Paraskumar Patel | Business Intelligence and Analytics | Editorial Board Member

Mr. Paraskumar Patel | Business Intelligence and Analytics | Editorial Board Member

Mr. Paraskumar Patel at Fractal.ai – United States

👨‍🎓 Profiles

🌟 Early Academic Pursuits

Paraskumar Patel’s academic journey is marked by a commitment to blending engineering and technology. He started with a Bachelor of Technology in Chemical Engineering from Dharmsinh Desai University in India, where he developed a strong foundation in engineering principles. His quest for deeper knowledge led him to Carnegie Mellon University, where he earned a Master of Chemical Engineering. This advanced degree allowed Patel to explore complex engineering systems and applications. Recognizing the importance of data technology, he pursued a Master of Science in Information Technology from the University of the Cumberlands in the USA. This educational path not only enhanced his technical skills but also equipped him to integrate chemical engineering with cutting-edge data analytics.

💼 Professional Endeavors

Paraskumar Patel’s professional journey is highlighted by his impactful roles across various industries. As a Senior Data Engineer at Fractal.ai, Patel has made significant strides in data migration, report optimization, and advanced analytics. His work with high-profile clients such as USAA, Suncor, Humana, Microsoft, and PepsiCo showcases his expertise in operationalizing complex models, migrating reports to Power BI, and enhancing data retrieval processes. Patel’s ability to streamline data processes and improve report efficiency has been instrumental in helping organizations make data-driven decisions and enhance operational performance.

📝 Contributions and Research Focus

Patel’s scholarly contributions are extensive and influential. His research addresses critical areas in data visualization, engineering challenges, and privacy-preserving analytics techniques. With publications in prestigious journals like the International Journal of Science and Research and the European Journal of Advances in Engineering and Technology, Patel has explored topics such as integrating privacy-preserving techniques, balancing creativity with compliance, and optimizing Power BI functionalities. His work not only contributes to the academic field but also provides practical solutions to complex data challenges, reflecting his thought leadership and commitment to advancing data engineering practices.

🏆 Accolades and Recognition

Paraskumar Patel’s work has earned him notable recognition within the data engineering community. His innovative approaches to optimizing data retrieval and enhancing report efficiency have been praised by clients and peers. Patel’s research publications are widely cited, underscoring the impact of his contributions on both academic and professional circles. His ability to bridge technical expertise with practical solutions has established him as a leading figure in data engineering, garnering accolades for his problem-solving skills and dedication to advancing the field.

🌍 Impact and Influence

Patel’s influence on the field of data engineering is profound. His work has not only improved data processes and access for various organizations but also set new standards for data-driven decision-making. By addressing complex data challenges and integrating advanced technologies, Patel has driven positive change across multiple sectors. His contributions have shaped how organizations approach data analytics, highlighting the importance of combining technical expertise with innovative solutions to enhance operational efficiencies and data accessibility.

🔮 Legacy and Future Contributions

As Paraskumar Patel continues to advance his career, his legacy in data engineering is defined by his innovative spirit and thought leadership. His contributions have left a lasting impact on the organizations he has worked with, improving their data processes and overall performance. Looking ahead, Patel’s focus on emerging challenges and his continued research efforts will likely drive further advancements in the field. His ability to merge engineering expertise with cutting-edge data analytics positions him as a key figure in shaping the future of data engineering, inspiring future generations of data professionals with his commitment to innovation and excellence.

📖 Publications

Seyedeh Azadeh Fallah Mortezanejad | Predictive Analytics | Best Researcher Award

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