Jingteng Liu | Business Analytics | Best Researcher Award

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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.

đź’Ľ 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.

đź“š 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.

đź“‘ 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.

đź’» 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 đź“–

  • 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

Vahid Naghashi | Temporal Data Patterns | Best Researcher Award

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Mr. Vahid Naghashi | Temporal Data Patterns | Best Researcher Award

Innovation Chair in Animal Welfare and Artificial Intelligence (WELL-E), Canada

Author Profile

Google Scholar

Early Academic Pursuits đź“š

Mr. Vahid Naghashi is currently a Ph.D. candidate, focusing on forecasting dairy income during future lactations using deep learning models. His academic journey reflects a strong foundation in time series forecasting, machine learning, and deep learning. Throughout his academic career, he has excelled in advancing knowledge in computational models and applied artificial intelligence.

Professional Endeavors đź’Ľ

Mr. Naghashi’s career has also been shaped by professional industry experience, including an internship at a multimedia company. During his internship, he worked on projects involving Large Language Models (LLMs) and audio processing with foundation models. His exposure to real-world applications of deep learning models has broadened his expertise in both academic and industry settings.

Contributions and Research Focus 🔬

Mr. Naghashi’s research primarily focuses on time series forecasting using deep learning techniques. His major research project involves the prediction of milk profits in future lactations, an area of great relevance to the dairy industry. One of his notable contributions is the development of a multiscale model for multivariate time series forecasting, which has applications across various fields, published in Nature Scientific Reports.

Impact and Influence 🌍

The impact of Mr. Naghashi’s work extends beyond academia. His contributions to the field of deep learning for time series forecasting can significantly transform industries like dairy farming. His work in forecasting and data analytics has proven to be useful in real-world scenarios, with a growing citation index, indicating the broader influence of his research.

Academic Cites đź“‘

His work has been recognized in several prestigious journals, including his recent article published in Nature Scientific Reports, which has been widely cited. Additionally, his research article “A multiscale model for multivariate time series forecasting” is a key example of his contributions to the academic community, helping to shape future research directions in time series analysis and forecasting.

Technical Skills 🧑‍💻

Mr. Naghashi possesses extensive technical expertise in deep learning, machine learning, and time series forecasting. He has proficiency in advanced data science tools and techniques, including large-scale machine learning models, deep neural networks, and predictive analytics, which are crucial in his research and consultancy projects.

Teaching Experience 👨‍🏫

While there is no direct mention of formal teaching roles, Mr. Naghashi’s research and consultancy work undoubtedly involve mentoring and knowledge sharing within his academic collaborations and industry projects. His involvement with the Innovation Chair in Animal Welfare and Artificial Intelligence (WELL-E) demonstrates his commitment to educating others in his field.

Legacy and Future Contributions đź”®

Looking forward, Mr. Naghashi aims to further advance deep learning methodologies, particularly in forecasting applications across industries such as agriculture, healthcare, and finance. His future research goals include enhancing predictive models and working on larger-scale applications that have a lasting impact on both academic and professional communities.

Top Noted Publications đź“–

Co-occurrence of adjacent sparse local ternary patterns: A feature descriptor for texture and face image retrieval
    • Authors: V. Naghashi
    • Journal: Optik
    • Year: 2018
Evaluation of dominant and non-dominant hand movements for volleyball action modelling
    • Authors: F. Haider, F. Salim, V. Naghashi, SBY Tasdemir, I. Tengiz, K. Cengiz, …
    • Journal: Adjunct of the 2019 International Conference on Multimodal Interaction
    • Year: 2019
Volleyball action modelling for behavior analysis and interactive multi-modal feedback
    • Authors: FA Salim, F. Haider, SBY Tasdemir, V. Naghashi, I. Tengiz, K. Cengiz, …
    • Journal: eNTERFACE’19: 15th International Summer Workshop on Multimodal Interfaces
    • Year: 2020
A searching and automatic video tagging tool for events of interest during volleyball training sessions
    • Authors: F. Salim, F. Haider, SBY Tasdemir, V. Naghashi, I. Tengiz, K. Cengiz, …
    • Journal: 2019 International Conference on Multimodal Interaction
    • Year: 2019
A multiscale model for multivariate time series forecasting
    • Authors: V. Naghashi, M. Boukadoum, AB Diallo
    • Journal: Scientific Reports
    • Year: 2025

Lucia Grumetto | Predictive Analytics | Best Researcher Award

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Prof. Lucia Grumetto | Predictive Analytics | Best Researcher Award

UniversitĂ  di napoli Dipartimento di Farmacia, Italy

👨‍🎓 Author Profiles

🎓 Academic Foundations and Professional Development

Prof. Lucia Grumetto’s academic path began at the University of Naples Federico II, where she completed dual degrees in Pharmacy and Biological Sciences. Over her extensive career, she gained considerable experience as a Researcher, later advancing to Associate Professor in the same institution. Her qualifications are further reinforced by a Master’s Degree in Food Law (2014), underscoring her ability to integrate scientific knowledge with legal and regulatory expertise, particularly in food safety.

