotropic steel bridge decks 🌉, and probabilistic modeling using data from structural health monitoring 📊. He is also focused on intelligent maintenance and management of in-service bridges ⚙️, as well as uncertainty quantification in structural engineering 🛠️.

📚 Teaching Experience

As an educator, Dr. Lu teaches undergraduate courses such as Principle of Structural Design (in both Chinese and English) and Building Information Modeling (BIM) Technology (in Chinese). He has supervised 24 undergraduate students and 4 postgraduate students between 2017 and 2020, guiding them in various aspects of civil engineering, particularly related to bridge design, maintenance, and reliability.

🏗️ Engineering Activities

In addition to his academic role, Dr. Lu is a Registered Construction Engineer and a Registered Inspection Engineer in Municipal Engineering and Bridge & Tunnel Engineering, respectively. His engineering activities include overseeing the structural safety of long-span bridges during construction 🏗️, conducting structural health monitoring of suspension bridges 🌉, and contributing to the detection and reinforcement of aging bridges 🛠️. He has also been involved in the advance geological forecasting and monitoring of tunnels during construction, working on over five extra-long tunnels.

Dr. Naiwei Lu’s work integrates advanced intelligent algorithms, data-driven methods, and structural health monitoring to enhance the safety, reliability, and longevity of bridges and infrastructure systems. His research and engineering expertise continue to make significant contributions to the field of civil engineering.

📖Top Noted Publications 

Structural damage diagnosis of a cable-stayed bridge based on VGG-19 networks and Markov transition field: numerical and experimental study

Authors: Naiwei Lu, Zengyifan Liu, Jian Cui, Lian Hu, Xiangyuan Xiao, Yiru Liu

Journal: Smart Materials and Structures

Year: 2025

Coupling effect of cracks and pore defects on fatigue performance of U-rib welds

Authors: Yuan Luo, Xiaofan Liu, Fanghuai Chen, Haiping Zhang, Xinhui Xiao, Naiwei Lu

Journal: Structures

Year: 2025

A Time–Frequency-Based Data-Driven Approach for Structural Damage Identification and Its Application to a Cable-Stayed Bridge Specimen

Authors: Naiwei Lu, Yiru Liu, Jian Cui, Xiangyuan Xiao, Yuan Luo, Mohammad Noori

Journal: Sensors

Year: 2024

A Novel Method of Bridge Deflection Prediction Using Probabilistic Deep Learning and Measured Data

Authors: Xinhui Xiao, Zepeng Wang, Haiping Zhang, Yuan Luo, Fanghuai Chen, Yang Deng, Naiwei Lu, Ying Chen

Journal: Sensors

Year: 2024

Experimental and numerical investigation on penetrating cracks growth of rib-to-deck welded connections in orthotropic steel bridge decks

Authors: Zitong Wang, Jun He, Naiwei Lu, Yang Liu, Xinfeng Yin, Haohui Xin

Journal: Structures

Year: 2024

Fatigue Reliability Assessment for Orthotropic Steel Decks: Considering Multicrack Coupling Effects

Authors: Jing Liu, Yang Liu, Guodong Wang, Naiwei Lu, Jian Cui, Honghao Wang

Journal: Metals

Year: 2024

Xueliang Han | Business Intelligence and Analytics | Best Researcher Award

Posted on by ScienceFather

Assoc Prof Dr. Xueliang Han | Business Intelligence and Analytics | Best Researcher Award

Henan University of Economics and Law, China

Author Profile

Scopus

Early Academic Pursuits 🎓

Dr. Xueliang Han’s educational journey began at Henan University of Finance and Economics, where he earned his Bachelor’s degree in Economics from the School of International Economics and Trade in 2009. He then pursued a Master of Business Administration (MBA) at Jinan University School of Management, completing his degree in 2012. This solid foundation laid the groundwork for his PhD in Management from the same university in 2016. Dr. Han’s academic training has shaped his deep understanding of organizational behavior, strategy, and the complexities of family business management.

