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
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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

 

Madan Mohan Tito Ayyalasomayajula | Big Data Analytics | Excellence in Research

Dr. Madan Mohan Tito Ayyalasomayajula | Big Data Analytics | Excellence in Research

Doctorate at Infosys/Aspen University, Arizona, United States

Dr. Madan Mohan Tito Ayyalasomayajula is a distinguished professional with a remarkable career in computer science and technology. His extensive background includes significant roles as a Senior Technology Architect, Research Scholar, and Industry Expert. Dr. Tito’s contributions span across academia, industry, and technology innovation, showcasing a profound impact on various domains such as artificial intelligence, machine learning, and system architecture.

Profiles

Scopus Profile
Orcid Profile

🌳Academic Background 

Dr. Ayyalasomayajula is a seasoned technology architect and research scholar with over 20 years of experience in system architecture, cloud technologies, big data, and AI/ML. He holds a Doctor of Science in Computer Science from Aspen University and has contributed extensively to both academia and industry through his work in various roles, including as a Senior Technology Architect at Infosys Ltd., and previously as an Enterprise Architect at Walgreens and Toyota Motors North America.

🎓 Education

Dr. Madan Mohan Tito Ayyalasomayajula holds a Doctor of Science in Computer Science from Aspen University, Phoenix, Arizona (Aug 2019 – May 2024). He completed his Master of Technology in Computer Science & Engineering at Osmania University (2003 – 2005) and his Master of Computer Applications from Osmania University (1998 – 2001). His undergraduate degree, a Bachelor of Science, is from Andhra University (1994 – 1997).

🏅 Memberships

He is a Senior Member of IEEE and IEEE Computer Society, and a member of MIET (The Institute of Engineering & Technology), AET (International Academy of Engineering & Technology), and IACSIT (International Association of Computer Science and Information Technology). Additionally, he is affiliated with IASA Global (International Association for Software Architects), IAENG (International Association of Engineers), and serves as an Editorial Member for ESP Journal of Engineering & Technology Advancements. His memberships extend to IOASD (International Organization for Academic and Scientific Development) and IET – AI TN Committee as a Research Officer, and he is also a Technical Advisory Board Member at Aspen University, Arizona, USA.

💡 Profile

Dr. Tito is a Doctor of Science in Computer Science and a Senior Technology Architect with over 20 years of experience. He is a Research Scholar, Author, and Peer Reviewer, with expertise in building and implementing machine learning models, leveraging natural language processing and computer vision techniques, and applying predictive analytics using AI and ML technologies. His experience spans Architecture, System Analysis, Development, and Project Planning, with notable skills in Azure & AWS cloud technologies, Big Data, IoT, and Advanced Databases.

📰 Media Articles

He has written media articles on topics including the power of machine learning in production, the role of AI in managing big data, and the future of manufacturing with Explainable AI. His other articles discuss AI’s potential in diagnostics and address the skepticism surrounding AI advancements.

🏆 Awards

Dr. Tito has been recognized with the Aegis Graham Bell Award for his work on Revenue Plus and Incremental Revenue Through Incremental Sales (IRIS) products at Mahindra Comviva.

🛠️ Patents

He holds patents for various innovative technologies, including predictive maintenance systems, smart healthcare devices using AI, and early prediction algorithms for kidney diseases.

💼 Work Experience

He has held significant positions at Infosys Ltd. as a Senior Technology Architect, Walgreens / OmTek as an Enterprise Architect, Toyota Motors North America as an Enterprise Cloud Solutions Architect, and Mahindra Comviva as a Principal Architect. His roles have involved delivering digital services, architectural design, system optimization, and leading R&D initiatives across multiple domains.

🎤 Presentations and Exhibitions

Dr. Tito has been a guest speaker and keynote presenter at various conferences and workshops, including GIET University, SR University, and international AI conferences. He has also participated in podcasts and interviews, sharing his expertise on AI and technology.

🏅 Judging

He has served as a judge at numerous science and technology events, including the Ohio State Science Day, Regeneron ISEF, and Technovation for Girls. Additionally, he contributes as a peer reviewer for various scholarly journals and conferences.

🧑‍🏫 Mentorships

Dr. Tito is actively involved in mentoring through platforms such as Mentoring Club, ADPList, and the Global Mentoring Initiative.

📖 Publication

Explainable Artificial Intelligence (XAI) for Emotion Detection
    • Authors: Ayyalasomayajula, M.M.T.; Ayyalasomayajula, S.; Pandey, J.K.
    • Journal/Book: Book chapter in DOI: 10.4018/979-8-3693-4143-8.ch010
    • Year: 2024
Exploring Strategies for Privacy-Preserving Machine Learning in Distributed Environments
    • Authors: Dodda, S.; Kumar, A.; Kamuni, N.; Ayyalasomayajula, M.M.T.
    • Journal/Conference: 3rd International Conference on Artificial Intelligence for Internet of Things (AIIoT 2024)
    • Year: 2024
Implementing Convolutional Neural Networks for Automated Disease Diagnosis in Telemedicine
    • Authors: Ayyalasomayajula, M.M.T.; Tiwari, A.; Arora, R.K.; Khan, S.
    • Journal/Conference: 3rd IEEE International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE 2024)
    • Year: 2024
Optimizing Photometric Light Curve Analysis: Evaluating Scipy’s Minimize Function for Eclipse Mapping of Cataclysmic Variables
    • Author: Dr. Madan Mohan Tito Ayyalasomayajula
    • Journal: Journal of Electrical Systems
    • Year: 2024
Reddit Social Media Text Analysis for Depression Prediction: Using Logistic Regression with Enhanced Term Frequency-Inverse Document Frequency Features
    • Authors: Madan Mohan Tito Ayyalasomayajula; Akshay Agarwal; Shahnawaz Khan
    • Journal: International Journal of Electrical and Computer Engineering (IJECE)
    • Year: 2024