Wenhai Shi | Predictive Modeling Innovations | Best Researcher Award

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

Natasa Zivic | Predictive Analytics | Best Researcher Award

Prof Dr. Natasa Zivic | Predictive Analytics | Best Researcher Award

Prof Dr. Natasa Zivic at University of Applied Sciences in Leipzig, Germany

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🌟Summary

Prof. Dr.-Ing. habil. Natasa Zivic is a distinguished professor specializing in information and coding theory and real-time image processing at the University of Applied Sciences in Leipzig, Germany. She is a leading researcher in predictive data analysis and robust real-time image and message communications, with a particular focus on applications in artificial intelligence and the car industry. Prof. Zivic has an extensive publication record, including 9 books, over 100 conference and journal papers, and several patents. She actively participates in international conferences and serves as a reviewer and editor for various scientific journals.

🎓Education

  • Ph.D. in Electrical Engineering, University of Siegen, Germany, 2007
  • Postdoctoral Habilitation, University of Siegen, Germany, 2013
  • Magister Thesis, University of Belgrade, Serbia, 2002
  • Bachelor’s Degree in Electrical Engineering, University of Belgrade, Serbia, 1999

💼 Professional Experience

Prof. Dr.-Ing. habil. Natasa Zivic is currently a professor at the University of Applied Sciences in Leipzig, Germany, where she specializes in information and coding theory and real-time image processing. Her professional experience spans various roles, including serving as a security expert in the car industry. Prof. Zivic is actively engaged in research focused on predictive data analysis and robust real-time image and message communications, particularly within the context of artificial intelligence. She has a prolific publication record, authoring 9 books, over 100 conference and journal papers, and several patents. Additionally, Prof. Zivic is a regular participant in international conferences and contributes to the academic community as a reviewer and editor for numerous scientific journals.

🔬 Research Interests

Prof. Dr.-Ing. habil. Natasa Zivic’s research interests lie at the intersection of predictive data analysis, robust real-time image and message communications, and artificial intelligence. She is particularly focused on developing innovative solutions for enhancing the efficiency and security of communication systems in real-time environments. Her work extends to the automotive industry, where she explores the application of advanced AI techniques to improve vehicle communication and security systems. Prof. Zivic is dedicated to advancing the field through her research, publications, and active participation in the scientific community.

📖 Publication Top Noted

  • Authors: Obaid Ur-Rehman, Natasa Zivic
    Journal: Störungstolerante Datenauthentifizierung für drahtlose Kommunikation
  • Year: 2024
  • Authors: Cyril Neba, Gillian Nsuh, Adrian Neba, F Webnda, Victory Ikpe, Adeyinka Orelaja, Nabintou Anissia Sylla
    Journal: Asian Research Journal of Mathematics
  • Year: 2024
  • Authors: Obaid Ur-Rehman, Natasa Zivic
    Journal: Störungstolerante Datenauthentifizierung für drahtlose Kommunikation
  • Year: 2024
  • Authors: Obaid Ur-Rehman, Natasa Zivic
    Journal: Störungstolerante Datenauthentifizierung für drahtlose Kommunikation
  • Year: 2024
  • Authors: Obaid Ur-Rehman, Natasa Zivic
    Journal: Störungstolerante Datenauthentifizierung für drahtlose Kommunikation
  • Year: 2024

Chenwi Neba Cyril | Predictive Analytics | Excellence in Research

Mr. Chenwi Neba Cyril ,Predictive Analytics, Excellence in Research

Austin Peay State University, United States

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🌟Summary

Chenwi Neba Cyril is a seasoned Predictive Data Analyst at Walmart Inc. and holds a Master’s Degree in Computer Science and Quantitative Methods. His expertise spans predictive analytics, with notable contributions in retail sales forecasting, credit card fraud detection, and environmental research. Cyril has published extensively in reputable journals and actively engages in consultancy projects. His current research focuses on integrating predictive analytics into geochemistry, advancing cancer detection through machine learning, and developing data-driven solutions for cybersecurity and public health challenges.

🎓Education

Chenwi Neba Cyril holds a Master’s Degree in Computer Science and Quantitative Methods with a concentration in Predictive Analytics from Austin Peay State University, USA, where he graduated with a perfect GPA of 4.00. He also earned Bachelor’s and Master’s degrees in Earth and Space Sciences from the University of Yaoundé I in Cameroon. His academic journey has equipped him with a robust foundation in both technical sciences and advanced quantitative methods, facilitating his expertise in predictive data analysis and research across diverse domains.