Professional Endeavors 💼

Dr. Han’s professional career has been marked by a blend of academic excellence and practical experience. Since 2016, he has been an Associate Professor at the School of Business Administration, Henan University of Finance and Economics. His role involves not only teaching but also guiding postgraduate students as a tutor. He has contributed significantly to various national and provincial-level research projects, which underscores his engagement with both academic research and industry trends. Before his academic career, Dr. Han worked at China Life Insurance Co., Ltd. from 2012 to 2013, gaining valuable practical insights into business management.

Contributions and Research Focus 📚

Dr. Han’s research interests revolve around organizational strategy, organizational behavior, and family business theory. He has conducted several groundbreaking studies in these areas, particularly on the dynamics of family businesses in China. His work bridges the gap between theory and practice, offering insights into how organizations, particularly family-run enterprises, can thrive in the competitive business environment. His research has been published in prestigious journals such as Management Review, Psychology Science, and Foreign Economics and Management, highlighting his reputation as a thought leader in his field.

Impact and Influence 🌍

Dr. Han has made a significant impact through his academic contributions, winning numerous awards. His paper received the Mao Lixiang Outstanding Paper Award for Family Business Research and the Annual Outstanding Paper Award from the Management Thought and Business Ethics Professional Committee of the China Management Modernization Research Association. Additionally, his monograph and co-published works have been recognized, further solidifying his reputation in academic circles. His involvement in consulting, especially on industrial transformation and technology innovation, shows his broader influence beyond academia.

Academic Cites 📑

Dr. Han’s research has garnered substantial attention in the academic community. His publications in high-quality journals such as Management Review and Foreign Economics and Management have earned him citations from peers worldwide. This reflects the importance of his work, particularly in the domains of organizational strategy and family business studies. His contributions to the field have helped shape how these areas are understood and applied, both in China and internationally.

Technical Skills 🖥️

Dr. Han possesses a diverse set of technical skills essential for his academic and research endeavors. He has led national-level projects, participated in social and natural science research, and collaborated with various academic and governmental bodies. His knowledge extends into business intelligence, data management, and technological innovations in management systems, making him well-versed in the evolving landscape of business technology.

Teaching Experience 📚👨‍🏫

As a seasoned educator, Dr. Han has taught a variety of courses at Henan University of Finance and Economics. His courses include “Organizational Theory and Organizational Behavior,” “Enterprise Strategic Management,” and “Entrepreneurship and Wealth Inheritance.” He is known for integrating cutting-edge research with practical applications, providing his students with a comprehensive understanding of management theory and its real-world implications. His teaching methods are praised for being interactive, research-oriented, and deeply grounded in both theory and practice.

Legacy and Future Contributions 🔮

Dr. Han’s legacy as an educator and researcher is evident in his awards and the lasting impact of his work. His future contributions are expected to continue shaping the fields of organizational behavior and family business research. He remains committed to advancing knowledge through his academic pursuits and mentoring the next generation of business leaders. With ongoing involvement in key research projects and educational initiatives, Dr. Han’s work will likely influence future management practices in both academic and corporate environments.

Top Noted Publications 📖

 Mitigate cross-market competition caused by the risk of uncertainty and improve firm performance through business intelligence
  • Authors: Han, X., Lin, T.X., Wang, X.
  • Journal: Heliyon
  • Year: 2024
BI&A capability: A discussion on the mechanism of enterprise’s performance improvement
  • Authors: Han, X., Wu, H.
  • Conference: ACM International Conference Proceeding Series
  • Year: 2019

Wenhai Shi | Predictive Modeling Innovations | Best Researcher Award

Posted on by ScienceFather

Prof. Wenhai Shi | Energy and Utilities Analytics | Best Researcher Award

Professor at Chang’an University, China

👨‍🎓Author Profiles

🎓 Early Academic Pursuits

Prof. Wenhai Shi’s academic journey is marked by a steadfast dedication to environmental sciences. He earned a Ph.D. in Soil Science (2015-2018) from the University of Chinese Academy of Sciences, Yangling, China, focusing on critical ecological processes. Prior to this, he completed his M.S. in Water Conservancy Engineering (2011-2014) at Guangxi University, Nanning, and a B.S. in Water Resources and Hydropower Engineering (2004-2008) from Xi’an University of Technology. His rigorous academic foundation laid the groundwork for his impactful career in hydrology and soil science.