đź’Ľ Professional Endeavors and Expertise

Throughout her career, Prof. Grumetto has contributed significantly to both pharmaceutical research and education. Her professional journey spans multiple roles, including Researcher, Professor, and Consultant in the areas of toxicology, pharmacokinetics, and environmental health. She has been actively involved in key research initiatives aimed at understanding the behavior of endocrine disruptors in biological systems, including the human blood-brain barrier and ocular barriers. Her research projects on sustainable drug formulations and environmental monitoring are crucial in addressing both public health and ecological concerns.

🔬 Research Focus and Scientific Contributions

Prof. Grumetto’s research has a broad scope, ranging from drug development to environmental health. She has led investigations into the pharmacokinetics of pharmaceutical compounds, focusing on their absorption, distribution, and metabolism in different biological systems. Her work on the interaction of endocrine disruptors in food and environmental matrices has positioned her as a leading expert in toxicology. Notable projects include the study of pharmaceutical permeation through biological membranes and the development of novel drug delivery systems targeting cancer therapies. Her contributions have been widely recognized through numerous publications, awards, and collaborations with international research networks.

🌍 Impact on Academia and Scientific Communities

Prof. Grumetto has profoundly impacted the scientific community through her research, teaching, and publications. With over 80 peer-reviewed papers and presentations at global conferences, she has shared her expertise in pharmacokinetics, endocrine toxicology, and drug testing. Her work on endocrine disruptors has not only influenced academic research but also shaped policies on environmental safety and public health. Her Most Cited Paper Award from the European Journal of Pharmaceutical Sciences and the Best Poster Award at various symposia are testaments to her influence. Additionally, she serves on the Editorial Boards of several high-impact journals, further contributing to the academic world.

👩‍🏫 Teaching and Pedagogical Innovations

Prof. Grumetto is deeply committed to education, having taught various specialized courses at the University of Naples Federico II. Her courses, such as Quality Control and Food Safety Regulations and Xenobiotic Analysis, are integral parts of the curricula for students pursuing degrees in Nutraceutical Sciences and Pharmaceutical Sciences. Beyond her classroom responsibilities, she has taken on leadership roles in shaping internship programs and curricular development, ensuring students gain hands-on experience and the necessary skills to succeed in their professional careers.

🔧 Technical Expertise and Analytical Innovations

One of Prof. Grumetto’s strengths lies in her technical expertise, particularly in the field of analytical chemistry. Her pioneering work with HPLC, mass spectrometry, and immobilized artificial membranes (IAM) has significantly advanced pharmacokinetic research. She has developed innovative methodologies for studying drug interactions and their bioavailability, especially for substances that cross biological barriers like the blood-brain barrier. These techniques are essential for understanding drug absorption and improving drug delivery systems.

🏆 Recognition, Awards, and Achievements

Prof. Grumetto’s contributions have been recognized with numerous awards and honors. In addition to her Best Poster Awards at international conferences, she received the Most Cited Paper Award from the European Journal of Pharmaceutical Sciences. She holds several patents, including one for a dermatological patch test device to identify allergic reactions to medications. Her innovations have extended beyond the academic realm, influencing practical applications in medicine, environmental monitoring, and sustainability.

🚀 Future Contributions and Vision

Looking ahead, Prof. Grumetto continues to push boundaries in both pharmaceutical research and sustainability. Her current projects, such as FRUIPAD, aim to create biodegradable food packaging from fruit by-products, highlighting her commitment to both environmental sustainability and public health. Her ongoing studies in endocrine disruptors and drug delivery systems hold the potential to influence future healthcare strategies, particularly in personalized medicine and targeted therapies. As she continues to lead innovative projects and collaborate internationally, her future contributions will likely reshape the way pharmaceuticals and environmental health issues are addressed globally.

