Mohammad Reza Ahangari | Big Data Analytics | Best Researcher Award

Mr. Mohammad Reza Ahangari | Big Data Analytics | Best Researcher Award

Mr. Mohammad Reza Ahangari at ministry of education, Iran

👨‍🎓 Profile

🧠 Early Academic Pursuits

Dr. Mohammad Reza Ahangari’s journey into the realm of mathematics began with his undergraduate studies at Isfahan University of Technology, where he pursued a Bachelor of Applied Mathematics from 2003 to 2008. This foundational education provided him with a solid grounding in mathematical theories and applications. Following his undergraduate studies, Dr. Ahangari continued his academic journey at Azad University in Mashhad, Razavi Khorasan, earning a Master of Applied Mathematics between 2009 and 2012. His master’s program allowed him to delve deeper into complex mathematical concepts and research methodologies. His quest for knowledge did not end there; he embarked on a PhD in Applied Mathematics at Payam-e-Noor University, which he pursued from 2016 to 2024. His doctoral research focused on advanced mathematical models and optimization techniques, further cementing his expertise in the field.

💼 Professional Endeavors

Since September 2009, Dr. Ahangari has been a dedicated Mathematics Teacher with the Ministry of Education in Mashhad, Razavi Khorasan, Iran. Over the past 15 years, he has demonstrated a profound commitment to fostering a positive learning environment. His teaching approach is characterized by innovative lesson plans that cater to diverse learning styles, ensuring that all students have the opportunity to excel. Dr. Ahangari has consistently utilized various teaching methodologies and educational technologies to enhance student engagement and understanding of complex mathematical concepts. His ability to create engaging and effective learning experiences has made him a respected figure in the educational community.

🔬 Contributions and Research Focus

Dr. Ahangari’s research has made significant contributions to the field of applied mathematics. His work includes the development and application of advanced mathematical models and optimization techniques. Notably, he co-authored the paper “A Generalized Optimization-Based Generative Adversarial Network,” published in Expert Systems with Applications in 2024. This research explores innovative approaches to optimization in generative adversarial networks, demonstrating Dr. Ahangari’s expertise in integrating mathematics with cutting-edge technology. Additionally, his work on fuzzy-based structural similarity indices in meteorology, as detailed in his paper “Utilizing Generative Adversarial Networks Using a Category of Fuzzy-Based Structural Similarity Indices for Constructing Datasets in Meteorology,” showcases his ability to apply mathematical theories to real-world problems. His research contributions reflect a deep understanding of both theoretical and practical aspects of mathematics.

🏆 Accolades and Recognition

Dr. Ahangari’s dedication to mathematics education and research has been recognized through various accolades. He earned his Mathematics Teacher Certification in 2024, a testament to his expertise and commitment to the field. In 2023, he participated in professional development programs focused on advancing mathematics education, further highlighting his commitment to staying at the forefront of educational practices. His research contributions have also been acknowledged through publications in esteemed journals and presentations at significant seminars, such as the 6th Seminar on Control & Optimization in Birjand, Iran.

🌟 Impact and Influence

Dr. Ahangari’s impact on mathematics education extends beyond his teaching role. His innovative curriculum development and creation of interactive learning modules have significantly enhanced the educational experience for his students. His commitment to nurturing critical thinking and problem-solving skills in students has prepared them for future academic and professional challenges. By integrating advanced mathematical concepts with practical applications, Dr. Ahangari has influenced both his students and the broader educational community.

🌱 Legacy and Future Contributions

Looking forward, Dr. Ahangari aims to continue his contributions to both mathematics education and research. His ongoing projects include the development of a comprehensive math curriculum guide and the creation of interactive math learning modules. These initiatives reflect his dedication to enhancing educational resources and methodologies. As he continues to advance his research and educational practices, Dr. Ahangari is poised to leave a lasting legacy in the field of mathematics. His work not only advances mathematical knowledge but also inspires future generations of students and educators.

📖 Publications

Manganese doped La0.8Ba0.2FeO3 perovskite oxide as an efficient electrode material for supercapacitor

    • Authors: Asadi, F., Ahangari, M., Mostafaei, J., Asghari, E., Niaei, A.
    • Journal: Journal of Alloys and Compounds
    • Year: 2024

A generalized optimization-based generative adversarial network

    • Authors: Farhadinia, B., Ahangari, M.R., Heydari, A., Datta, A.
    • Journal: Expert Systems with Applications
    • Year: 2024

Utilizing Generative Adversarial Networks Using a Category of Fuzzy-Based Structural Similarity Indices for Constructing Datasets in Meteorology

    • Authors: Farhadinia, B., Ahangari, M.R., Heydari, A.
    • Journal: Mathematics
    • Year: 2024

Effect of Pd doping on the structural properties and supercapacitor performance of La0.8Sr0.2Cu0.7Mn0.3O3 and La0.8Sr0.2Cu0.4Mn0.6O3 as electrode materials

    • Authors: Ahangari, M., Mostafaei, J., Zakerifar, H., Asghari, E., Niaei, A.
    • Journal: Electrochimica Acta
    • Year: 2023

Machine learning-based life cycle optimization for the carbon dioxide methanation process: Achieving environmental and productivity efficiency

    • Authors: Sayyah, A., Ahangari, M., Mostafaei, J., Nabavi, S.R., Niaei, A.
    • Journal: Journal of Cleaner Production
    • Year: 2023

Investigation of structural and electrochemical properties of SrFexCo1-xO3-δ perovskite oxides as a supercapacitor electrode material

    • Authors: Ahangari, M., Mostafaei, J., Sayyah, A., Delibas, N., Niaei, A.
    • Journal: Journal of Energy Storage
    • Year: 2023

Application of SrFeO3 perovskite as electrode material for supercapacitor and investigation of Co-doping effect on the B-site

    • Authors: Ahangari, M., Mahmoodi, E., Delibaş, N., Asghari, E., Niaei, A.
    • Journal: Turkish Journal of Chemistry
    • Year: 2022

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