💼 Professional Endeavors

Prof. Shi has built a robust professional portfolio through progressive academic and industry roles. Currently an Associate Professor at the School of Water and Environment, Chang’an University, Xi’an, he has held positions as a Lecturer and Assistant Professor in esteemed institutions, alongside early-career roles as a Laboratory Technician and Reservoir Dispatcher. These experiences have sharpened his expertise in managing large-scale water resource systems and developing ecohydrological solutions.

🌍 Contributions and Research Focus

Prof. Shi’s research addresses critical environmental challenges, including multi-scale ecohydrological processes, land surface soil and water dynamics, and the nutrient cycle in Earth’s critical zones. He is particularly renowned for investigating soil erosion mechanisms and advancing water conservation techniques. His projects, supported by prestigious bodies like the National Natural Science Foundation of China, focus on organic and inorganic carbon dynamics, hydrological simulation, and water cycle evolution in fragile ecosystems like the Loess Plateau.

🌟 Impact and Influence

Through his contributions, Prof. Shi has significantly influenced both academic and practical domains. As a reviewer for prominent international journals such as Land, Hydrology, and Remote Sensing, he ensures the dissemination of high-quality scientific knowledge. His research has enhanced understanding of hydrological systems and informed policies on sustainable water and soil management.

📚 Academic Cites

Prof. Shi is an active member of leading academic societies, including the China Soil Society and the China Society of Soil and Water Conservation, where he contributes to advancing scientific discourse. As a peer review expert for the National Natural Science Foundation of China and the Ministry of Education, his expertise shapes the future of soil and hydrology research in China and beyond.

💻 Technical Skills

With a diverse skill set, Prof. Shi excels in hydrological modeling, ecohydrological simulations, and spatial variability analysis. His technical acumen is complemented by his proficiency in research tools, project management, and data-driven decision-making in environmental sciences.

🏫 Teaching Experience

An accomplished educator, Prof. Shi has developed and taught both undergraduate and postgraduate courses, such as Soil Mechanics, Modern Hydrology, and Soil and Water Conservation. His innovative teaching methods inspire students to engage deeply with critical environmental issues. Notably, he led his students to secure the National First Prize in the 7th National College Students Water Conservancy Innovation Design Competition.

🌟 Legacy and Future Contributions

Prof. Shi’s accolades, including being recognized as a Young Academic Backbone under the Chang’an Scholars Talent Support Program, underscore his lasting contributions to academia and society. He continues to lead impactful research, mentor the next generation of environmental scientists, and innovate in teaching. Prof. Shi’s vision for the future includes enhancing sustainable practices and advancing ecohydrological resilience globally.

📖Top Noted Publications

An improved method that incorporates the estimated runoff for peak discharge prediction on the Chinese Loess Plateau
    • Authors: Shi, W.; Wang, M.; Li, D.; Li, X.; Sun, M.
    • Journal: International Soil and Water Conservation Research
    • Year: 2023
Effects of Crop Rotation and Topography on Soil Erosion and Nutrient Loss under Natural Rainfall Conditions on the Chinese Loess Plateau
    • Authors: Li, C.; Shi, W.; Huang, M.
    • Journal: Land
    • Year: 2023
An improved MUSLE model incorporating the estimated runoff and peak discharge predicted sediment yield at the watershed scale on the Chinese Loess Plateau
    • Authors: Shi, W.; Chen, T.; Yang, J.; Lou, Q.; Liu, M.
    • Journal: Journal of Hydrology
    • Year: 2022
Revised runoff curve number for runoff prediction in the Loess Plateau of China
    • Authors: Shi, W.; Wang, N.; Wang, M.; Li, D.
    • Journal: Hydrological Processes
    • Year: 2021
Predictions of soil and nutrient losses using a modified SWAT model in a large hilly-gully watershed of the Chinese Loess Plateau
    • Authors: Shi, W.; Huang, M.
    • Journal: International Soil and Water Conservation Research
    • Year: 2021