💼 Professional Experience

Chenwi Neba Cyril currently serves as a Pricing Analyst and Manager at Walmart Inc., where he applies his extensive knowledge of data science and predictive analytics to drive strategic business decisions. His role involves leveraging advanced analytical techniques to optimize pricing strategies and enhance revenue growth. Cyril has also undertaken consultancy projects with multiple banks, specializing in improving fraud detection systems and customer relationship management through predictive analytics. Additionally, he has collaborated with microfinance institutions in Cameroon on projects aimed at implementing data-driven solutions for environmental challenges and sustainable development initiatives. His professional journey reflects a commitment to leveraging analytics to drive innovation and impact across various sectors.

🔬 Research Interests

Chenwi Neba Cyril’s research interests are interdisciplinary, spanning the integration of predictive analytics in geochemistry, machine learning applications for cancer detection, data-driven cybersecurity for military operations, and combating the opioid epidemic through advanced analytics. His current research aims to apply predictive analytics to identify geochemical pathways and predict mineral sources, revolutionize cancer detection methodologies through machine learning advancements, develop proactive cybersecurity solutions for military networks, and optimize interventions to mitigate the opioid crisis using big data analytics. Cyril’s work underscores a commitment to harnessing data-driven approaches to address complex societal challenges and drive transformative outcomes in public health and cybersecurity domains.

📖 Publication Top Noted

  • Authors: Cyril Neba, Gillian Nsuh, Adrian Neba, F Webnda, Victory Ikpe, Adeyinka Orelaja, Nabintou Anissia Sylla
  • Journal: Unfallchirurgie (Germany)
  • Volume: 20
  • Issue: 7
  • Pages: 9-30
  • Year: 2024

Article : Advancing Retail Predictions: Integrating Diverse Machine Learning Models for Accurate Walmart Sales Forecasting

  • Authors: Nabintou Anissia Sylla, Cyril Neba C., Gerard Shu F., Gillian Nsuh, Philip Amouda A., Adrian Neba F., F. Webnda, Victory Ikpe, Adeyinka Orelaja
  • Journal: Asian Journal of Probability and Statistics
  • Volume: 26
  • Issue: 7
  • Pages: 1-23
  • Year: 2024

Article : Comparative Analysis of Stock Price Prediction Models: Generalized Linear Model (GLM), Ridge Regression, Lasso Regression, Elasticnet Regression, and Random Forest – A Case …

  • Authors: Cyril Neba C., Gillian Nsuh, Gerard Shu F., Philip Amouda A., Adrian Neba F., Aderonke Adebisi, P. Kibet., F. Webnda
  • Journal: International Journal of Innovative Science and Research Technology
  • Volume: 8
  • Issue: 10
  • Pages: 12
  • Year: 2023

Article : Time Series Analysis and Forecasting of COVID-19 Trends in Coffee County, Tennessee, United States

  • Authors: Cyril Neba C., Gerard Shu F., Gillian Nsuh, Philip Amouda A., Adrian Neba F., Aderonke Adebisi, P. Kibet., F. Webnda
  • Journal: International Journal of Innovative Science and Research Technology
  • Volume: 8
  • Issue: 9
  • Pages: 14
  • Year: 2023

Article : Using Regression Models to Predict Death Caused by Ambient Ozone Pollution (AOP) in the United States

  • Authors: Cyril Neba C., Gerard Shu F., Adrian Neba F., Aderonke Adebisi, P. Kibet., F. Webnda, Philip Amouda A.
  • Journal: International Journal of Innovative Science and Research Technology
  • Volume: 8
  • Issue: 9
  • Pages: 18
  • Year: 2023

Chenwi Neba Cyril | Predictive Analytics | Best Researcher Award

Mr. Chenwi Neba Cyril ,Predictive Analytics, Best Researcher Award

Austin Peay State University, United States

Author Profile

Orcid Profile
Google Scholar Profile
Research Gate Profile

🌟Summary

Chenwi Neba Cyril is a seasoned Predictive Data Analyst at Walmart Inc. and holds a Master’s Degree in Computer Science and Quantitative Methods. His expertise spans predictive analytics, with notable contributions in retail sales forecasting, credit card fraud detection, and environmental research. Cyril has published extensively in reputable journals and actively engages in consultancy projects. His current research focuses on integrating predictive analytics into geochemistry, advancing cancer detection through machine learning, and developing data-driven solutions for cybersecurity and public health challenges.