đź“– Top Noted Publications

 The combined use of biological investigations, bio chromatographic and in silico methods to solve the puzzle of badge and its derivative’s toxicity
  • Authors: Ilaria Neri, Marialuisa Piccolo, Giacomo Russo, Maria Grazia Ferraro, Vincenzo Marotta, Rita Santamaria, Lucia Grumetto
    Journal: Chemosphere
    Year: 2024
Phenylalanine Butyramide: A Butyrate Derivative as a Novel Inhibitor of Tyrosinase
  • Authors: Ritamaria Di Lorenzo, Vincenzo Di Lorenzo, Teresa Di Serio, Adua Marzocchi, Lucia Ricci, Eleonora Vardaro, Giovanni Greco, Maria Maisto, Lucia Grumetto, Vincenzo Piccolo et al.
    Journal: International Journal of Molecular Sciences
    Year: 2024
Investigating the Effect of Surface Hydrophilicity on the Destiny of PLGA-Poloxamer Nanoparticles in an In Vivo Animal Model
  • Authors: Teresa Silvestri, Lucia Grumetto, Ilaria Neri, Maria De Falco, Sossio Fabio Graziano, Sara Damiano, Daniela Giaquinto, Lucianna Maruccio, Paolo de Girolamo, Fabrizio Villapiano et al.
    Journal: International Journal of Molecular Sciences
    Year: 2023
Dermocosmetic evaluation of a nutricosmetic formulation based on Curcuma
  • Authors: Ritamaria Di Lorenzo, Lucia Grumetto, Antonia Sacchi, Sonia Laneri, Irene Dini
    Journal: Phytotherapy Research
    Year: 2023
Validation of an LC-MS/MS Method for the Determination of Abscisic Acid Concentration in a Real-World Setting
  • Authors: Elisabetta Schiano, Ilaria Neri, Maria Maisto, Ettore Novellino, Fortuna Iannuzzo, Vincenzo Piccolo, Vincenzo Summa, Lucia Grumetto, Gian Carlo Tenore
    Journal: Foods
    Year: 2023

Jianhong Hao | Predictive Analytics | Best Researcher Award

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Dr. Jianhong Hao | Predictive Analytics | Best Researcher Award

Doctorate at Honghui Hosipital, Xi’an Jiaotong University, China

👨‍🎓Professional Profiles

👨‍⚕️ Summary

Dr. Jianhong Hao is a Master of Anesthesia and a prominent researcher in perioperative care at Honghui Hospital, Xi’an Jiaotong University, China. His expertise lies in analyzing risk factors for perioperative complications and applying ultrasound technology for airway management. With over 9 SCI papers published in the last five years, his research focuses on improving patient outcomes, particularly in trauma and post-surgical settings.

🎓 Education

Dr. Hao completed his Master of Anesthesia at Xi’an Jiaotong University, where he developed a strong foundation in clinical anesthesia and perioperative medicine.

🏥 Professional Experience

Currently, Dr. Hao serves as a clinical specialist and researcher at Honghui Hospital. He specializes in risk factor analysis for perioperative complications and has made significant contributions to optimizing care for trauma and surgical patients.

đź“š Academic Citations

Dr. Hao’s research is widely recognized in the scientific community. His publications in journals like Journal of Clinical Anesthesia and BMC Anesthesiology cover diverse topics such as postoperative pulmonary complications (PPCs) and the use of ultrasound in predicting respiratory issues in trauma patients.

đź’» Technical Skills

Dr. Hao is skilled in utilizing ultrasound technology for airway management and perioperative care. He also specializes in statistical modeling, data analysis, and risk factor identification for various surgical complications, with an emphasis on predictive tools and clinical trials.

👩‍🏫 Teaching Experience

In addition to his clinical and research work, Dr. Hao is an educator at Xi’an Jiaotong University, where he mentors medical students and residents in anesthesia and perioperative management.

🔬 Research Interests

Dr. Hao’s research interests center around the identification of risk factors for perioperative complications, especially those involving trauma patients. His ongoing projects include developing risk stratification models based on lung ultrasound scores for traumatic lung injuries and optimizing care for patients with postoperative pulmonary complications.

🏅 Key Contributions

Dr. Hao has made pioneering contributions in the use of postoperative lung ultrasound scores to predict pulmonary complications in patients with blunt thoracic trauma. His work also includes developing models for early identification of risks in trauma patients and optimizing blood use in surgery

🤝 Collaborations

Dr. Hao collaborates with multidisciplinary teams at Honghui Hospital and is an active member of the Shaanxi Clinical Trial Research Society, contributing to ongoing clinical studies and evidence-based practices in anesthesia.

Rahul Pratap Singh | Data Analysis | Best Researcher Award

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Dr. Rahul Pratap Singh | Data Analysis | Best Researcher Award

Dr. Rahul Pratap Singh at Veer Bahadur Singh Purvanchal University Jaunpur, India

👨‍🎓 Profile

👤 Summary

Dr. Rahul Pratap Singh is a dedicated physicist specializing in semiconducting and magnetic nanomaterials. His research focuses on their synthesis, characterization, and industrial applications, utilizing advanced spectroscopic techniques and electron microscopy.