Haixia Mao | Data Science | Best Researcher Award

Posted on by ScienceFather

Dr. Haixia Mao | Data Science | Best Researcher Award

Shenzhen Polytechnic University, China

👨‍🎓Professional Profile

Scopus Profile

👩‍🏫 Summary

Dr. Haixia Mao is an Associate Professor at the School of Automobile and Transportation at Shenzhen Polytechnic University, China. She holds a Ph.D. in Geographic Information System (GIS) and Remote Sensing from the Hong Kong Polytechnic University. Her research focuses on GIS-T, big data analytics, and analyzing urban mobility patterns, using spatial-temporal data from transportation systems to improve urban planning and human behavior modeling.

🎓 Education

Dr. Mao earned her Ph.D. in GIS and Remote Sensing from the Hong Kong Polytechnic University in 2010. She also completed her M.S. in GIS at Wuhan University in 2004 and her B.S. in Photogrammetry and Remote Sensing from Wuhan University.

💼 Professional Experience

Dr. Mao currently serves as an Associate Professor at Shenzhen Polytechnic University (since 2012), where she has contributed to the development of transportation-related GIS courses. Previously, she worked as a Postdoctoral Researcher at the Hong Kong Polytechnic University from 2014 to 2016, furthering her expertise in urban computing and GIS.

📚 Research Interests

Her research encompasses GIS-T (Geographic Information Systems for Transportation), big data analytics, remote sensing, deep learning, and urban planning. She investigates the mobility patterns of citizens through traffic data (including taxis, buses, and metro) and leverages spatial-temporal data to enhance urban infrastructure and predict human behavior.

🏅 Academic Contributions

Dr. Mao has authored over 20 peer-reviewed journal articles and conference papers. She has also been awarded a patent for a caching system with a new cache placement method. She has received research grants for spatial-temporal data analytics in transportation and has actively contributed to major projects in urban computing.

💻 Technical Skills

Dr. Mao’s technical expertise spans GIS, remote sensing, big data analytics, deep learning, and spatial-temporal data analysis. She integrates these advanced techniques to solve complex transportation and urban planning challenges.

📚 Teaching Experience

Dr. Mao has taught several courses since 2012 at Shenzhen Polytechnic University, including GIS for Transportation, Traffic Engineering Cartography, and Traffic Information Processing. She has a long-standing dedication to educating future professionals in the field of urban planning and transportation technology.

 

📖Top Noted Publications

Multiple sclerosis lesions segmentation based on 3D voxel enhancement and 3D alpha matting

Authors: Sun, Y., Zhang, Y., Wang, X., Zeng, Z., Mao, H.
Journal: Chinese Journal of Medical Physics
Year: 2022

Customer attractiveness evaluation and classification of urban commercial centers by crowd intelligence

Authors: Mao, H., Fan, X., Guan, J., Wang, Y., Xu, C.
Journal: Computers in Human Behavior
Year: 2019

 When Taxi Meets Bus: Night bus stop planning over large-scale traffic data

Authors: Xiao, L., Fan, X., Mao, H., Lu, P., Luo, S.
Conference: Proceedings – 2016 7th International Conference on Cloud Computing and Big Data, CCBD 2016
Year: 2017

Characterizing On-Bus WiFi passenger behaviors by approximate search and cluster analysis

Authors: Jiang, M., Fan, X., Zhang, F., Mao, H., Liu, R.
Conference: Proceedings – 2016 7th International Conference on Cloud Computing and Big Data, CCBD 2016
Year: 2017