🎓Education

Chenwi Neba Cyril holds a Master’s Degree in Computer Science and Quantitative Methods with a concentration in Predictive Analytics from Austin Peay State University, USA, where he graduated with a perfect GPA of 4.00. He also earned Bachelor’s and Master’s degrees in Earth and Space Sciences from the University of Yaoundé I in Cameroon. His academic journey has equipped him with a robust foundation in both technical sciences and advanced quantitative methods, facilitating his expertise in predictive data analysis and research across diverse domains.

💼 Professional Experience

Chenwi Neba Cyril currently serves as a Pricing Analyst and Manager at Walmart Inc., where he applies his extensive knowledge of data science and predictive analytics to drive strategic business decisions. His role involves leveraging advanced analytical techniques to optimize pricing strategies and enhance revenue growth. Cyril has also undertaken consultancy projects with multiple banks, specializing in improving fraud detection systems and customer relationship management through predictive analytics. Additionally, he has collaborated with microfinance institutions in Cameroon on projects aimed at implementing data-driven solutions for environmental challenges and sustainable development initiatives. His professional journey reflects a commitment to leveraging analytics to drive innovation and impact across various sectors.

🔬 Research Interests

Chenwi Neba Cyril’s research interests are interdisciplinary, spanning the integration of predictive analytics in geochemistry, machine learning applications for cancer detection, data-driven cybersecurity for military operations, and combating the opioid epidemic through advanced analytics. His current research aims to apply predictive analytics to identify geochemical pathways and predict mineral sources, revolutionize cancer detection methodologies through machine learning advancements, develop proactive cybersecurity solutions for military networks, and optimize interventions to mitigate the opioid crisis using big data analytics. Cyril’s work underscores a commitment to harnessing data-driven approaches to address complex societal challenges and drive transformative outcomes in public health and cybersecurity domains.

📖 Publication Top Noted

  • Authors: Cyril Neba, Gillian Nsuh, Adrian Neba, F Webnda, Victory Ikpe, Adeyinka Orelaja, Nabintou Anissia Sylla
  • Journal: Unfallchirurgie (Germany)
  • Volume: 20
  • Issue: 7
  • Pages: 9-30
  • Year: 2024

Article : Advancing Retail Predictions: Integrating Diverse Machine Learning Models for Accurate Walmart Sales Forecasting

  • Authors: Nabintou Anissia Sylla, Cyril Neba C., Gerard Shu F., Gillian Nsuh, Philip Amouda A., Adrian Neba F., F. Webnda, Victory Ikpe, Adeyinka Orelaja
  • Journal: Asian Journal of Probability and Statistics
  • Volume: 26
  • Issue: 7
  • Pages: 1-23
  • Year: 2024

Article : Comparative Analysis of Stock Price Prediction Models: Generalized Linear Model (GLM), Ridge Regression, Lasso Regression, Elasticnet Regression, and Random Forest – A Case …

  • Authors: Cyril Neba C., Gillian Nsuh, Gerard Shu F., Philip Amouda A., Adrian Neba F., Aderonke Adebisi, P. Kibet., F. Webnda
  • Journal: International Journal of Innovative Science and Research Technology
  • Volume: 8
  • Issue: 10
  • Pages: 12
  • Year: 2023

Article : Time Series Analysis and Forecasting of COVID-19 Trends in Coffee County, Tennessee, United States

  • Authors: Cyril Neba C., Gerard Shu F., Gillian Nsuh, Philip Amouda A., Adrian Neba F., Aderonke Adebisi, P. Kibet., F. Webnda
  • Journal: International Journal of Innovative Science and Research Technology
  • Volume: 8
  • Issue: 9
  • Pages: 14
  • Year: 2023

Article : Using Regression Models to Predict Death Caused by Ambient Ozone Pollution (AOP) in the United States

  • Authors: Cyril Neba C., Gerard Shu F., Adrian Neba F., Aderonke Adebisi, P. Kibet., F. Webnda, Philip Amouda A.
  • Journal: International Journal of Innovative Science and Research Technology
  • Volume: 8
  • Issue: 9
  • Pages: 18
  • Year: 2023