Seyedeh Azadeh Fallah Mortezanejad | Predictive Analytics | Best Researcher Award

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

Doctorate at Jiangsu University, China

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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

 

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