Efficient visibility analysis for massive observers

Authors: Wang, W., Tang, B., Fan, X., Yang, H., Zhu, M.
Conference: Procedia Computer Science
Year: 2017

Web access patterns enhancing data access performance of cooperative caching in IMANETs

Authors: Fan, X., Cao, J., Mao, H., Zhao, Y., Xu, C.
Conference: Proceedings – IEEE International Conference on Mobile Data Management
Year: 2016

Richard Ingwe Chuy | Predictive Analytics | Best Researcher Award

Posted on by ScienceFather

Dr. Richard Ingwe Chuy | Predictive Analytics | Best Researcher Award

Dr. Richard Ingwe Chuy at Programme National de Lutte contre le Sida, Congo, Democratic Republic of the

Professional Profile👨‍🎓

 👤 Summary

Richard Ingwe Chuy is a Congolese expert in methodology and statistics, specializing in biomedical research and data science. With over eight years of experience, he provides consultancy services and training in research design and statistical analysis, particularly in public health and epidemiology.

🎓 Education

  • Doctorant en Technologie de l’Information, Spécialité Science des Données
    Bircham International University, Espagne & Delaware (Mai 2022)
  • Master 2 en Méthodologie et Statistiques en Recherche Biomédicale
    Université Paris Saclay, France (2020/2021)
  • Master 1 en Méthodes en Santé Publique
    Université Paris Saclay, France (2019/2020)
  • Diplôme en Médecine Générale
    Université de Lubumbashi (UNILU), République Démocratique du Congo (2013)

💼 Professional Experience

Richard is currently a Consultant Indépendant, providing expertise in methodology and statistics to various organizations. He facilitates training on data analysis and research design. Previously, he worked at the Programme National de Lutte contre le VIH/SIDA et les IST in the Ministry of Health, DRC, and has experience in clinical medicine in Lubumbashi.

🔬 Research Interests

His research interests include methods in epidemiology and clinical studies, predictive analysis, and qualitative research. Richard is also focused on gender, human rights, and vulnerability reduction in public health contexts.

🤝 Professional Affiliations

Richard is a member of several professional organizations, including the International Aids Society (IAS), AFRAVIH, and the CQUIN network.

💻 Technical Skills

He possesses advanced skills in Microsoft Office, R, Python, SAS, and qualitative analysis software (Nvivo, QDA Miner Lite), as well as experience in electronic questionnaire design (CoboCollect, ODK).

 

Top Noted Publications 📖

Unsuppressed HIV Viral Load and Related Factors in Patients Receiving Antiretroviral Treatment in Tanganyika Province, Democratic Republic of Congo (DRC)
  • Authors: Michel Luhembwe, Richard Ingwe, Aimée Lulebo, Dalau Nkamba, John Ditekemena
  • Journal: BioMed
  • Volume: 4
  • Issue: 3
  • Pages: 27
  • Year: 2024

Seyedeh Azadeh Fallah Mortezanejad | Predictive Analytics | Best Researcher Award

Posted on by ScienceFather

Dr. Seyedeh Azadeh Fallah Mortezanejad | Predictive Analytics | Best Researcher Award

Doctorate at Jiangsu University, China

👨‍🎓 Profiles

Orcid Profile
Scopus Profile
Research Gate Profile

Dr. Seyedeh Azadeh Fallah Mortezanejad, born on July 31, 1990, in Rasht, Iran, is an accomplished statistician specializing in statistical inferences and quality control. Her work focuses on maximum entropy, copula functions, and machine learning applications, reflecting her expertise in diverse areas of statistics and data analysis.

🎓 Academic Background

Dr. Mortezanejad earned her Ph.D. in Statistical Inferences from Ferdowsi University of Mashhad, Iran (2015-2020), with a thesis on “Applications of entropy in statistical quality control.” She completed her M.Sc. in Mathematical Statistics at Guilan University, Rasht, Iran (2012-2014), where her thesis was titled “Semi-parametric estimation of conditional Copula.” Her academic journey began with a B.Sc. in Statistics from Guilan University, Rasht, Iran (2008-2012).