🎓 Education

Dr. Singh holds a PhD in Physics from Veer Bahadur Singh Purvanchal University, where he investigated semiconducting nanomaterials and their industrial applications. He completed his M.Sc. and B.Sc. in Physics & Maths at Pratap Bahadur Post Graduate College, and his schooling in Science and Mathematics at Government Inter College, Pratapgarh.

đź’Ľ Professional Experience

He has taught both undergraduate and postgraduate courses at S.V.M. Science and Technology Post Graduate College since 2016, with additional experience at B.N.S. Post Graduate College in 2017-2018.

🔧 Technical Skills

Dr. Singh is skilled in the synthesis and characterization of nanomaterials, as well as various spectroscopic techniques (IR, Raman, XRD) and electron microscopy (SEM, TEM).

🔬 Research Interests

His research interests include the synthesis and characterization of semiconducting and magnetic nanomaterials, as well as 2D materials, focusing on their potential industrial applications.

 

📖 Top Noted Publications 

Humidity sensing study of cobalt-doped cadmium sulphide nanomaterials
    • Authors: Rahul Pratap Singh, Prabhat Ranjan Tiwari, Keval Bharati, Bala Bhardwaj, Kuwar Ankur Singh, B. C. Yadav, Prof. Santosh Kumar
    • Journal: Journal of Solid State Electrochemistry
    • Year: 2023
Synthesis and Characterization of Manganese Doped Zinc Ferrite for its Structural and Magnetic Properties
    • Authors: Avinash Chand Yadav, Prabhat Ranjan Tiwari, Rahul Pratap Singh, Gulab Singh, Ajaz Hussain, Mukul Gupta, Aartee Sharma, Manvendra Kumar, Prof. Santosh Kumar
    • Journal: Iranian Journal of Science
    • Year: 2023
Synthesis of bismuth-doped praseodymium ortho ferrite nanomaterials for LPG sensing
    • Authors: Keval Bharati, Prabhat Ranjan Tiwari, Rahul Pratap Singh, Ajeet Singh, Bal Chandra Yadav, Manish Pratap Singh, Prof. Santosh Kumar
    • Journal: Applied Nanoscience
    • Year: 2023
Cobalt-doped praseodymium ortho ferrite as a promising nanomaterial for carbon dioxide gas sensing
    • Authors: Keval Bharati, Prabhat Ranjan Tiwari, Rahul Pratap Singh, Bala, Ajeet Singh, Bal Chandra Yadav, Prof. Santosh Kumar
    • Journal: Journal of Materials Chemistry C
    • Year: 2023
Nickel-Doped Cadmium Sulphide as a Promising Nanomaterials for Humidity Sensing Applications
    • Authors: Rahul Pratap Singh, Prabhat Ranjan Tiwari, Keval Bharati, Bala, Kuwar Ankur Singh, B. C. Yadav, Santosh Kumar
    • Journal: Sensing and Imaging
    • Year: 2023
Synthesis of calcium doped zinc ferrite nanomaterial and its application as a humidity sensor
    • Authors: Prabhat Ranjan Tiwari, Rahul Pratap Singh, Keval Bharati, Avinash Chand Yadav, Bal Chand Yadav, Ajeet Singh, Manish Pratap Singh, Santosh Kumar
    • Journal: Journal of Dispersion Science and Technology
    • Year: 2023

Richard Ingwe Chuy | Predictive Analytics | Best Researcher Award

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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, SpĂ©cialitĂ© Science des DonnĂ©es
    Bircham International University, Espagne & Delaware (Mai 2022)
  • Master 2 en MĂ©thodologie et Statistiques en Recherche BiomĂ©dicale
    Université Paris Saclay, France (2020/2021)
  • Master 1 en MĂ©thodes en SantĂ© Publique
    Université Paris Saclay, France (2019/2020)
  • DiplĂ´me en MĂ©decine GĂ©nĂ©rale
    Université de Lubumbashi (UNILU), République Démocratique du Congo (2013)

đź’Ľ 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.

đź’» 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 đź“–

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, AimĂ©e Lulebo, Dalau Nkamba, John Ditekemena
  • Journal: BioMed
  • Volume: 4
  • Issue: 3
  • Pages: 27
  • Year: 2024

Seyedeh Azadeh Fallah Mortezanejad | Predictive Analytics | Best Researcher Award

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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).

đź’Ľ 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.

đź“ť 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).

đź’» 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.

đź“– 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

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

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

Author Profile

Orcid Profile
Google Scholar

🌟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

đź’Ľ 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.

đź“– 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

Published on by Research Data Analysis

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

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.

đź’Ľ 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.

đź“– 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

Published on by Research Data Analysis

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.

đź’Ľ 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.

đź“– 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