💼 Professional Experience

Dr. Mortezanejad has taught various courses at prominent institutions, including Ferdowsi University of Mashhad and University of Guilan. Her teaching experience includes courses such as Statistics and Probability for Engineering, Applied Statistics 2, and Statistics and Probabilities in Management. Additionally, she has served as a Teacher Assistant for several courses, including “Statistics for Economy I and II” and “Mathematical Statistics,” at Ferdowsi University of Mashhad.

🔬 Research Interests

Her research interests encompass a range of topics including Maximum Entropy, Measures of Information, Copula Functions, Tied Observations, Machine Learning, Image Processing, Quality Control, and Control Charts. Dr. Mortezanejad’s work explores innovative applications and methodologies in these fields.

📝 Published Articles

Dr. Mortezanejad has authored several notable publications. Her work includes articles such as “Variational Bayesian Approximation (VBA): Implementation and Comparison of Different Optimization Algorithms” in Entropy (2024) and “Joint dependence distribution of data set using optimizing Tsallis copula entropy” in Physica A (2019). Other significant contributions include research on entropic structures in capability indices and the analysis of stock data based on copula functions.

🎤 Seminars

Dr. Mortezanejad has actively participated in international seminars and workshops. Notable presentations include “Profile Control Chart Based on Maximum Entropy” at the International Workshop on Responsible AI in Vietnam (2023) and discussions on Variational Bayesian Approximation (VBA) at the 41st and 42nd International Workshops on Bayesian Inference in France and Germany (2022-2023). She has also contributed to workshops on copula theory and information measures in Iran.

🧑‍🔬 Reviewer

She has been recognized as a Certified Reviewer for Helion Journal (2024) and has served as a reviewer for the 16th FLINS Conference and the 19th ISKE Conference in Spain (2024).

💻 Software Skills

Dr. Mortezanejad is proficient in several software and programming languages, including Python, R, MATLAB, Scilab, and C++. She is also skilled in SPSS Modeler, SPSS Statistics, and Minitab, with experience in using Latex for academic writing and documentation.

📖 Publications

Variational Bayesian Approximation (VBA): Implementation and Comparison of Different Optimization Algorithms”

  • Authors: Seyedeh Azadeh Fallah Mortezanejad, Ali Mohammad-Djafari
    Journal: Entropy
    Year: 2024

Variational Bayesian Approximation (VBA) with Exponential Families and Covariance Estimation

  • Authors: Seyedeh Azadeh Fallah Mortezanejad, Ali Mohammad-Djafari
    Journal: Physical Sciences Forum
    Year: 2023

Variational Bayesian Approximation (VBA): A Comparison between Three Optimization Algorithms

  • Authors: Seyedeh Azadeh Fallah Mortezanejad, Ali Mohammad-Djafari
    Conference: MaxEnt 2022
    Year: 2023

Evaluation of Anti-lice Topical Lotion of Ozonated Olive Oil and Comparison of its Effect with Permethrin Shampoo

  • Authors: Omid Rajabi, Atoosa Haghighizadeh, Seyedeh Azadeh Fallah Mortezanejad, Saba Dadpour
    Journal: Reviews on Recent Clinical Trials
    Year: 2022

An Entropic Structure in Capability Indices

  • Authors: Seyedeh Azadeh Fallah Mortezanejad, Gholamreza Mohtashami Borzadaran, Bahram Sadeghpour Gildeh
    Journal: Communications in Statistics – Theory and Methods
    Year: 2019

Joint Dependence Distribution of Data Set Using Optimizing Tsallis Copula Entropy

  • Authors: Seyedeh Azadeh Fallah Mortezanejad, Gholamreza Mohtashami Borzadaran, Bahram Sadeghpour Gildeh
    Journal: Physica A: Statistical Mechanics and its Applications
    Year: 2019